WO2024027388A1 - 信道状态信息的上报方法及通信装置 - Google Patents

信道状态信息的上报方法及通信装置 Download PDF

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Publication number
WO2024027388A1
WO2024027388A1 PCT/CN2023/103330 CN2023103330W WO2024027388A1 WO 2024027388 A1 WO2024027388 A1 WO 2024027388A1 CN 2023103330 W CN2023103330 W CN 2023103330W WO 2024027388 A1 WO2024027388 A1 WO 2024027388A1
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Prior art keywords
covariance matrix
channel
matrix
indicate
information
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PCT/CN2023/103330
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English (en)
French (fr)
Inventor
范利
蓝瑞宁
陈淑菁
秦启波
种稚萌
金黄平
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华为技术有限公司
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Publication of WO2024027388A1 publication Critical patent/WO2024027388A1/zh

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Classifications

    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station
    • H04B7/0613—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission
    • H04B7/0615—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal
    • H04B7/0619—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station using simultaneous transmission of weighted versions of same signal using feedback from receiving side
    • H04B7/0621—Feedback content
    • H04B7/0626—Channel coefficients, e.g. channel state information [CSI]
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/0413—MIMO systems
    • H04B7/0417—Feedback systems
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04B—TRANSMISSION
    • H04B7/00—Radio transmission systems, i.e. using radiation field
    • H04B7/02—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas
    • H04B7/04—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas
    • H04B7/06—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the transmitting station

Definitions

  • the present application relates to the field of communications, and in particular, to a method and communication device for reporting channel state information.
  • MIMO Multiple input and multiple output
  • LTE long term evolution
  • 5G fifth generation new radio
  • CSI channel state information
  • the terminal device can receive a reference signal from the network device, and calculate the covariance matrix corresponding to the channel matrix based on the reference signal, and then calculate the covariance matrix corresponding to the channel matrix based on the reference signal.
  • the covariance matrix constructs the feature basis.
  • the terminal device feeds back the CSI, it can feed back the feature base and the coefficient matrix of the feature base to the network device.
  • the network device can restore the CSI by combining the feature base and the coefficient matrix of the feature base.
  • the terminal equipment determines the feature base, taking advantage of the sparse characteristics of the channel, and needs to feedback the relevant characteristics of airspace information on different subbands (subbands), that is to say, the selected feature base and feature base need to be reported
  • subbands subbands
  • the superposition coefficient of the full bandwidth, the air interface overhead is large. How to feed back CSI more efficiently is an urgent problem that needs to be solved in the application of MIMO technology.
  • Embodiments of the present application provide a method and communication device for reporting channel state information, which can reduce overhead.
  • the first aspect is to provide a method for reporting channel status information.
  • the method for reporting channel state information includes: the first device receives a reference signal from the second device. The first device determines the first indication information according to the reference signal, and sends the first indication information to the second device. Wherein, the first indication information is used to construct a first covariance matrix corresponding to a channel matrix, and the channel matrix is used to indicate channel state information of a channel between the first device and the second device.
  • the first device sends the first instruction information used to construct the covariance matrix corresponding to the channel matrix to the second device, which can avoid the reporting being directly used to restore the channel state information.
  • the second device may determine the first covariance matrix corresponding to the channel matrix according to the first indication information, and determine the characteristic base according to the covariance matrix corresponding to the channel matrix.
  • the dimension of the channel matrix may be M ⁇ N dimensions.
  • the first device determines the first indication information based on the reference signal, which may include: the first device determines a channel matrix based on the reference signal, and determines a channel column vector based on the channel matrix, and then, the first device determines the first indication information based on the channel column vector.
  • the first indication information may be used to indicate the superposition coefficient and the codebook vector, and the superposition coefficient and the codebook vector are used to determine the first covariance matrix.
  • the first covariance matrix and the actual covariance matrix corresponding to the channel matrix satisfy a preset optimization model. In this way, the data amount of the first indication information can be reduced, thereby further reducing feedback overhead.
  • the preset optimization model may include: stL ⁇ Lmax .
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • R is the actual space-frequency joint covariance matrix corresponding to the channel matrix
  • ⁇ means the summation operation
  • 0 ⁇ l ⁇ L And l is an integer.
  • ⁇ l is the l-th superposition coefficient
  • w l is the l-th codebook vector
  • st is the constraint condition
  • L is the number of channel multipaths
  • L max is the maximum value of L
  • both L and L max are integers greater than 0.
  • the first device determines the channel matrix and obtains R by measuring the reference signal
  • the corresponding ⁇ l and w l can be obtained through the above optimization model, so that the first space-frequency joint covariance matrix corresponds to the channel matrix
  • the error between the actual space-frequency joint covariance matrices should be as small as possible. That is to say, the first indication information can be determined based on the solution results of the preset optimization model.
  • the superposition coefficient may include a first superposition coefficient used to indicate the characteristics of the angular delay power spectrum
  • the codebook vector may include first information used to indicate the angular delay
  • the first superposition coefficient and the first information are used to The first space-frequency joint covariance matrix is determined
  • the preset optimization model includes: a first optimization model that satisfies the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first device determining the first indication information used to construct the first space-frequency joint covariance matrix and sending it to the second device, it is possible to avoid reporting a large amount of information that can be directly used to restore channel state information, such as space-frequency joint
  • the superposition coefficient corresponding to the feature base and the space-frequency joint feature base can be determined.
  • the second device can determine the first space-frequency joint covariance matrix corresponding to the channel matrix according to the first indication information, and determine the space-frequency joint feature base according to the first space-frequency joint covariance matrix corresponding to the channel matrix, thereby reducing feedback
  • the amount of data can be reduced, thereby reducing feedback overhead and improving CSI feedback efficiency.
  • the first optimization model includes: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual space-frequency joint covariance matrix corresponding to the channel matrix, ⁇ represents the summation operation, 0 ⁇ l 0 ⁇ L 0 , and l 0 is an integer.
  • the first device determines the channel matrix by measuring the reference signal, and obtains In the case of , the corresponding can be obtained through the above first optimization model as well as and The error between the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix is made as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset first optimization model.
  • the superposition coefficient may include a second superposition coefficient indicating a characteristic of the angle power spectrum
  • the codebook vector may include second information indicating an angle.
  • the second superposition coefficient and the second information are used to determine the first spatial covariance matrix.
  • the preset optimization model includes: a preset second optimization model that satisfies the relationship between the first spatial covariance matrix and the actual spatial covariance matrix corresponding to the channel matrix.
  • the first device can avoid reporting a large amount of information directly used to restore the channel state information, such as the airspace feature base and the airspace feature base.
  • the corresponding superposition coefficient For example, the second device can determine the first spatial covariance matrix corresponding to the channel matrix according to the first indication information, and determine the spatial characteristic base according to the first spatial covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, thereby reducing Feedback overhead and improve feedback efficiency.
  • the second optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual spatial covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 1 second superposition coefficient, is the steering vector corresponding to the l 1th multipath angle, for The conjugate transpose of , st is the constraint condition, L 1 is the number of channel multipaths in the air domain, is the maximum value of L 1 , L 1 , are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1 , and l 1 is an integer.
  • the first device determines the channel matrix by measuring the reference signal and obtains In the case of , the corresponding can be obtained through the above second optimization model and The error between the first spatial domain covariance matrix and the actual spatial domain covariance matrix corresponding to the channel matrix is made as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset first optimization model.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include third information used to indicate the delay
  • the third superposition coefficient and the third information are used to determine the third A frequency domain covariance matrix.
  • the preset optimization model includes: a third optimization model that is satisfied between the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix.
  • the first device can avoid reporting a large amount of information directly used to restore the channel state information, such as the frequency domain characteristic base and frequency domain information.
  • the superposition coefficient corresponding to the domain feature base For example, the second device can determine the first frequency domain covariance matrix according to the first indication information, and determine the frequency domain feature base according to the first frequency domain covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, thereby reducing feedback overhead to improve feedback efficiency.
  • the third optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual frequency domain covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 2nd third superposition coefficient, is the l 2th phase change vector, for The conjugate transpose of , st is the constraint condition, L 2 is the number of channel multipaths in the frequency domain, is the maximum value of L 2 , L 2 , are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2 , and l 2 is an integer.
  • the first device determines the channel matrix by measuring the reference signal and obtains
  • the above-mentioned second optimization model can be used to make the error between the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset third optimization model.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum and a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include second information used to indicate the angle.
  • third information used to indicate the time delay, the second superposition coefficient and the second information are used to determine the first spatial domain covariance matrix, and the third superposition coefficient and the third information are used to determine the first frequency domain covariance matrix.
  • the preset optimization model includes: a second optimization model that satisfies the relationship between the first spatial covariance matrix and the actual spatial covariance matrix corresponding to the channel matrix, and the actual frequency domain covariance corresponding to the first frequency domain covariance matrix and the channel matrix. The third optimization model satisfied between matrices.
  • the first device can avoid reporting a large amount of information directly used to restore the channel state information.
  • the first spatial domain covariance matrix and the first frequency domain covariance matrix are determined based on the first indication information from the first device.
  • the second device can determine the first spatial domain covariance matrix and the first spatial domain covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first frequency domain covariance matrix determines the spatial domain characteristic base according to the first spatial domain covariance matrix corresponding to the channel matrix, and determines the frequency domain characteristic base according to the first frequency domain covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, thereby It can reduce feedback overhead and improve feedback efficiency.
  • the second optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual spatial covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 1 second superposition coefficient, is the steering vector corresponding to the l 1th multipath angle, for The conjugate transpose of , st is the constraint condition, L 1 is the number of channel multipaths in the air domain, is the maximum value of L 1 , L 1 , are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1 , and l 1 is an integer.
  • the third optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual frequency domain covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 2nd third superposition coefficient, is the l 2th phase change vector, for The conjugate transpose of , st is the constraint condition, L 2 is the number of channel multipaths in the frequency domain, is the maximum value of L 2 , L 2 , are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2 , and l 2 is an integer.
  • the first device sending the first indication information to the second device may include: the first device sending the first indication information to the second device according to the first cycle.
  • the method provided in the first aspect may further include: the first device sending second indication information to the second device according to a second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined according to the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the first decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and the order of the first row elements of the space-frequency joint feature base of the first space-frequency joint covariance matrix decomposition. Type, such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantization vector after quantization of the first row elements of the first P columns in the space-frequency joint feature base of the first decomposition result.
  • the first decomposition result can be uniquely determined, so that the space-frequency joint feature base determined by the second device can be combined with the space-frequency joint used to determine the first feedback coefficient.
  • the feature base is consistent, thereby improving the accuracy of channel state information.
  • the feature vectors in the feature base are arranged from large to small in energy, the feature vectors (column vectors) with larger energy can be selected from the empty joint feature base to restore the channel state information, thereby taking into account the reporting overhead and recovery The accuracy of the channel state information.
  • the space-frequency joint feature base can be combined with the first feedback coefficient, that is, the short period coefficient to enable the second device to restore the complete channel status information.
  • sending the first instruction information to the second device by the first device includes: the first device sends the first instruction information to the second device according to the third period.
  • the method provided in the first aspect may further include: the first device sending third indication information to the second device according to a fourth cycle.
  • the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined according to the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the spatial feature base of the first spatial covariance matrix.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the frequency domain feature base of the first frequency domain covariance matrix, such as positive real numbers.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base of the second decomposition result.
  • K is a positive integer.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base of the third decomposition result.
  • D is a positive integer.
  • the combination of the spatial domain characteristic base and the frequency domain characteristic base with the second feedback coefficient that is, the short-period feedback coefficient, enables the second device to restore complete channel state information.
  • the second aspect is to provide a method for reporting channel status information.
  • the method for reporting channel state information may include: the second device receives first indication information from the first device.
  • the first indication information is used to construct a covariance matrix corresponding to a channel matrix, and the channel matrix is used to indicate channel state information of a channel between the first device and the second device.
  • the second device determines the first covariance matrix corresponding to the channel matrix according to the first indication information.
  • the second device can determine the first covariance matrix by receiving the first instruction information from the first device for constructing the covariance matrix corresponding to the channel matrix. Avoid transmitting a large amount of information directly used to restore channel state information, thereby reducing feedback overhead and improving CSI feedback efficiency.
  • the first indication information may include a superposition coefficient and a codebook vector.
  • the second device determines the first covariance matrix corresponding to the channel matrix according to the first indication information, which may include: the second device determines the first covariance matrix according to the superposition coefficient and the codebook vector.
  • the superposition coefficient includes a first superposition coefficient used to indicate the characteristics of the angular delay power spectrum
  • the codebook vector includes first information used to indicate the angular delay.
  • the second device determines the first covariance matrix corresponding to the channel matrix according to the superposition coefficient and the codebook vector, including: the second device determines the first space-frequency joint covariance matrix according to the first superposition coefficient and the first information.
  • receiving the first indication information from the first device by the second device may include: the second device receives the first indication information from the first device according to the first cycle.
  • the method provided in the second aspect may further include: the second device receiving second indication information from the first device according to a second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined according to the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the method provided in the second aspect may further include: the second device determines an effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the effective space-frequency joint feature base includes the first P columns of the space-frequency joint feature base, and P is a positive integer.
  • the second device determines the channel matrix according to the effective space-frequency joint characteristic base and the first feedback coefficient. In this way, when the feature vectors in the space-frequency joint feature base are arranged from large to small in energy, the first device can select a feature vector (column vector) with larger energy from the space-frequency joint feature base to restore the channel state information. , thereby taking into account the reporting overhead and the accuracy of the restored channel state information.
  • the first decomposition rule may include: an arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and a first The type of the first row elements of the space-frequency joint covariance matrix decomposition of the space-frequency joint feature basis, such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantized vector of the first row elements of the first P columns in the space-frequency joint feature base decomposed by the first space-frequency joint covariance matrix.
  • P is a positive integer.
  • the second device can combine the effective space-frequency joint feature base with the first feedback coefficient, that is, the short period coefficient to restore the complete channel state information.
  • the second device determines the effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule, which may include: the second device determines the first space-frequency joint feature base according to the first decomposition rule and the first quantization vector.
  • the superposition coefficient may include a second superposition coefficient indicating a characteristic of the angle power spectrum
  • the codebook vector may include second information indicating an angle.
  • the second device determines the first covariance matrix according to the superposition coefficient and the codebook vector, which may include: the second device determines the first spatial covariance matrix according to the second superposition coefficient and the second information.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include third information used to indicate the delay.
  • the second device determines the first covariance matrix according to the superposition coefficient and the codebook vector, which may include: the second device determines the first frequency domain covariance matrix according to the third superposition coefficient and third information.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum and a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include second information used to indicate the angle. and third information indicating the delay.
  • the second device determines the first covariance matrix according to the superposition coefficient and the codebook vector, including: the second device determines the first spatial covariance matrix according to the second superposition coefficient and the second information.
  • the second device determines the first frequency domain covariance matrix according to the third superposition coefficient and the third information.
  • receiving the first indication information from the first device by the second device may include: the second device receives the first indication information from the first device according to a third period.
  • the method provided in the second aspect may further include: the second device receiving third indication information from the first device according to a fourth cycle.
  • the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined based on the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the characteristic basis of the first spatial covariance matrix.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the frequency domain feature base of the first frequency domain covariance matrix, such as positive real numbers.
  • the method provided in the second aspect may also include: the second device determines the effective airspace characteristic base according to the second decomposition rule.
  • the second device determines the effective frequency domain characteristic base according to the third decomposition rule.
  • the second device determines the channel state information based on the effective spatial domain characteristic base, the effective frequency domain characteristic base and the second feedback coefficient.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base decomposed by the first spatial covariance matrix.
  • the second device determines the effective airspace feature base according to the second decomposition rule, including: the second device determines the effective airspace feature base according to the second decomposition rule and the second quantization vector.
  • the effective spatial feature base includes the first K columns of the spatial feature base of the first spatial covariance matrix.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base decomposed by the first frequency domain covariance matrix.
  • the method provided in the second aspect may further include: the second device determines the effective frequency domain feature base according to the third decomposition rule and the third quantization vector.
  • the effective frequency domain feature base includes the first D columns of the frequency domain feature base of the first frequency domain covariance matrix.
  • the third decomposition result can be uniquely determined, so that the frequency domain feature base determined by the second device can be consistent with the frequency domain feature base used to determine the second feedback coefficient. , thereby improving the accuracy of channel state information.
  • the second device can combine the spatial domain feature base, the frequency domain feature base and the second feedback coefficient, that is, the short period feedback coefficient, from And restore complete channel status information.
  • a communication device in a third aspect, includes: a processing module and a transceiver module.
  • the transceiver module is used to receive the reference signal from the second device.
  • a processing module configured to determine the first indication information according to the reference signal.
  • the first indication information is used to construct a first covariance matrix corresponding to a channel matrix, and the channel matrix is used to indicate channel state information of a channel between the communication device and the second device.
  • the transceiver module is configured to send the first indication information to the second device.
  • the first indication information may include a superposition coefficient and a codebook vector, and the superposition coefficient and the codebook vector are used to determine the first covariance matrix.
  • the first covariance matrix and the actual covariance matrix corresponding to the channel matrix satisfy a preset optimization model.
  • preset optimization models can include: stL ⁇ Lmax .
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • R is the actual space-frequency joint covariance matrix corresponding to the channel matrix
  • ⁇ means the summation operation
  • 0 ⁇ l ⁇ L means the summation operation
  • 0 ⁇ l ⁇ L means the summation operation
  • 0 ⁇ l ⁇ L means the summation operation
  • l is an integer.
  • ⁇ l is the l-th superposition coefficient
  • w l is the l-th codebook vector
  • st is the constraint condition
  • L is the number of channel multipaths
  • L max is the maximum value of L
  • both L and L max are integers greater than 0.
  • the superposition coefficient may include a first superposition coefficient used to indicate the characteristics of the angle delay power spectrum
  • the codebook vector may include first information used to indicate the angle
  • the first superposition coefficient and the first information are used to determine the first
  • the preset optimization model includes: a first optimization model that satisfies the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual space-frequency joint covariance matrix corresponding to the channel matrix, ⁇ represents the summation operation, 0 ⁇ l 0 ⁇ L 0 , and l 0 is an integer.
  • the superposition coefficient may include a second superposition coefficient indicating a characteristic of the angular power spectrum
  • the codebook vector may include second information indicating an angle.
  • the second superposition coefficient and the second information are used to determine the first spatial covariance matrix.
  • the preset optimization model includes: a second optimization model that is satisfied between the first spatial covariance matrix and the actual spatial covariance matrix corresponding to the channel matrix.
  • the second optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual spatial covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 1 second superposition coefficient, is the steering vector corresponding to the l 1th multipath angle, for The conjugate transpose of , st is the constraint condition, L 1 is the number of channel multipaths in the air domain, is the maximum value of L 1 , L 1 , are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1 , and l 1 is an integer.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include third information used to indicate the delay
  • the third superposition coefficient and the third information are used to determine the third A frequency domain covariance matrix.
  • the preset optimization model includes: a third optimization model that is satisfied between the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix.
  • the third optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual frequency domain covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 2nd third superposition coefficient, is the l 2th phase change vector, for The conjugate transpose of , st is the constraint condition, L 2 is the number of channel multipaths in the frequency domain, is the maximum value of L 2 , L 2 , are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2 , and l 2 is an integer.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum and a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include second information used to indicate the angle.
  • third information used to indicate the time delay, the second superposition coefficient and the second information are used to determine the first spatial domain covariance matrix, and the third superposition coefficient and the third information are used to determine the first frequency domain covariance matrix.
  • the preset optimization model includes: the first spatial domain covariance matrix and the actual spatial domain covariance matrix corresponding to the channel matrix satisfy the preset second optimization model, and the first frequency domain covariance matrix and the actual frequency domain corresponding to the channel matrix The third optimization model satisfied between covariance matrices.
  • the second optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual spatial covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 1 second superposition coefficient, is the steering vector corresponding to the l 1th multipath angle, for The conjugate transpose of , st is the constraint condition, L 1 is the number of channel multipaths in the air domain, is the maximum value of L 1 , L 1 , are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1 , and l 1 is an integer.
  • the third optimization model may include: Among them, min means taking the minimum value, " ⁇ F " means taking the F norm, is the actual frequency domain covariance matrix corresponding to the channel matrix, and ⁇ represents the summation operation. is the l 2nd third superposition coefficient, is the l 2th phase change vector, for The conjugate transpose of , st is the constraint condition, L 2 is the number of channel multipaths in the frequency domain, is the maximum value of L 2 , L 2 , are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2 , and l 2 is an integer.
  • the transceiver module is specifically configured to send the first indication information to the second device according to the first cycle.
  • the transceiver module may also be configured to send the second indication information to the second device according to the second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined according to the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the first decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and the order of the first row elements of the space-frequency joint feature basis of the first space-frequency joint covariance matrix decomposition.
  • Type such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantization vector after quantization of the first row elements of the first P columns in the space-frequency joint feature base of the first decomposition result.
  • P is a positive integer.
  • the transceiver module is specifically configured to send the first indication information to the second device according to the third cycle.
  • the transceiver module may also be configured to send the third indication information to the second device according to the fourth cycle.
  • the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined according to the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the spatial feature basis of the first spatial covariance matrix, such as positive real numbers.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base of the second decomposition result.
  • K is a positive integer.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the frequency domain feature base of the first frequency domain covariance matrix.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base of the third decomposition result.
  • D is a positive integer.
  • the transceiver module may include a receiving module and a sending module. Wherein, the transceiver module is used to implement the sending function and receiving function of the communication device described in the third aspect.
  • the communication device described in the third aspect may further include a storage module that stores programs or instructions.
  • the processing module executes the program or instruction, the communication device can perform the channel state information reporting method described in the first aspect.
  • the communication device described in the third aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • a fourth aspect provides a communication device.
  • the communication device includes: a processing module and a transceiver module.
  • a transceiver module configured to receive first indication information from the first device.
  • the first indication information is used to construct a covariance matrix corresponding to a channel matrix, and the channel matrix is used to indicate channel state information of a channel between the first device and the second device.
  • processing module configured to determine the channel matrix pair according to the first indication information corresponding first covariance matrix.
  • the first indication information may include a superposition coefficient and a codebook vector.
  • a processing module specifically configured to determine the first covariance matrix according to the superposition coefficient and the codebook vector.
  • the superposition coefficient includes a first superposition coefficient used to indicate the characteristics of the angle delay power spectrum
  • the codebook vector includes first information used to indicate the angle.
  • the processing module is specifically configured to determine the first space-frequency joint covariance matrix according to the first superposition coefficient and the first information.
  • the transceiver module is specifically configured to receive the first instruction information from the first device according to the first cycle.
  • the transceiver module may also be configured to receive second indication information from the first device according to the second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined according to the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the processing module may also be configured to determine an effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the effective space-frequency joint feature base includes the first P columns of the space-frequency joint feature base, and P is a positive integer. And, determine the channel matrix according to the effective space-frequency joint characteristic base and the first feedback coefficient.
  • the first decomposition rule may include: an arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and a first space-frequency joint characteristic basis of the first space-frequency joint covariance matrix decomposition.
  • the type of row elements such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantized vector of the first row elements of the first P columns in the space-frequency joint feature base decomposed by the first space-frequency joint covariance matrix.
  • P is a positive integer.
  • the processing module is specifically configured to determine an effective space-frequency joint feature basis of the first space-frequency joint covariance matrix according to the first decomposition rule and the first quantization vector.
  • the superposition coefficient may include a second superposition coefficient indicating a characteristic of the angular power spectrum
  • the codebook vector may include second information indicating an angle.
  • a processing module specifically configured to determine the first spatial covariance matrix according to the second superposition coefficient and the second information.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum, and the codebook vector includes third information used to indicate the delay.
  • a processing module specifically configured to determine the first frequency domain covariance matrix according to the third superposition coefficient and the third information.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum and a third superposition coefficient used to indicate the characteristics of the delay power spectrum, and the codebook vector includes second information used to indicate the angle and Third information used to indicate the delay.
  • a processing module specifically configured to determine the first spatial covariance matrix according to the second superposition coefficient and the second information. And, determine the first frequency domain covariance matrix according to the third superposition coefficient and the third information.
  • the transceiver module is specifically configured to receive the first instruction information from the first device according to the first cycle.
  • the transceiver module may also be configured to receive third indication information from the first device according to the fourth cycle.
  • the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined based on the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the spatial feature base of the first spatial covariance matrix.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the frequency domain feature base of the first frequency domain covariance matrix, such as positive real numbers.
  • the processing module can also be used to determine the effective airspace feature base according to the second decomposition rule. According to the third decomposition rule, the effective frequency domain characteristic base is determined. And, determine the channel state information according to the effective spatial domain characteristic base, the effective frequency domain characteristic base and the second feedback coefficient.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base decomposed by the first spatial covariance matrix.
  • the processing module is specifically configured to determine the effective spatial feature base according to the second decomposition rule and the second quantization vector.
  • the effective spatial feature base includes the first K columns of the spatial feature base of the first spatial covariance matrix.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base decomposed by the first frequency domain covariance matrix.
  • the processing module is specifically configured to determine the effective frequency domain feature base according to the third decomposition rule and the third quantization vector.
  • the effective frequency domain feature base includes the first D columns of the frequency domain feature base of the first frequency domain covariance matrix.
  • the transceiver module may include a receiving module and a sending module. Wherein, the transceiver module is used to implement the sending function and receiving function of the communication device described in the fourth aspect.
  • the communication device described in the fourth aspect may further include a storage module that stores programs or instructions.
  • the processing module executes the program or instruction, the communication device can perform the channel state information reporting method described in the first aspect.
  • the communication device described in the fourth aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • a communication device configured to perform the channel state information reporting method described in any one of the implementations of the first aspect to the second aspect.
  • the communication device described in the fifth aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • the communication device described in the fifth aspect includes a module, unit, or means corresponding to the method for reporting channel state information described in any one of the first to second aspects.
  • the module or unit , or means can be implemented by hardware, software, or by hardware executing corresponding software implementation.
  • the hardware or software includes one or more modules or units for performing functions involved in the above method for reporting channel state information.
  • a sixth aspect provides a communication device.
  • the communication device includes: a processor, configured to perform the channel state information reporting method described in any one of the possible implementations of the first aspect to the second aspect.
  • the communication device described in the sixth aspect may further include a transceiver.
  • the transceiver can be a transceiver circuit or an interface circuit.
  • the transceiver can be used for the communication device described in the sixth aspect to communicate with other communication devices.
  • the communication device described in the sixth aspect may further include a memory.
  • This memory can be integrated with the processor or provided separately.
  • the memory may be used to store computer programs and/or data involved in the reporting method of channel state information described in any one of the first to second aspects.
  • the communication device described in the sixth aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • a communication device in a seventh aspect, includes: a processor, the processor is coupled to a memory, and the processor is used to execute a computer program stored in the memory, so that the communication device executes any one of the possible implementation methods of the first aspect to the second aspect. Method for reporting channel status information.
  • the communication device described in the seventh aspect may further include a transceiver.
  • the transceiver can be a transceiver circuit or an interface circuit.
  • the transceiver can be used for the communication device described in the seventh aspect to communicate with other communication devices.
  • the communication device described in the seventh aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • a communication device including: a processor and a memory.
  • the memory is used to store a computer program.
  • the processor executes the computer program, the communication device performs the channel state information reporting method described in any one of the implementations of the first to second aspects.
  • the communication device described in the eighth aspect may further include a transceiver.
  • the transceiver can be a transceiver circuit or an interface circuit.
  • the transceiver can be used for the communication device described in the eighth aspect to communicate with other communication devices.
  • the communication device described in the eighth aspect may be the first device described in the first aspect or the second device described in the second aspect, or a chip that may be disposed in the first device or the second device. (system) or other components or components, or a device containing the first device or the second device.
  • a communication device including: a processor.
  • the processor is configured to be coupled to the memory, and after reading the computer program in the memory, execute the channel state information reporting method as described in any one of the implementations of the first to second aspects according to the computer program.
  • the communication device described in the ninth aspect may further include a transceiver.
  • the transceiver can be a transceiver circuit or an interface circuit.
  • the transceiver can be used for the communication device described in the eleventh aspect to communicate with other communication devices.
  • the communication device described in the ninth aspect may be the first device or the second device, or it may be a chip (system) or other component or component that can be disposed in the first device or the second device, or it may be It is a device including the first device or the second device, which is not limited in this application.
  • a processor configured to execute the channel state information reporting method described in any possible implementation manner from the first aspect to the second aspect.
  • a communication system in an eleventh aspect, includes one or more first devices and one or more second devices.
  • a computer-readable storage medium including: a computer program or instructions.
  • the computer program or instruction When the computer program or instruction is run on the computer, the computer is caused to execute the channel state information reporting method described in any one of the possible implementations of the first aspect to the second aspect.
  • a computer program product including a computer program or instructions.
  • the computer program or instructions When the computer program or instructions are run on a computer, the computer is caused to execute any one of the possible implementation methods of the first aspect to the second aspect.
  • the above-mentioned reporting method of channel status information is provided, including a computer program or instructions.
  • Figure 1 is a schematic architectural diagram of a communication system provided by an embodiment of the present application.
  • Figure 2 is a schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application
  • Figure 3 is another schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application.
  • Figure 4 is a schematic diagram of multipath angles provided by an embodiment of the present application.
  • Figure 5 is another schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application.
  • Figure 6 is another schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application.
  • Figure 7 is another schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application.
  • Figure 8 is a schematic structural diagram of a communication device provided by an embodiment of the present application.
  • Figure 9 is a schematic second structural diagram of a communication device provided by an embodiment of the present application.
  • Steering vector is the response of all array elements of the array antenna to a narrowband signal source with unit energy.
  • Phase change vector a vector composed of a set of coefficients that represent phase changes.
  • Angular delay power spectrum the power distribution function of the channel in the angular delay domain.
  • Angle power spectrum the power distribution function of the channel in the angle domain.
  • Delay power spectrum the power distribution function of the channel in the delay domain.
  • Codebook vector a vector composed of a certain column of elements in the codebook.
  • WiFi wireless fidelity
  • V2X vehicle to everything
  • D2D device-to-device
  • Internet of Vehicles communication systems 4th generation (4G) mobile communication systems, such as long term evolution (LTE) systems, global interoperability for microwave access (WiMAX) communication systems
  • 5th generation, 5G mobile communication system
  • NR new radio
  • 6th generation, 6G sixth generation
  • MIMO Multiple input and multiple output
  • LTE long term evolution
  • 5G fifth generation new radio
  • a sending device such as a network device
  • the signal needs to be precoded based on the downlink channel state information (CSI) so that the signal passes through
  • CSI downlink channel state information
  • the terminal device receives a reference signal from the network device, determines the covariance matrix corresponding to the channel matrix based on the reference signal, and then determines the characteristic base corresponding to the channel matrix and the characteristic base correspondence based on the covariance matrix corresponding to the channel matrix. superposition coefficient.
  • the terminal device feeds back to the network device the characteristic base corresponding to the channel matrix and the superposition coefficient corresponding to the characteristic base. After receiving the feature base and the superposition coefficient corresponding to the feature base, the network device can recover the channel state information.
  • the above scheme takes advantage of the sparse characteristics of the channel in the air domain (i.e., angle domain) and frequency domain (i.e., delay domain), and needs to feedback the relevant characteristics of air domain information on different subbands (subbands). Therefore, it is necessary to report the characteristic base and full bandwidth ( full bandwidth) (including all subbands) superposition coefficient.
  • the terminal device can report the superposition coefficient in the following manner: the terminal device can divide the superposition coefficient into multiple parts, where some of the superposition coefficients are reported to the network device in a long period, and some of the superposition coefficients are reported to the network device in a short period. Among them, the number of superposition coefficients reported according to the long period is related to the number of feature vectors in the feature base and the number of superposition coefficients corresponding to each feature vector in the feature base.
  • C 1 is a coefficient matrix composed of the superposition coefficients corresponding to each eigenvector in the airspace feature base.
  • the number of elements in C 1 is: the number of eigenvectors in the airspace feature base and the superposition corresponding to each eigenvector in the airspace feature base. The product of the number of coefficients.
  • C 3 is a coefficient matrix composed of the superposition coefficients corresponding to each eigenvector in the frequency domain feature base.
  • the number of elements in C 3 is: the number of eigenvectors in the frequency domain feature base and the number of eigenvectors in the frequency domain feature base.
  • C 2 is a coefficient matrix composed of a set of superposition coefficients corresponding to each eigenvector in the spatial domain feature base and each eigenvector in the frequency domain feature base, or each eigenvector and frequency in the airspace feature base.
  • the total amount of superposition coefficients reported by the terminal equipment in a long period is the total amount of C 1 and C 3 . It can be seen that the superposition coefficient fed back by the terminal device in a long period has a large overhead and low feedback efficiency.
  • the duration of the long cycle is longer than the duration of the short cycle, for example, the duration of the long cycle is multiple integer multiples of the duration of the short cycle.
  • the short-period reporting is based on one reference signal measurement, and the long-period reporting is based on multiple reference signal measurements. The specific number of times is not specifically limited in this application.
  • the reference signal can be a channel state information-reference signal (CSI-RS), a synchronization signal and a physical broadcast channel block (synchronization signal and physical broadcast channel block) sent by the network device. , referred to as SSB), demodulation reference signal (demodulation reference signal, DMRS), etc., this application is not specifically limited here.
  • embodiments of the present application provide a method for reporting channel status information.
  • the first device can determine the first indication information according to the channel matrix. , and sent to the second device.
  • the first indication information is used to construct a first covariance matrix corresponding to the channel matrix.
  • the first indication information used to construct the covariance matrix corresponding to the channel matrix is reported to avoid reporting a large amount of information directly used to restore the channel state information, thereby reducing feedback overhead and improving CSI feedback efficiency.
  • the second device can determine the first covariance matrix corresponding to the channel matrix according to the first indication information, and determine the characteristic base and the superposition coefficient corresponding to the characteristic base according to the first covariance matrix corresponding to the channel matrix. Further, the characteristic base and The superposition coefficients corresponding to the characteristic base can be combined with short-period coefficients to restore complete channel state information.
  • FIG. 1 is a schematic architectural diagram of a communication system to which the channel state information reporting method provided by the embodiment of the present application is applicable.
  • the communication system includes a first device (101a, 101b) and a second device 102. Communication is possible between the second device 102 and the first device 101a, and between the second device 102 and the first device 101b.
  • the second device 102 is a device that sends data
  • the first device (101a, 101b) is a device that receives data
  • the second device 102 may be a network device or a terminal device
  • the first device (101a, 101b) may be a network device or a terminal device.
  • the first device (101a, 101b) is a network device, and the second device 102 is a network device.
  • the first device (101a, 101b) is a terminal device, and the second device 102 is a network device.
  • the first device (101a, 101b) is a terminal device, and the second device 102 is a terminal device.
  • the above-mentioned network device is a device located on the network side of the above-mentioned communication system and having a wireless transceiver function, or a chip or chip system that can be installed on the device.
  • Network equipment includes but is not limited to: access points (APs) in wireless fidelity (WiFi) systems, such as home gateways, routers, servers, switches, bridges, etc., evolved Node B (evolved Node B, eNB), wireless network controller (radio network controller, RNC), node B (Node B, NB), base station controller (base station controller, BSC), base transceiver station (base transceiver station, BTS), home base station (For example, home evolved NodeB, or home Node B, HNB), baseband unit (baseband unit, BBU), wireless relay node, wireless backhaul node, transmission point (transmission and reception point, TRP or transmission point, TP), etc.
  • APs access points
  • WiFi wireless fidelity
  • eNB evolved
  • 5G such as gNB in the new radio (NR) system, or transmission point (TRP or TP), one or a group (including multiple antenna panels) of the base station in the 5G system.
  • Antenna panels or it can also be a network node that constitutes a gNB or transmission point, such as a baseband unit (BBU), or a distributed unit (DU), a roadside unit (RSU) with base station functions, etc.
  • BBU baseband unit
  • DU distributed unit
  • RSU roadside unit
  • the above-mentioned terminal device is a terminal that is connected to the above-mentioned communication system and has a wireless transceiver function, or a chip or chip system that can be installed on the terminal.
  • a terminal device may also be referred to as an access terminal, subscriber unit, subscriber station, mobile station, mobile station, remote station, remote terminal, mobile device, user terminal, terminal, wireless communications device, user agent or user device.
  • the first device in the embodiment of the present application may be a mobile phone (mobile phone), a tablet computer (Pad), a computer with a wireless transceiver function, a first virtual reality (VR) device, or an augmented reality (AR) device.
  • VR virtual reality
  • AR augmented reality
  • the first device of the present application may also be a vehicle-mounted module, vehicle-mounted module, vehicle-mounted component, vehicle-mounted chip or vehicle-mounted unit built into the vehicle as one or more components or units.
  • the vehicle uses the built-in vehicle-mounted module, vehicle-mounted module , vehicle-mounted components, vehicle-mounted chips or vehicle-mounted units can implement the channel state information reporting method provided by this application.
  • channel state information reporting method provided by the embodiment of the present application can be applied between any two nodes shown in Figure 1, such as between the first device and the second device.
  • Method embodiments will not be described again here.
  • FIG. 1 is only a simplified schematic diagram for ease of understanding.
  • the communication system may also include other second devices and/or other first devices, which are not shown in FIG. 1 .
  • Figures 2, 3, and Figures 5 to 7 are schematic flow charts of method embodiments of the present application, showing detailed communication steps or operations of the method, but these steps or operations are only examples.
  • the embodiment of the present application can also perform other operations or modifications of the various operations in Figures 2, 3, and Figures 5 to 7.
  • the steps in Figures 2, 3, and 5 to 7 may be performed in a different order than those presented in Figures 2, 3, and 5 to 7, and may not necessarily be performed in Figures 2, 3, and 5 to 7.
  • FIG. 2 is a schematic flowchart of a method for reporting channel state information provided by an embodiment of the present application. This method of reporting channel state information may be applicable to communication between the second device and the first device shown in FIG. 1 .
  • the reporting method of channel status information includes the following steps:
  • the second device sends a reference signal. Accordingly, the first device receives the reference signal.
  • the reference signal may be a CSI-RS (for example, the second device is a network device, and the first device is a terminal device) or a channel sounding reference signal (SRS) (for example, the first device is a terminal device, and the second device is a terminal device).
  • SRS channel sounding reference signal
  • device is a network device.
  • the reference signal can also be other signals, such as cell-specific reference signal (CRS), SSB, DMRS, tracking reference signal (tracking reference signal, TRS), etc., which is not limited in this application.
  • S202 The first device determines the first indication information according to the reference signal.
  • the first indication information is used to construct a first covariance matrix corresponding to the channel matrix.
  • the channel matrix is used to indicate the CSI of the transmission channel between the first device and the second device.
  • the first covariance matrix corresponding to the channel matrix may include one or more of the following: a first space-frequency joint covariance matrix corresponding to the channel matrix, a first spatial domain covariance matrix corresponding to the channel matrix, and a first frequency domain corresponding to the channel matrix. covariance matrix.
  • the channel matrix may be determined by the first device according to a received reference signal (such as CSI-RS).
  • the dimension of the channel matrix may be M ⁇ N dimensions. M ⁇ 1, N ⁇ 1, M and N are both integers, M is the number of transmit antenna ports of the second device, and N is the number of frequency domain units for the second device to transmit the reference signal.
  • the frequency domain unit can be a subcarrier, a resource block (RB), or a subband.
  • for indicating may include direct indicating and indirect indicating.
  • indication information when describing that certain indication information is used to indicate A, it may include that the indication information directly indicates A or indirectly indicates A, but it does not mean that the indication information must carry A.
  • the information indicated by the indication information is called information to be indicated.
  • the information to be indicated can be directly indicated, such as the information to be indicated itself or the information to be indicated. Index indicating information, etc.
  • the information to be indicated may also be indirectly indicated by indicating other information, where there is an association relationship between the other information and the information to be indicated. It is also possible to indicate only a part of the information to be indicated, while other parts of the information to be indicated are known or agreed in advance.
  • the indication of specific information can also be achieved by means of a pre-agreed (for example, protocol stipulated) arrangement order of each piece of information, thereby reducing the indication overhead to a certain extent.
  • each piece of information can also be identified and indicated in a unified manner to reduce the instruction overhead caused by indicating the same information individually.
  • a precoding matrix is composed of precoding vectors, and each precoding vector in the precoding matrix may have the same parts in terms of composition or other attributes.
  • the specific indication method may also be various existing indication methods, such as, but not limited to, the above-mentioned indication methods and various combinations thereof.
  • the specific details of various indication methods can be referred to the existing technology, and will not be described again here.
  • the required indication method can be selected according to specific needs.
  • the embodiments of the present application do not limit the selected indication method. In this way, the indication methods involved in the embodiments of the present application should be understood to cover the indication methods to be indicated. Various ways to obtain information to be indicated.
  • the information to be instructed can be sent together as a whole, or can be divided into multiple sub-information and sent separately, and the sending period and/or sending timing of these sub-information can be the same or different.
  • the specific sending method is not limited in this application.
  • the sending period and/or sending timing of these sub-information may be predefined, for example, according to a protocol, or may be configured by the transmitting device by sending configuration information to the receiving device.
  • the configuration information may include, for example but not limited to, one or a combination of at least two of radio resource control signaling, medium access control (medium access control, MAC) layer signaling and physical layer signaling.
  • radio resource control signaling includes, for example, radio resource control (RRC) signaling;
  • MAC layer signaling for example, includes MAC control element (CE);
  • physical layer signaling for example, includes downlink control information (downlink control information, DCI).
  • the first device determines the first indication information according to the reference signal, which may include step 2.1 and step 2.2.
  • Step 2.1 The first device determines the channel matrix based on the reference signal.
  • Step 2.2 The first device determines the first indication information according to the channel matrix.
  • the first indication information is used to indicate the superposition coefficient and the codebook vector, and the superposition coefficient and the codebook vector are used to determine the first covariance matrix. That is to say, the first covariance matrix is a covariance matrix corresponding to the channel matrix constructed according to the first indication information.
  • the first covariance matrix and the actual covariance matrix corresponding to the channel matrix can satisfy a preset optimization model.
  • the preset optimization model may include the following formula (1) and formula (2).
  • the preset optimization model can be determined according to the following formula (1) and formula (2): stL ⁇ Lmax ; (2)
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • R is the actual covariance matrix corresponding to the channel matrix
  • ⁇ means the summation operation
  • 0 ⁇ l ⁇ L means the summation operation
  • 0 ⁇ l ⁇ L means the summation operation
  • l is an integer.
  • ⁇ l is the l-th superposition coefficient
  • w l is the l-th codebook vector
  • st is the constraint condition
  • L is the number of channel multipaths
  • L max is the maximum value of L
  • both L and L max are integers greater than 0.
  • the first device determines the channel matrix and obtains R by measuring the reference signal
  • the corresponding ⁇ l and w l can be obtained through the above optimization model, so that the actual covariance corresponding to the first covariance matrix and the channel matrix
  • the error between matrices should be as small as possible. That is to say, the first indication information can be determined based on the solution results of the preset optimization model.
  • R is the actual space-frequency joint covariance matrix corresponding to the channel matrix
  • R is an MN ⁇ MN matrix
  • R is the actual spatial covariance matrix corresponding to the channel matrix
  • R is an M ⁇ M matrix
  • R is the actual frequency domain covariance matrix corresponding to the channel matrix
  • R is an N ⁇ N matrix.
  • the superposition coefficient can be a complex number and the codebook vector can be a basis vector.
  • the basis vector can be a vector composed of a certain row element or a certain column element of the basis.
  • the basis may include one or more of the following: a spatial domain basis, a frequency domain basis, a space-frequency joint basis, a basis composed of steering vectors, a basis composed of phase change vectors, or a basis determined based on steering vectors and phase change vectors.
  • the superposition coefficient in the solution result of the preset optimization model is the superposition coefficient
  • the codebook vector is Then the superposition coefficient indicated by the first indication information may be the superposition coefficient
  • the codebook vector indicated by the first indication information is Among them, the superposition coefficient is the superposition coefficient Quantified.
  • step 2.2 please refer to step 3.2, step 5.2, step 6.2, or step 7.2 in the following method embodiments, which will not be described again here.
  • the first device sends first instruction information.
  • the second device receives the first indication information.
  • the first indication information may be carried in a physical uplink control channel (PUCCH) or a physical layer uplink share channel (PUSCH).
  • PUCCH physical uplink control channel
  • PUSCH physical layer uplink share channel
  • S203 Regarding the specific implementation principle of S203, please refer to S303, S503, S603, or S703 in the following method embodiments, which will not be described again here.
  • the first device sends the first instruction information used to construct the first covariance matrix corresponding to the channel matrix to the second device, which can avoid the transmission being directly used to restore the channel.
  • a large amount of status information can reduce feedback overhead and improve CSI feedback efficiency.
  • the second device may determine the first covariance matrix corresponding to the channel matrix according to the first indication information, and determine the characteristic base and the long-period coefficient corresponding to the characteristic base according to the covariance matrix corresponding to the channel matrix. Further, the second device can combine the characteristic base and the long period coefficient corresponding to the characteristic base with the short period coefficient to restore the complete channel state information.
  • the first device may perform processing in the space-frequency joint domain and report the first indication information related to recovering the channel state information.
  • the first device may send first indication information for determining the first space-frequency joint covariance matrix to the second device.
  • the reporting methods of the channel status information include:
  • the second device sends a reference signal. Accordingly, the first device receives the reference signal.
  • the first device determines the first indication information according to the reference signal.
  • the first indication information is used to construct a first space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first indication information is used to indicate the superposition coefficient and the codebook vector, and the superposition coefficient and the codebook vector are used to determine the first space-frequency joint covariance matrix.
  • the first space-frequency joint covariance matrix is an approximation matrix of the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first covariance matrix described in the aforementioned S202 corresponds to the first space-frequency joint covariance matrix.
  • the first device determines the first indication information based on the reference signal, which may include steps 3.1 and 3.2:
  • Step 3.1 The first device determines the channel matrix based on the reference signal.
  • step 3.1 please refer to the relevant introduction of step 2.1 mentioned above, and will not be repeated here.
  • Step 3.2 The first device determines the first indication information according to the channel matrix.
  • step 3.2 may include step 3.2-1 to step 3.2-3.
  • Step 3.2-1 The first device determines the channel column vector according to the channel matrix.
  • H is the channel matrix
  • M is the number of antenna ports of the second device
  • N is the number of frequency units
  • S is the spatial base
  • L 0 is the number of channel multipaths
  • C is a diagonal matrix
  • F is the frequency domain basis
  • ⁇ represents the Khatri-Rao product.
  • diag() means constructing a diagonal matrix
  • c is a vector composed of the diagonal elements of C.
  • (F * ⁇ S)[:,l 0 ] represents the column vector composed of the l 0th column of (F * ⁇ S)
  • F(:,l 0 ) represents the column vector composed of the l 0th column of F
  • [F (:,l 0 )] * represents the conjugate of F(:,l 0 )
  • S(:,l 0 ) represents the column vector composed of the l 0th column of S, 0 ⁇ l 0 ⁇ L 0 .
  • M and N are both positive integers.
  • the relationship between the channel column vector h and the channel matrix can satisfy the relationship shown in the following formula (6):
  • n 1, 2,...,N.
  • H(:,n) represents the nth column of the channel matrix.
  • Step 3.2-2 The first device determines the actual space-frequency joint covariance matrix corresponding to the channel matrix based on the channel column vector.
  • the actual space-frequency joint covariance matrix corresponding to the channel matrix is the inter-polarization average space-frequency joint covariance matrix
  • the relationship between the channel column vector and the actual space-frequency joint covariance matrix corresponding to the channel matrix satisfies the relationship shown in the following formula (7):
  • h + is the channel column vector corresponding to the positive polarization direction (also called the first polarization direction)
  • h - is the negative polarization direction (also called the second polarization direction) corresponding channel column vector.
  • conjugate transpose of h + is the conjugate transpose of h - .
  • Step 3.2-3 The first device determines the first indication information based on the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix satisfy a preset first optimization model.
  • first optimization model please refer to the relevant introduction of the following formula (13) and formula (14), which will not be described again here.
  • the actual covariance matrix R corresponding to the channel matrix in the above formula (1) corresponds to the actual space-frequency joint covariance matrix R h .
  • the superposition coefficient may be a first superposition coefficient used to indicate characteristics of the angle delay power spectrum, such as amplitude and/or phase.
  • the first superposition coefficient may be obtained by sampling the angle delay power spectrum, or by sampling the angle delay power spectrum.
  • the sampling results of the delay power spectrum are quantified.
  • the codebook vector may be a vector determined based on the steering vector and phase change vector corresponding to the multipath. The following takes a dual-polarized antenna array as an example to further explain step 3.2-3. In a dual-polarized antenna panel, the channel column vector corresponding to the antenna in the positive polarization direction satisfies the relationship shown in the following formula (8):
  • the pitch angle of the diameter can refer to the angle between the diameter and the first plane.
  • the first plane is a plane perpendicular to the plane where the antenna panel is located.
  • the horizontal angle of the diameter can refer to the angle between the diameter and the second plane.
  • the angle between the second plane and the second plane is a plane perpendicular to both the plane where the antenna panel is located and the first plane.
  • the following is an example based on the three-dimensional coordinate axes. As shown in Figure 4, the x-axis, y-axis and z-axis are perpendicular to each other.
  • the plane where the antenna panel is located is parallel to the plane formed by the y-axis and z-axis, then
  • the pitch angle of the diameter is the diameter and the x-axis,
  • the angle between the planes where the z-axis lies, and the horizontal angle of the diameter is the angle between the projection of the diameter on the xOy plane and the x-axis.
  • the actual joint space-frequency covariance matrix corresponding to the channel matrix can also satisfy the relationship shown in the following formulas (10) and (11):
  • codebook vector can satisfy the relationship shown in the following formula (12):
  • the l0th codebook vector is determined based on the steering vector corresponding to the multipath angle of the l0th path and the phase change vector corresponding to the time delay of the l0th path.
  • l in formula (1) corresponds to l 0 .
  • the first optimization model may include the following formula (13) and formula (14).
  • the first optimization model can be determined according to the following formula (13) and formula (14):
  • l 0th first superposition coefficient that is, the first superposition coefficient corresponding to the l 0th path.
  • l 0 is an integer
  • L 0 is the number of channel multipaths
  • L 0 are all integers greater than 0.
  • the first device determines the channel matrix by measuring the reference signal, and obtains In the case of , the corresponding can be obtained through the above first optimization model as well as and The error between the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix is made as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset first optimization model.
  • the multipath angle is The steering vector is the first steering vector
  • the delay is Delay
  • the corresponding phase change vector is the first phase change vector representation and
  • the first superposition coefficient corresponding to the characteristic of the angular delay power spectrum is the first space-frequency joint superposition coefficient (i.e. the aforementioned superposition coefficient )
  • the codebook vector indicated by the first indication information is The superposition coefficient indicated by the first indication information is the second space-frequency joint superposition coefficient
  • the second space-frequency joint superposition coefficient is the first space-frequency joint superposition coefficient
  • the quantized coefficient, the second space-frequency joint superposition coefficient Can also be used to characterize and Characteristics of the corresponding angular delay power spectrum. Need to explain, Can be unquantized or quantized multipath angle, Can be unquantized or quantized delay.
  • the first indication information is used to indicate the above-mentioned first steering vector The above first phase change vector and the above second space-frequency joint superposition coefficient
  • the codebook vector indicated by the first indication information corresponds to the first steering vector
  • the first phase change vector Superposition coefficient i.e. superposition coefficient
  • the first indication information is used to indicate the above-mentioned multipath angle The above delay and the above second space-frequency joint superposition coefficient
  • the codebook vector indicated by the first indication information corresponds to the multipath angle
  • delay Superposition coefficient i.e. superposition coefficient
  • the channel state information reporting method shown in Figure 3 also includes the following steps 3.3 to 3.5.
  • Step 3.3 The second device sends information indicating the antenna array configuration, and the first device receives the information.
  • the information includes: horizontal array spacing, vertical array spacing, the number of single-polarized horizontal arrays, and the number of single-polarized vertical arrays.
  • Step 3.4 The first device determines the steering vector based on the indication information of the antenna array shape.
  • Step 3.5 the first device determines the phase change vector based on the indication information of the antenna array shape
  • phase change vector Satisfies the relationship shown in the following formula (18):
  • f 0 is the frequency of the 0th frequency unit
  • f N-1 is the frequency of the N-1th frequency unit
  • N is the number of frequency units.
  • step 3.5 can be performed before step 3.4; one or more of steps 3.3 to 3.5 can also be performed before step 3.2-3.
  • the first device sends first instruction information.
  • the second device receives the first indication information.
  • the first indication information may be carried in PUCCH or PUSCH.
  • the first device sends the first indication information according to the first period
  • the second device receives the first indication information according to the first period
  • the second device determines the first space-frequency joint covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first space-frequency joint covariance matrix is a space-frequency joint covariance matrix corresponding to the channel matrix determined and constructed according to the first indication information.
  • the first indication information can indicate the superposition coefficient and codebook vector
  • the first space-frequency joint covariance matrix can satisfy the relationship shown in the following formula (19):
  • the first indication information is used to indicate the first steering vector first phase change vector and the second space-frequency joint superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the first steering vector and the first phase change vector
  • the superposition coefficient corresponds to the second space-frequency joint superposition coefficient
  • the first space-frequency joint covariance matrix can satisfy the relationship shown in the following formula (20):
  • the first indication information is used to indicate the multipath angle. Delay and That is, the codebook vector indicated by the first indication information corresponds to the multipath angle and delay The superposition coefficient corresponds to the second space-frequency joint superposition coefficient
  • the second device can first determine the multipath angle according to formula (15) to formula (17) The corresponding guidance vector And determine the phase change vector according to formula (18) Then, the first space-frequency joint covariance matrix is determined according to formula (20).
  • the first device determines the first indication information used to construct the first space-frequency joint covariance matrix and sending it to the second device, it is possible to avoid reporting a large amount of information directly used to restore the channel state information.
  • Information such as the superposition coefficient corresponding to the space-frequency joint feature base.
  • the second device can determine the first space-frequency joint covariance matrix corresponding to the channel matrix according to the first indication information, and determine the characteristic base according to the first space-frequency joint covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, This can reduce feedback overhead and improve CSI feedback efficiency.
  • the first device may report the partial superposition coefficient, such as the superposition coefficient indicated by the above-mentioned first indication information, to the second device according to a long period (i.e., the first period).
  • the first feedback coefficient as described below is reported to the second device according to a short cycle (ie, the second cycle).
  • the second device can determine complete channel state information based on the first indication information and the first feedback coefficient.
  • the duration of the first period is longer than the duration of the second period.
  • the duration of the first period is multiple integers of the duration of the second period. times. It should be noted that the short-period reporting is based on one reference signal measurement, and the long-period reporting is based on multiple reference signal measurements. The specific number of times is not specifically limited in this application.
  • the channel state information reporting method provided in Figure 3 may also include step 3.6:
  • Step 3.6 The first device sends the second instruction information.
  • the second device receives the second indication information.
  • the second indication information is used to indicate the first feedback coefficient.
  • the first feedback coefficient is determined based on the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the first decomposition rule may include: the arrangement order of the elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, such as the order from large to small or the order from small to large, and the first space-frequency joint The type of the first row elements of the space-frequency joint feature basis of the covariance matrix decomposition, such as positive real numbers.
  • the following uses an example to illustrate the principle of the first device obtaining the first feedback coefficient.
  • the first indication information indicates the first steering vector first phase change vector and the second space-frequency joint superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the first steering vector and the first phase change vector
  • the superposition coefficient corresponds to the second space-frequency joint superposition coefficient
  • the first indication information indicates the multipath angle Delay and the second space-frequency joint superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the multipath angle and delay
  • the superposition coefficient corresponds to the second space-frequency joint superposition coefficient
  • the channel matrix determined by the first device is H.
  • the channel state information reporting method provided in Figure 3 may also include: step 3.6-1 to step 3.6-5.
  • Step 3.6-1 The first device determines the first space-frequency joint covariance matrix according to the first indication information.
  • the first space-frequency joint covariance matrix and the first indication information satisfy the relationship shown in the above formula (19) or formula (20).
  • Step 3.6-2 The first device decomposes the first space-frequency joint covariance matrix, such as singular value decomposition (SVD) decomposition or eigen value decomposition (EVD), to obtain the space-frequency joint feature base.
  • the first space-frequency joint covariance matrix satisfies the relationship shown in the following formula (21):
  • U is the space-frequency joint feature base of the first space-frequency joint covariance matrix
  • ⁇ is the diagonal matrix after SVD decomposition of the first space-frequency joint covariance matrix
  • U H is the conjugate transpose of U.
  • feature vectors (column vectors) with larger energy can be selected from the space-frequency joint feature base to form an effective space-frequency joint feature base.
  • the number of columns of the selected feature vector can be determined according to the energy of the feature vector, and the feature vector with the first column number is given priority. For details, please refer to the following steps As shown in 3.6-3.
  • Step 3.6-3 the first device determines the matrix composed of the first P columns of the space-frequency joint feature base U as the effective space-frequency joint feature base
  • the effective space-frequency joint feature base includes the first P columns of the space-frequency joint feature base.
  • P is a positive integer.
  • Step 3.6-4 the first device determines the base based on the effective space-frequency joint feature Determine the space-frequency joint short-period feedback coefficient, where the space-frequency joint short-period feedback coefficient is the projection coefficient of the channel on the space-frequency joint domain.
  • the space-frequency joint short-period feedback coefficient satisfies the relationship shown in the following formula (22):
  • C 21 is the space-frequency joint short-period feedback coefficient
  • I 2 is the unit matrix determined according to the number of polarizations of the array antenna.
  • Step 3.6-5 the first device quantizes some or all elements of the space-frequency joint short-period feedback coefficient to obtain the first feedback coefficient
  • the data amount of the first feedback coefficient can be reduced, thereby further reducing air interface overhead and improving feedback efficiency.
  • the first indication information may also indicate: the quantized first quantization vector of the first row elements of the first P columns in the space-frequency joint feature base of the first decomposition result.
  • P is a positive integer.
  • the first quantized vector Quantification of the effective space-frequency joint characteristic basis by the first device The first row of is obtained.
  • Figure 3 provides Methods can also include:
  • the second device determines an effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the first space-frequency joint covariance matrix may have multiple roots, that is to say, the decomposition result of the first space-frequency joint covariance matrix is not unique.
  • the first indication information is also used to indicate: in the space-frequency joint feature base after decomposition of the first space-frequency joint covariance matrix , the first quantized vector after quantizing the elements in the first row of the first P columns.
  • P is a positive integer.
  • the space-frequency joint feature base can be combined with the first feedback coefficient, that is, the short-period coefficient, so that the second device can recover complete channel state information.
  • the second device determines the effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule, which may include: the second device determines the first space-frequency joint feature base according to the first decomposition rule and the first quantization vector.
  • the second device determines channel state information, such as a channel column vector corresponding to the channel matrix, based on the effective space-frequency joint feature base and the first feedback coefficient.
  • the channel column vector corresponding to the channel matrix determined by the second device can satisfy the relationship shown in the following formula (23):
  • h' is the channel column vector determined by the second device, or it can also be called the channel state information determined by the second device.
  • the first device may perform processing in the air domain and report the first indication information related to recovering the channel state information.
  • the first device may send first indication information for determining the first spatial covariance matrix to the second device.
  • the reporting methods of the channel status information include:
  • the second device sends a reference signal. Accordingly, the first device receives the reference signal.
  • S502 The first device determines the first indication information according to the reference signal.
  • the first indication information is used to construct a first spatial covariance matrix corresponding to the channel matrix.
  • the first indication information is used to indicate the superposition coefficient and the codebook vector.
  • the superposition coefficient includes a second superposition coefficient used to indicate the characteristics of the angular power spectrum, such as amplitude and/or phase.
  • the second superposition coefficient can be obtained by sampling the angular power spectrum, or by sampling the angular power spectrum.
  • the codebook vector includes second information indicating the angle. The second superposition coefficient and the second information are used to determine the first spatial covariance matrix.
  • the first device determines the first indication information based on the reference signal, which may include steps 5.1 to 5.2:
  • Step 5.1 The first device determines the channel matrix based on the reference signal.
  • step 5.1 please refer to the relevant introduction of step 2.1 mentioned above, and will not be repeated here.
  • Step 5.2 The first device determines the first indication information according to the channel matrix.
  • the first spatial covariance matrix is an approximation matrix of the actual spatial covariance matrix corresponding to the channel matrix, and the two satisfy the preset second optimization model.
  • the actual covariance matrix R corresponding to the channel matrix in the above formula (1) corresponds to the actual spatial covariance matrix
  • the second information may be indicated by the steering vector corresponding to each multipath angle (the angle of each path in the multipath), or the multipath angle of each path in the multipath. That is to say, the first indication information may indicate the second superposition coefficient and the steering vector corresponding to each multipath angle. Alternatively, the first indication information may indicate the second superposition coefficient and the multipath angle of each of the multipaths.
  • the second optimization model may include formula (24) and formula (25).
  • the second optimization model can be determined according to formula (24) and formula (25):
  • L 1 is the number of channel multipaths in the spatial domain, is the maximum value of L 1 , L 1 , are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1 , and l 1 is an integer.
  • the first device determines the channel matrix by measuring the reference signal and obtains In the case of , the corresponding can be obtained through the above second optimization model and The error between the first spatial domain covariance matrix and the actual spatial domain covariance matrix corresponding to the channel matrix is made as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset first optimization model.
  • the steering vector corresponding to the l 1th multipath angle For the implementation principle, please refer to the relevant introduction in steps 3.3 and 3.4 above, and will not be repeated here.
  • the actual spatial covariance matrix corresponding to the channel matrix can be determined based on the channel matrix.
  • the actual spatial covariance matrix corresponding to the channel matrix satisfies the relationship shown in the following formula (26):
  • the first indication information may be determined based on the solution result of the preset second optimization model.
  • the multipath angle is
  • the steering vector is the second steering vector used to indicate
  • the second superposition coefficient corresponding to the characteristic of the angular power spectrum is the first spatial domain superposition coefficient.
  • the first indication information indicates the second steering vector and the second airspace superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the second steering vector
  • the superposition coefficient corresponds to the second airspace superposition coefficient
  • the first indication information indicates the multipath angle and the second airspace superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the multipath angle
  • the superposition coefficient corresponds to the second airspace superposition coefficient
  • Second airspace superposition coefficient is the first airspace superposition coefficient Quantized coefficients.
  • the codebook vector Corresponding to superposition coefficient Corresponds to the second airspace superposition coefficient
  • l in formula (1) corresponds to l 1 . Need to explain, is the quantized multipath angle.
  • the first device sends the first instruction information.
  • the second device receives the first indication information.
  • the first indication information may be carried in PUCCH or PUSCH.
  • the second device determines the first spatial covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first indication information indicates the second steering vector and the second airspace superposition coefficient That is, the superposition coefficient indicated by the first indication information corresponds to the second airspace superposition coefficient.
  • the codebook vector corresponds to the second steering vector Alternatively, the first indication information indicates the multipath angle and the second airspace superposition coefficient That is, the superposition coefficient indicated by the first indication information corresponds to The codebook vector corresponds to the multipath angle In this case, the first space-frequency covariance matrix satisfies the following relationship (27):
  • the first device can avoid reporting a large number of coefficients directly used to restore the channel state information.
  • the second device can determine the first spatial covariance matrix corresponding to the channel matrix according to the first indication information, and determine the spatial characteristic base according to the first spatial covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, thereby reducing Feedback overhead and improve feedback efficiency.
  • the spatial domain feature base can be combined with the short-period feedback coefficient and the frequency domain feature base so that the second device can restore complete channel state information.
  • the first device may perform processing in the frequency domain and report the first indication information related to recovering the channel state information.
  • the first device may send first indication information for determining the frequency domain covariance matrix to the second device.
  • the reporting methods of the channel status information include:
  • the second device sends a reference signal to the first device. Accordingly, the first device receives the reference signal from the second device.
  • the first device determines the first indication information according to the reference signal.
  • the first indication information is used to construct a first frequency domain covariance matrix corresponding to the channel matrix.
  • the first indication information is used to indicate the superposition coefficient and the codebook vector.
  • the superposition coefficient includes the time delay power spectrum used to indicate Characteristics, such as the third superposition coefficient of amplitude and/or phase, the third superposition coefficient can be obtained by sampling the delay power spectrum, or by quantizing the sampling result of the delay power spectrum.
  • the codebook vector includes third information indicating the delay. Wherein, the third superposition coefficient and the third information are used to determine the first frequency domain covariance matrix.
  • the first device determines the first indication information based on the reference signal, which may include steps 6.1 to 6.2:
  • Step 6.1 The first device determines the channel matrix based on the reference signal.
  • step 6.1 please refer to the relevant introduction of step 2.1 mentioned above, and will not be repeated here.
  • Step 6.2 The first device determines the first indication information according to the channel matrix.
  • the first frequency domain covariance matrix is an approximation matrix of the actual frequency domain covariance matrix corresponding to the channel matrix, and the two satisfy a preset third optimization model.
  • the actual covariance matrix R corresponding to the channel matrix in the above formula (1) corresponds to the actual spatial covariance matrix
  • the third information may be indicated by the phase change vector corresponding to the time delay of each path, or the time delay of each path. That is to say, the first indication information may indicate the third superposition coefficient and the phase change vector corresponding to each path. Alternatively, the first indication information may indicate the third superposition coefficient and the delay of each path.
  • the third optimization model may include formula (28) and formula (29).
  • the third optimization model can be determined according to formula (28) and formula (29):
  • L 2 is the number of channel multipaths in the frequency domain, is the maximum value of L 2 , L 2 , are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2 , and l 2 is an integer.
  • the first device determines the channel matrix by measuring the reference signal and obtains
  • the above-mentioned second optimization model can be used to make the error between the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix as small as possible. That is to say, the first indication information can be determined based on the solution result of the preset third optimization model.
  • the actual frequency domain covariance matrix corresponding to the above channel matrix can be determined based on the channel matrix.
  • the actual frequency domain covariance matrix corresponding to the channel matrix satisfies the relationship shown in the following formula (30):
  • the time delay is Delay
  • the corresponding phase change vector is the second phase change vector representation
  • the coefficient corresponding to the characteristic of the delay power spectrum is the first frequency domain superposition coefficient.
  • the first indication information is used to indicate the second phase change vector Second frequency domain superposition coefficient That is, the codebook vector indicated by the first indication information corresponds to the second phase change vector
  • the superposition coefficient corresponds to the second frequency domain superposition coefficient
  • the first indication information is used to indicate the delay and the second delay power spectrum That is, the codebook vector indicated by the first indication information corresponds to the delay
  • the superposition coefficient corresponds to the second frequency domain superposition coefficient
  • the second frequency domain superposition coefficient is the first frequency domain superposition coefficient Quantized coefficients.
  • the codebook vector Corresponding to superposition coefficient Corresponds to the second frequency domain superposition coefficient l in formula (1) corresponds to l 2 . Need to explain, is the quantized delay.
  • the first device sends the first instruction information.
  • the second device receives the first indication information.
  • the first indication information may be carried in PUCCH or PUSCH.
  • the second device determines the first frequency domain covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first frequency domain covariance matrix satisfies the relationship shown in the following formula (31):
  • the first device can avoid reporting a large amount of information directly used to restore the channel state information.
  • a large amount of information directly used to restore the channel state information Such as the superposition coefficient corresponding to the frequency domain feature base.
  • the second device can determine the first frequency domain covariance matrix according to the first indication information, and determine the frequency domain feature base according to the first frequency domain covariance matrix corresponding to the channel matrix, thereby reducing the amount of feedback data, thereby reducing feedback overhead to improve feedback efficiency.
  • frequency domain feature base can be combined with the spatial domain feature base and short-period feedback coefficients to enable the second device to restore complete channel state information.
  • the first device may perform processing in the air domain and frequency domain and report the first indication information related to recovering the channel state information.
  • the first device may send first indication information for determining the frequency domain covariance matrix and the spatial domain covariance matrix to the second device.
  • the reporting methods of the channel status information include:
  • the second device sends a reference signal. Accordingly, the first device receives the reference signal.
  • the first device determines the first indication information according to the reference signal.
  • the first indication information is used to construct a first spatial domain covariance matrix corresponding to the channel matrix, and to construct a first frequency domain covariance matrix corresponding to the channel matrix.
  • the first indication information may indicate the superposition coefficient and the codebook vector.
  • the superposition coefficient may include a second superposition coefficient used to indicate characteristics of the angle power spectrum, such as amplitude and/or phase, and a third superposition coefficient used to indicate characteristics of the delay power spectrum, such as amplitude and/or phase.
  • the second superposition coefficient may be obtained by sampling the angular power spectrum, or by quantizing the sampling result of the angular power spectrum
  • the third superposition coefficient may be obtained by sampling the delay power spectrum, or by quantizing the delay power spectrum. The sampling results are quantified.
  • the codebook vector may include second information indicating the angle and third information indicating the delay.
  • the second superposition coefficient and the second information are used to determine the first spatial domain covariance matrix
  • the third superposition coefficient and the third information are used to determine the first frequency domain covariance matrix.
  • the first spatial domain covariance matrix and the actual spatial domain covariance matrix corresponding to the channel matrix satisfy the preset second optimization model
  • the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix satisfy the preset The third optimization model.
  • the covariance matrix R corresponding to the channel matrix in the above formula (1) includes the actual spatial covariance matrix corresponding to the channel matrix
  • the spatial domain covariance matrix and the frequency domain covariance matrix can be fed back.
  • the second information, the first spatial domain covariance matrix and the second optimization model please refer to the relevant introduction in S502.
  • the third information, the first frequency domain covariance matrix and the third optimization please refer to the relevant introduction in S602 and will not be repeated here.
  • the first device determines the first indication information according to the reference signal, which may include step 7.1 and step 7.2.
  • Step 7.1 The first device determines the channel matrix based on the reference signal.
  • step 7.1 For the implementation principle of step 7.1, please refer to the relevant introduction of step 2.1 above, and will not be repeated here.
  • Step 7.2 The first device determines the first indication information according to the channel matrix.
  • the first device sends the first instruction information.
  • the second device receives the first indication information.
  • the first indication information may be carried in PUCCH or PUSCH.
  • the first device sends the first indication information according to the third cycle.
  • the second device receives the first indication information according to the third cycle.
  • the second device determines the first spatial domain covariance matrix and the first frequency domain covariance matrix corresponding to the channel matrix according to the first indication information.
  • S704 may include step 7.3 and step 7.4.
  • Step 7.3 The second device determines the first spatial covariance matrix corresponding to the channel matrix according to the first indication information.
  • step 7.3 you can refer to the relevant introduction of S504, which will not be described again here.
  • Step 7.4 The second device determines the first frequency domain covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first device feeds back the first instruction information used to construct the first spatial domain covariance matrix and the first frequency domain covariance matrix and sends it to the second device, which can avoid reporting directly for recovery.
  • a large amount of information about the channel state information such as the superposition coefficient corresponding to the spatial domain feature base and the superposition coefficient corresponding to the frequency domain feature base.
  • the first spatial domain covariance matrix and the first frequency domain covariance matrix are determined based on the first indication information from the first device. For example, the second device may determine the corresponding channel matrix according to the first indication information.
  • the first spatial domain covariance matrix and the first frequency domain covariance matrix and determine the spatial domain characteristic base according to the first spatial domain covariance matrix corresponding to the channel matrix, and determine the frequency domain characteristic base according to the first frequency domain covariance matrix corresponding to the channel matrix, Reduce the amount of feedback data, thereby reducing feedback overhead and improving feedback efficiency.
  • the first device can report the partial superposition coefficient, such as the superposition coefficient indicated by the above-mentioned first indication information, to the second device in a long period (ie, the third period); the partial superposition coefficient is as follows
  • the above-mentioned second feedback coefficient is reported to the second device according to the short cycle (ie, the fourth cycle).
  • the second device may determine the channel state information based on the first indication information and the second feedback coefficient.
  • the channel state information reporting method provided in Figure 7 may also include: the first device sending third indication information according to the fourth cycle.
  • the second device receives the third indication information according to the fourth cycle.
  • the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined based on the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of the elements in the diagonal matrix of the first spatial covariance matrix, such as the order from small to large or from large to small, and the spatial characteristic basis of the first spatial covariance matrix.
  • the elements in the first row are all of type, such as positive real numbers.
  • the third decomposition rule may include: the arrangement order of the elements in the diagonal matrix of the first frequency domain covariance matrix, such as from small to large or from large to small, and the frequency of the first frequency domain covariance matrix.
  • the type of the first row elements of the domain feature base such as positive real numbers.
  • the process of the first device determining the second feedback coefficient includes the following steps 7.5 to 7.8.
  • Step 7.5 The first device determines the first spatial domain covariance matrix and the first frequency domain covariance matrix according to the third indication information.
  • Step 7.6 The first device performs SVD decomposition on the first spatial covariance matrix according to the second decomposition rule to obtain the spatial feature base.
  • the first device performs SVD decomposition on the first frequency domain covariance matrix according to the third decomposition rule to obtain a frequency domain feature base.
  • the first spatial domain covariance matrix satisfies the relationship shown in the following formula (32):
  • the first frequency domain covariance matrix satisfies the relationship shown in the following formula (33):
  • U S is the spatial domain feature base
  • ⁇ S is the diagonal matrix of the first spatial domain covariance matrix
  • U F is the frequency domain characteristic base
  • ⁇ F is the diagonal matrix of the first frequency domain covariance matrix
  • feature vectors (column vectors) with larger energy can be selected from the spatial domain feature base to form an effective spatial domain feature base, and the energy can be selected from the frequency domain feature base.
  • the larger feature vectors (column vectors) constitute the effective frequency domain feature base.
  • Step 7.7 for the airspace feature base U S , take the first D columns of the airspace feature base U S to get the effective airspace feature base
  • For the frequency domain feature base U F take the first D columns of the frequency domain feature base U F to obtain the effective frequency domain feature base.
  • Step 7.8 based on the effective airspace feature base and effective frequency domain feature base Determine the feedback coefficient C 22 that combines the spatial domain and the frequency domain, and quantize the short-period feedback coefficient that combines the spatial domain and the frequency domain (such as represented by a binary number) to obtain the second feedback coefficient
  • the feedback coefficient C 22 that combines the spatial domain and the frequency domain is a coefficient matrix composed of the superposition coefficients corresponding to a set of space-frequency vectors composed of each eigenvector in the spatial domain feature base and each eigenvector in the frequency domain feature base, or A coefficient matrix composed of the superposition coefficients corresponding to each eigenvector in the spatial domain feature base and each eigenvector in the frequency domain feature base.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base of the second decomposition result.
  • K is a positive integer.
  • the method shown in Figure 7 may also include: the receiving device determines the quantized vector of the first row elements of the first K columns of the spatial feature base U S as the second quantized vector
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base of the third decomposition result.
  • D is a positive integer.
  • the method shown in Figure 7 may also include: the receiving device determines the quantized vector of the first row elements of the first D columns of the frequency domain feature base U F as the third quantized vector
  • the method provided in Figure 7 may also include step 7.9:
  • Step 7.9 The second device determines the effective airspace characteristic base according to the second decomposition rule.
  • the second device determines the effective airspace feature base according to the second decomposition rule, including: the second device determines the effective airspace feature base according to the second decomposition rule and the second quantization vector.
  • the effective spatial feature base includes the first K columns of the spatial feature base of the first spatial covariance matrix.
  • the method provided in Figure 7 may also include step 7.10 :
  • Step 7.10 The second device determines the effective frequency domain characteristic base according to the third decomposition rule.
  • the second device determines the channel state information based on the effective spatial domain characteristic base, the effective frequency domain characteristic base and the second feedback coefficient.
  • the channel state information may be expressed in the form of a channel matrix estimated by the second device.
  • the channel matrix estimated by the second device satisfies the relationship shown in the following formula (35):
  • H' is the channel matrix determined by the second device, or it can also be called the channel state information determined by the second device.
  • the method provided in Figure 7 may also include: the second device determines the effective frequency domain feature base according to the third decomposition rule and the third quantization vector.
  • the effective frequency domain feature base includes the first D columns of the frequency domain feature base of the first frequency domain covariance matrix.
  • the second device can combine the spatial domain feature base, the frequency domain feature base and the second feedback coefficient, that is, the short period feedback coefficient, to restore complete channel state information.
  • a long-period feedback requires feedback in the scheme of feedback spatial domain feature base and frequency domain feature base. and There are a total of (B ⁇ K+D ⁇ T) complex coefficients, where B is the number of air domain bases selected by the second device or the first device, T is the number of frequency domain bases selected by the second device or the first device, and K represents the downlink air domain characteristics.
  • the effective dimension of the space, D represents the effective dimension of the downlink frequency domain feature space.
  • the baseline scheme of feedbacking the spatial domain feature base and the frequency domain feature base requires quantified feedback of 640 complex coefficients. This embodiment requires quantified feedback of 64 data, such as positive real numbers, which greatly reduces the feedback overhead. In other words, under the same overhead, the overhead can be used to increase the values of K and D to improve the CSI quantization accuracy, thereby improving system performance.
  • steering vectors and phase change vectors in the above-mentioned Figure 3, Figure 5 or Figure 6 can all be oversampled discrete Fourier transform (DFT) codebooks.
  • DFT discrete Fourier transform
  • the "quantization” involved in this application may refer to the process of approximating the continuous values of a signal (or a large number of possible discrete values) into a finite number (or fewer) discrete values, such as uniform quantization, or it may be Convert data represented by complex numbers into data represented by binary numbers, which will not be described here.
  • FIG. 8 is a schematic structural diagram of a communication device provided by an embodiment of the present application.
  • the communication device 800 includes: a processing module 801 and a transceiver module 802 .
  • FIG. 8 shows only the main components of the communication device.
  • the communication device 800 may be adapted to the communication system shown in Figure 1 to perform reporting of channel state information shown in Figure 2, Figure 3, or Figure 5, or Figure 6, or Figure 7 The function of the first device in the method.
  • the transceiver module is used to receive the reference signal from the second device.
  • Processing module 801 configured to determine first indication information according to the reference signal.
  • the first indication information is used to construct a first covariance matrix corresponding to a channel matrix, and the channel matrix is used to indicate channel state information of a channel between the communication device and the second device.
  • the transceiver module 802 is used to send first indication information.
  • the first indication information may be used to indicate the superposition coefficient and the codebook vector, and the superposition coefficient and the codebook vector are used to determine the first space-frequency joint covariance matrix.
  • the first optimization model is satisfied between the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first optimization model may include: stL ⁇ Lmax ;
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • R is the actual space-frequency joint covariance matrix corresponding to the channel matrix
  • ⁇ means the summation operation, 0 ⁇ l ⁇ L
  • l is an integer
  • ⁇ l is the l-th superposition coefficient
  • w l is the l-th codebook vector
  • st is the constraint condition
  • L is the number of channel multipaths
  • L max is the maximum value of L
  • both L and L max are integers greater than 0.
  • the superposition coefficient includes a first superposition coefficient used to indicate the characteristics of the angular delay power spectrum
  • the codebook vector includes first information used to indicate the angular delay
  • the first superposition coefficient and the first indication information are used to determine
  • the preset optimization model includes: a first optimization model that is satisfied between the first space-frequency joint covariance matrix and the actual space-frequency joint covariance matrix corresponding to the channel matrix.
  • the first optimization model includes:
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • ⁇ is the actual space-frequency joint covariance matrix corresponding to the channel matrix
  • ⁇ represents the summation operation
  • l 0 is an integer
  • is the l0th first superposition coefficient is the steering vector corresponding to the l0th multipath angle
  • the conjugate transpose of is the l0th phase change vector
  • st is the constraint condition
  • L 0 is the number of channel multipaths
  • L FS max is the maximum value of L 0
  • L 0 and L FS max are both integers greater than 0.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angular power spectrum
  • the codebook vector may include second information used to indicate the angle.
  • the second superposition coefficient and the second information are used to determine the first spatial covariance matrix.
  • the preset optimization model includes: a second optimization model that is satisfied between the first spatial covariance matrix and the actual spatial covariance matrix corresponding to the channel matrix.
  • the second optimization model may include:
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • ⁇ is the actual spatial covariance matrix corresponding to the channel matrix
  • ⁇ represents the summation operation
  • st is the constraint condition
  • L 1 is the number of channel multipaths in the air domain
  • L 1 are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1
  • l 1 is an integer.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include third information used to indicate the delay, the third superposition coefficient and the third information Used to determine the first frequency domain covariance matrix.
  • the preset optimization model includes: a third optimization model that is satisfied between the first frequency domain covariance matrix and the actual frequency domain covariance matrix corresponding to the channel matrix.
  • the third optimization model may include:
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • ⁇ is the actual frequency domain covariance matrix corresponding to the channel matrix
  • ⁇ represents the summation operation
  • st is the constraint condition
  • L 2 is the number of channel multipaths in the frequency domain
  • L 2 are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2
  • l 2 is an integer.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angular power spectrum and a second superposition coefficient used to indicate the characteristics of the angular power spectrum.
  • the third superposition coefficient indicating the characteristics of the delay power spectrum the codebook vector may include second information for indicating the angle and third information for indicating the delay, and the second superposition coefficient and the second information are used to determine the first The spatial domain covariance matrix, the third superposition coefficient and the third information are used to determine the first frequency domain covariance matrix.
  • the preset optimization model includes: a second optimization model that satisfies the relationship between the first spatial covariance matrix and the actual spatial covariance matrix corresponding to the channel matrix, and the actual frequency domain covariance corresponding to the first frequency domain covariance matrix and the channel matrix.
  • the third optimization model satisfied between matrices.
  • the second optimization model may include:
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • ⁇ is the actual spatial covariance matrix corresponding to the channel matrix
  • ⁇ represents the summation operation.
  • l 1 second superposition coefficient is the steering vector corresponding to the l 1th multipath angle
  • st is the constraint condition
  • L 1 is the number of channel multipaths in the air domain
  • L 1 are all integers greater than 0, 0 ⁇ l 1 ⁇ L 1
  • l 1 is an integer.
  • the third optimization model may include:
  • min means taking the minimum value
  • ⁇ F means taking the F norm
  • ⁇ is the actual frequency domain covariance matrix corresponding to the channel matrix
  • ⁇ represents the summation operation.
  • l 2nd third superposition coefficient is the l 2th phase change vector, for The conjugate transpose of
  • st is the constraint condition
  • L 2 is the number of channel multipaths in the frequency domain
  • L 2 are all integers greater than 0, 0 ⁇ l 2 ⁇ L 2
  • l 2 is an integer.
  • the transceiver module is specifically configured to send the first indication information to the second device according to the first cycle.
  • the transceiver module 802 may also be configured to send the second indication information to the second device according to the second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined based on the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the first decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and the first row of the space-frequency joint feature basis of the first space-frequency joint covariance matrix decomposition.
  • the type of the element such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantization vector after quantization of the first row elements of the first P columns in the space-frequency joint feature base of the first decomposition result.
  • P is a positive integer.
  • the transceiver module is specifically configured to send the first indication information to the second device according to the third cycle.
  • the transceiver module 802 may also be configured to send third indication information to the second device according to a fourth period; wherein the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined based on the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix.
  • the second decomposition result is obtained by decomposing the first spatial domain covariance matrix according to the second decomposition rule
  • the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the spatial feature base of the first spatial covariance matrix, such as positive real numbers.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the spatial domain feature base of the first frequency domain covariance matrix, such as positive real numbers.
  • the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base of the second decomposition result.
  • K is a positive integer.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base of the third decomposition result.
  • D is a positive integer.
  • the transceiver module 802 may include a receiving module and a sending module. Among them, the transceiver module 802 is used to implement the sending function and receiving function of the communication device 800.
  • the communication device 800 may also include a storage module (not shown in FIG. 8), which stores programs or instructions. make.
  • the processing module 801 executes the program or instruction, the communication device 800 can perform the function of the first device in the channel state information reporting method shown in Figure 2, Figure 3, or Figure 5, or Figure 6, or Figure 7.
  • the processing module 801 involved in the communication device 800 can be implemented by a processor or a processor-related circuit component, and can be a processor or a processing unit;
  • the transceiver module 802 can be implemented by a transceiver or a transceiver-related circuit component, and can be a transceiver. transmitter or transceiver unit.
  • the communication device 800 may be the first device or the second device shown in FIG. 1 , or may be a chip (system) or other component or component provided in the first device or the second device. Or a device including the first device or the second device, which is not limited in the embodiments of the present application.
  • the technical effects of the communication device 800 can be referred to the technical effects of the channel state information reporting method shown in any one of FIG. 2, FIG. 3, or FIG. 5, or FIG. 6, or FIG. 7, which are not mentioned here. Again.
  • the communication device 800 may be adapted to the communication system shown in Figure 1 to perform the processing of channel state information shown in Figure 2, Figure 3, or Figure 5, or Figure 6, or Figure 7 The function of the second device in the reporting method.
  • the transceiver module 802 is used to receive the first indication information from the first device.
  • the first indication information is used to construct a first covariance matrix corresponding to a channel matrix
  • the channel matrix is used to indicate channel state information of a channel between the first device and the second device.
  • the processing module 801 is configured to determine the first covariance matrix corresponding to the channel matrix according to the first indication information.
  • the first indication information may include a superposition coefficient and a codebook vector.
  • a processing module specifically configured to determine the first covariance matrix according to the superposition coefficient and the codebook vector.
  • the superposition coefficient includes a first superposition coefficient used to indicate the characteristics of the angular delay power spectrum
  • the codebook vector includes first information used to indicate the angular delay.
  • the processing module is specifically configured to determine the first space-frequency joint covariance matrix according to the first superposition coefficient and the first information.
  • the transceiver module is specifically configured to receive the first indication information from the first device according to the first cycle.
  • the transceiver module 802 may also be configured to receive second indication information from the first device according to the second cycle.
  • the second indication information is used to indicate the first feedback coefficient, and the second period is smaller than the first period.
  • the first feedback coefficient is determined according to the first decomposition result of the first space-frequency joint covariance matrix and the channel matrix.
  • the first decomposition result is obtained by decomposing the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the processing module 801 may also be configured to determine an effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule.
  • the effective space-frequency joint feature base includes the first P columns of the space-frequency joint feature base, and P is a positive integer. And, determine the channel matrix according to the effective space-frequency joint characteristic base and the first feedback coefficient.
  • the first decomposition rule may include: an arrangement order of elements in the diagonal matrix of the first space-frequency joint covariance matrix decomposition, and a first space-frequency joint characteristic basis of the first space-frequency joint covariance matrix decomposition.
  • the type of row elements such as positive real numbers.
  • the first indication information may also be used to indicate: the first quantized vector of the first row elements of the first P columns in the space-frequency joint feature base decomposed by the first space-frequency joint covariance matrix.
  • P is a positive integer.
  • the processing module 801 is specifically configured to determine an effective space-frequency joint feature base of the first space-frequency joint covariance matrix according to the first decomposition rule and the first quantization vector.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angular power spectrum
  • the codebook vector may include second information used to indicate the angle.
  • the processing module 801 is specifically configured to determine the first spatial covariance matrix according to the second superposition coefficient and the second information.
  • the superposition coefficient may include a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include third information used to indicate the delay.
  • the processing module 801 is specifically configured to determine the first frequency domain covariance matrix according to the third superposition coefficient and the third information.
  • the superposition coefficient may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum and a third superposition coefficient used to indicate the characteristics of the delay power spectrum
  • the codebook vector may include a second superposition coefficient used to indicate the characteristics of the angle power spectrum.
  • the processing module 801 is specifically configured to determine the first spatial covariance matrix according to the second superposition coefficient and the second information. And, determine the first frequency domain covariance matrix according to the third superposition coefficient and the third information.
  • the transceiver module is specifically configured to receive the first indication information from the first device according to the first cycle.
  • the transceiver module 802 may also be configured to receive third indication information from the first device according to a fourth period; wherein the third indication information is used to indicate the second feedback coefficient, and the fourth period is smaller than the third period.
  • the second feedback coefficient is determined based on the second decomposition result of the first spatial domain covariance matrix, the third decomposition result of the first frequency domain covariance matrix and the channel matrix; wherein the second decomposition result is determined by the first spatial domain covariance matrix.
  • the covariance matrix is decomposed according to the second decomposition rule, and the third decomposition result is obtained by decomposing the first frequency domain covariance matrix according to the third decomposition rule.
  • the second decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first spatial covariance matrix, and the type of the first row elements of the spatial feature base of the first spatial covariance matrix.
  • the third decomposition rule may include: the arrangement order of elements in the diagonal matrix of the first frequency domain covariance matrix, and the type of the first row elements of the frequency domain feature base of the first frequency domain covariance matrix, such as positive real numbers.
  • the processing module 801 can also be used to determine the effective airspace feature base according to the second decomposition rule. According to the third decomposition rule, the effective frequency domain characteristic base is determined. And, determine the channel state information according to the effective spatial domain characteristic base, the effective frequency domain characteristic base and the second feedback coefficient. Further, the first indication information may also be used to indicate: the second quantization vector after quantization of the first row elements of the first K columns in the spatial feature base decomposed by the first spatial covariance matrix.
  • the processing module 801 is specifically configured to determine the effective spatial feature base according to the second decomposition rule and the second quantization vector.
  • the effective spatial feature base includes the first K columns of the spatial feature base of the first spatial covariance matrix.
  • the first indication information may also be used to indicate: the third quantization vector after quantization of the first row elements of the first D columns in the frequency domain feature base decomposed by the first frequency domain covariance matrix.
  • processing module 801 is specifically configured to determine an effective frequency domain feature base according to the third decomposition rule and the third quantization vector; wherein the effective frequency domain feature base includes the frequency domain feature base of the first frequency domain covariance matrix.
  • First column D is specifically configured to determine an effective frequency domain feature base according to the third decomposition rule and the third quantization vector; wherein the effective frequency domain feature base includes the frequency domain feature base of the first frequency domain covariance matrix.
  • the transceiver module 802 may include a receiving module and a sending module. Among them, the transceiver module 802 is used to implement the sending function and receiving function of the communication device 800.
  • the processing module 801 involved in the communication device 800 can be implemented by a processor or a processor-related circuit component, and can be a processor or a processing unit.
  • the transceiver module 802 may be implemented by a transceiver or a transceiver-related circuit component, and may be a transceiver or a transceiver unit.
  • the communication device 800 may be a first device or a second device, or may be a chip (system) or other component or component that may be disposed in the first device or the second device, or may include the first device. Or the device of the second device, this application does not limit this.
  • the technical effects of the communication device 800 can be referred to the technical effects of the channel state information reporting method shown in any one of FIG. 2, FIG. 3, or any one of FIGS. 5 to 7, which will not be described again here.
  • FIG. 9 is a second structural schematic diagram of a communication device provided by an embodiment of the present application.
  • the communication device may be a first device or a second device, or may be a chip (system) or other component or component that can be disposed on the first device or the second device.
  • the communication device 900 may include a processor 901 .
  • the communication device 900 may also include a memory 902 and/or a transceiver 903.
  • the processor 901 is coupled to the memory 902 and the transceiver 903, for example, through a communication bus.
  • the processor 901 is the control center of the communication device 900, and may be a processor or a collective name for multiple processing elements.
  • the processor 901 is one or more central processing units (CPUs), an application specific integrated circuit (ASIC), or one or more processors configured to implement the embodiments of the present application.
  • An integrated circuit such as one or more digital signal processors (DSP), or one or more field programmable gate arrays (FPGA).
  • DSP digital signal processors
  • FPGA field programmable gate arrays
  • the processor 901 can perform various functions of the communication device 900 by running or executing software programs stored in the memory 902 and calling data stored in the memory 902.
  • the processor 901 may include one or more CPUs, such as CPU0 and CPU1 shown in FIG. 9 .
  • the communication device 900 may also include multiple processors, such as the processor 901 and the processor 904 shown in FIG. 9 .
  • processors can be a single-core processor (single-CPU) or a multi-core processor (multi-CPU).
  • a processor here may refer to one or more devices, circuits, and/or processing cores for processing data (eg, computer program instructions).
  • the memory 902 is used to store the software program for executing the solution of the present application, and the processor 901 controls the execution.
  • the processor 901 controls the execution.
  • the memory 902 may be a read-only memory (ROM) or other type of static storage device that can store static information and instructions, a random access memory (random access memory, RAM) or a random access memory (RAM) that can store information and instructions. other instructions
  • ROM read-only memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • RAM random access memory
  • Transceiver 903 used for communication with other communication devices.
  • the communication device 900 is a first device, and the transceiver 903 can be used to communicate with a second device, or with another first device.
  • the communication device 900 is a second device, and the transceiver 903 can be used to communicate with the first device, or with another second device.
  • the transceiver 903 may include a receiver and a transmitter (not shown separately in Figure 9). Among them, the receiver is used to implement the receiving function, and the transmitter is used to implement the sending function.
  • the transceiver 903 can be integrated with the processor 901, or can exist independently and be coupled to the processor 901 through the interface circuit (not shown in Figure 9) of the communication device 900. This is not the case in the embodiment of this application. Specific limitations.
  • the structure of the communication device 900 shown in Figure 9 does not constitute a limitation on the communication device.
  • the actual communication device may include more or less components than shown in the figure, or some components may be combined, or Different component arrangements.
  • the technical effects of the communication device 900 can be referred to the technical effects of the channel state information reporting method described in the above method embodiment, which will not be described again here.
  • the processor in the embodiment of the present application can be a central processing unit (CPU).
  • the processor can also be other general-purpose processors, digital signal processors (DSP), special-purpose integrated processors, etc.
  • Circuit application specific integrated circuit, ASIC), off-the-shelf programmable gate array (field programmable gate array, FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc.
  • a general-purpose processor may be a microprocessor or the processor may be any conventional processor, etc.
  • non-volatile memory may be volatile memory or non-volatile memory, or may include both volatile and non-volatile memory.
  • non-volatile memory can be read-only memory (ROM), programmable ROM (PROM), erasable programmable read-only memory (erasable PROM, EPROM), electrically removable memory. Erase electrically programmable read-only memory (EPROM, EEPROM) or flash memory.
  • Volatile memory can be random access memory (RAM), which is used as an external cache.
  • RAM random access memory
  • static random access memory static random access memory
  • DRAM dynamic random access memory
  • RAM synchronous dynamic random access memory
  • SDRAM synchronous dynamic random access memory
  • double data rate SDRAM double data rate SDRAM
  • DDR SDRAM double data rate SDRAM
  • enhanced SDRAM enhanced synchronous dynamic random access memory
  • SLDRAM synchronous connection dynamic random access memory access memory
  • direct rambus RAM direct rambus RAM, DR RAM
  • the above embodiments may be implemented in whole or in part by software, hardware (such as circuits), firmware, or any other combination.
  • the above-described embodiments may be implemented in whole or in part in the form of a computer program product.
  • the computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on the computer, the processes or functions described in the embodiments of the present application are generated in whole or in part.
  • the computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices.
  • the computer instructions may be stored in or transmitted from one computer-readable storage medium to another, e.g., the computer instructions may be transferred from a website, computer, server, or data center Transmit to another website, computer, server or data center through wired (such as infrared, wireless, microwave, etc.) means.
  • the computer-readable storage medium may be any available medium that a computer can access, or a data storage device such as a server or a data center that contains one or more sets of available media.
  • the usable media may be magnetic media (eg, floppy disk, hard disk, tape), optical media (eg, DVD), or semiconductor media.
  • the semiconductor medium may be a solid state drive.
  • At least one refers to one or more, and “plurality” refers to two or more.
  • At least one of the following” or its Similar expressions refer to any combination of these items, including any combination of single items (items) or plural items (items).
  • at least one of a, b, or c can mean: a, b, c, ab, ac, bc, or abc, where a, b, c can be single or multiple .
  • the size of the sequence numbers of the above-mentioned processes does not mean the order of execution.
  • the execution order of each process should be determined by its functions and internal logic, and should not be used in the embodiments of the present application.
  • the implementation process constitutes any limitation.
  • the disclosed systems, devices and methods can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the units is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or can be integrated into another system, or some features can be ignored, or not implemented.
  • the coupling or direct coupling or communication connection between each other shown or discussed may be through some interfaces, and the indirect coupling or communication connection of the devices or units may be in electrical, mechanical or other forms.
  • the units described as separate components may or may not be physically separated.
  • the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed to multiple network units. Superior. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of this embodiment.
  • each functional unit in each embodiment of the present application can be integrated into one processing unit, each unit can exist physically alone, or two or more units can be integrated into one unit.
  • the functions are implemented in the form of software functional units and sold or used as independent products, they can be stored in a computer-readable storage medium.
  • the technical solution of the present application is essentially or the part that contributes to the existing technology or the part of the technical solution can be embodied in the form of a software product.
  • the computer software product is stored in a storage medium, including Several instructions are used to cause a computer device (which may be a personal computer, a server, or a second device, etc.) to execute all or part of the steps of the methods described in various embodiments of this application.
  • the aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), magnetic disk or optical disk and other media that can store program code. .

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Abstract

本申请提供一种信道状态信息的上报方法及通信装置，能够降低反馈开销。该方法包括：第一设备接收来自第二设备的参考信号。第一设备根据参考信号确定第一指示信息，并发送第一指示信息。其中，第一指示信息用于构建信道矩阵对应的协方差矩阵，信道矩阵用于指示第一设备与第二设备之间的信道的信道状态信息。

Description

信道状态信息的上报方法及通信装置
本申请要求于2022年07月30日提交国家知识产权局、申请号为202210912627.9、申请名称为“信道状态信息的上报方法及通信装置”的中国专利申请的优先权，其全部内容通过引用结合在本申请中。
技术领域
本申请涉及通信领域，尤其涉及一种信道状态信息的上报方法及通信装置。
背景技术
多输入多输出(multiple input and multiple output，MIMO)技术是长期演进(long term evolution，LTE)系统以及第五代(5th generation，5G)新空口(new radio，NR)的核心技术。在采用MIMO技术的通信系统中，若网络设备向终端设备发送数据，则需要根据下行信道的信道状态信息(channel state information，CSI)进行信号预编码，以使经过预编码的信号与信道匹配。
在频分双工(frequency-sivision duplexing，FDD)的通信系统中，终端设备可以接收来自网络设备的参考信号，并根据该参考信号计算出信道矩阵对应的协方差矩阵，进而根据信道矩阵对应的协方差矩阵构建特征基底。终端设备在反馈CSI时，可以将特征基底和特征基底的系数矩阵反馈给网络设备，网络设备接收该特征基底后，可以结合特征基底和特征基底的系数矩阵恢复CSI。
但是，上述方案中，终端设备确定特征基底，利用了信道的稀疏特性，需要对不同子带(subband)上的空域信息相关特性进行反馈，也就是说，需要上报所选择的特征基底和特征基底的全带宽的叠加系数，空口开销大。如何更高效地反馈CSI，是MIMO技术应用中亟需解决的问题。
发明内容
本申请实施例提供一种信道状态信息的上报方法及通信装置，能够降低开销。
为达到上述目的，本申请采用如下技术方案：
第一方面，提供一种信道状态信息的上报方法。该信道状态信息的上报方法包括：第一设备接收来自第二设备的参考信号。第一设备根据参考信号确定第一指示信息，并向第二设备发送第一指示信息。其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵，信道矩阵用于指示第一设备与第二设备之间的信道的信道状态信息。
基于第一方面所提供的信道状态信息的上报方法，通过第一设备将用于构建信道矩阵对应的协方差矩阵的第一指示信息发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，从而可以降低反馈开销，提高CSI的反馈效率。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一协方差矩阵，并根据信道矩阵对应的协方差矩阵确定特征基底。
示例性地，信道矩阵的维度可以为M×N维。第一设备根据参考信号确定第一指示信息，可以包括：第一设备根据参考信号确定信道矩阵，并根据信道矩阵确定信道列向量，接着，第一设备根据信道列向量确定第一指示信息。
一种可能的设计方案中，第一指示信息可以用于指示叠加系数和码本向量，叠加系数和码本向量用于确定第一协方差矩阵。
一种可能的设计方案中，第一协方差矩阵与信道矩阵对应的实际协方差矩阵之间满足预设的优化模型。如此，可以降低第一指示信息的数据量，从而进一步降低反馈开销。
示例性地，预设的优化模型可以包括：s.t.L≤Lmax。其中，min表示取最小值，“‖‖F”表示取F范数，R为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l<L， 且l为整数。αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。如此，在第一设备通过测量参考信号确定了信道矩阵并获得了R的情况下，可以通过上述优化模型获取相应的αl和wl，使得第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的优化模型的求解结果确定。
可选地，叠加系数可以包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量可以包括用于指示角度时延的第一信息，第一叠加系数和第一信息用于确定第一空频联合协方差矩阵，预设的优化模型包括：第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间满足的第一优化模型。如此，通过第一设备确定用于构建第一空频联合协方差矩阵的第一指示信息，并发送给第二设备，可以避免上报可直接用于恢复信道状态信息的大量信息，如空频联合特征基底以及空频联合特征基底对应的叠加系数。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一空频联合协方差矩阵，并根据信道矩阵对应的第一空频联合协方差矩阵确定空频联合特征基底，减少反馈的数据量，从而能够降低反馈开销，提高CSI的反馈效率。
进一步地，第一优化模型包括： 其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l0<L0，且l0为整数。为第l0个第一叠加系数，为第l0个多径角度对应的导向矢量，为的共轭转置，为第l0个相位变化向量，为的共轭，为的转置，为第l0个第一信息，s.t.为约束条件，L0为信道多径数目，为L0的最大取值，L0、均为大于0的整数。如此，在第一设备通过测量参考信号确定了信道矩阵，并获得了的情况下，可以通过上述第一优化模型获取相应的以及和使得第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第一优化模型的求解结果确定。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量可以包括用于指示角度的第二信息。其中，第二叠加系数和第二信息用于确定第一空域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足预设的第二优化模型。
如此，通过第一设备反馈用于构建第一空域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如空域特征基底以及空域特征基底对应的叠加系数。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵，并根据信道矩阵对应的第一空域协方差矩阵确定空域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
进一步地，第二优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算。为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。如此，在第一设备通过测量参考信号确定了信道矩阵并获得了的情况下，可以通过上述第二优化模型获取相应的和使得第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第一优化模型的求解结果确定。
可选地，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示时延的第三信息，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
如此，通过第一设备反馈用于构建第一频域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如频域特征基底以及频域特征基底对应的叠加系数。例如，可以由第二设备根据第一指示信息确定第一频域协方差矩阵，并根据信道矩阵对应的第一频域协方差矩阵确定频域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
进一步地，第三优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算。为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。如此，在第一设备通过测量参考信号确定了信道矩阵并获得了的情况下，可以通过上述第二优化模型使得第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第三优化模型的求解结果确定。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息，第二叠加系数和第二信息用于确定第一空域协方差矩阵，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型，以及第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
如此，通过第一设备反馈用于构建第一空域协方差矩阵和第一频域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如空域特征基底以及空域特征基底对应的叠加系数和频域特征基底以及频域特征基底对应的叠加系数。基于来自第一设备的第一指示信息确定第一空域协方差矩阵和第一频域协方差矩阵，例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵和第一频域协方差矩阵，并根据信道矩阵对应的第一空域协方差矩阵确定空域特征基底，根据信道矩阵对应的第一频域协方差矩阵确定频域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
进一步地，第二优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算。为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。第三优化模型可以包括： 其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算。为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
需要说明，第一设备向第二设备发送第一指示信息，可以包括：第一设备按照第一周期向第二设备发送第一指示信息。
进一步地，第一方面提供的方法还可以包括：第一设备按照第二周期向第二设备发送第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
示例性地，第一反馈系数根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。例如，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。更进一步地，第一指示信息还可以用于指示：第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量。其中，P为正整数。如此，在第一空频联合协方差矩阵存在重根的情况下，可以唯一确定第一分解结果，从而可以使第二设备确定的空频联合特征基底与用于确定第一反馈系数的空频联合特征基底一致，从而提高信道状态信息的精度。另外，在特征基底中特征向量按照能量从大到小排列的情况下，可以从空联合特征基底中选择能量较大的特征向量(列向量)用于恢复信道状态信息，从而兼顾上报开销和恢复的信道状态信息的精度。
此外，空频联合特征基底可以与第一反馈系数，即短周期系数结合以使第二设备能恢复完整的信道 状态信息。
需要说明，第一设备向第二设备发送第一指示信息，包括：第一设备按照第三周期向第二设备发送第一指示信息。
进一步地，第一方面提供的方法还可以包括：第一设备按照第四周期向第二设备发送第三指示信息。其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
示例性地，第二反馈系数根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。
例如，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中元素的排列顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素的类型。如此，可以减少分解结果，从而提高信道状态信息的精度。第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中元素的排列顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量。其中，K为正整数。如此，在第一空域协方差矩阵存在重根的情况下，可以唯一确定第二分解结果，从而可以使第二设备确定的空域特征基底与用于确定第二反馈系数的空域特征基底一致，从而提高信道状态信息的精度。
更进一步地，第一指示信息还可以用于指示：第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量。其中，D为正整数。如此，在第一频域协方差矩阵存在重根的情况下，可以唯一确定第三分解结果，从而可以使第二设备确定的频域特征基底与用于确定第二反馈系数的频域特征基底一致，从而提高信道状态信息的精度。
此外，空域特征基底、频域特征基底以及与第二反馈系数，即短周期反馈系数结合，可以使第二设备能恢复完整的信道状态信息。
第二方面，提供一种信道状态信息的上报方法。该信道状态信息的上报方法可以包括：第二设备接收来自第一设备的第一指示信息。其中，第一指示信息用于构建信道矩阵对应的协方差矩阵，信道矩阵用于指示第一设备与第二设备之间的信道的信道状态信息。第二设备根据第一指示信息确定信道矩阵对应的第一协方差矩阵。
基于第二方面所提供的信道状态信息的上报方法，第二设备通过接收来自于第一设备的用于构建信道矩阵对应的协方差矩阵的第一指示信息，以确定第一协方差矩阵，可以避免传输直接用于恢复信道状态信息的大量信息，从而可以降低反馈开销，提高CSI的反馈效率。
一种可能的设计方案中，第一指示信息可以包括叠加系数和码本向量。第二设备根据第一指示信息确定信道矩阵对应的第一协方差矩阵，可以包括：第二设备根据叠加系数和码本向量确定第一协方差矩阵。
可选地，叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量包括用于指示角度时延的第一信息。第二设备根据叠加系数和码本向量确定信道矩阵对应的第一协方差矩阵，包括：第二设备根据第一叠加系数和第一信息确定第一空频联合协方差矩阵。
需要说明，第二设备接收来自第一设备的第一指示信息，可以包括：第二设备按照第一周期接收来自第一设备的第一指示信息。
进一步地，第二方面提供的方法还可以包括：第二设备按照第二周期接收来自第一设备的第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
示例性地，第一反馈系数是根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定的。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
更进一步地，第二方面提供的方法还可以包括：第二设备根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底。其中，有效空频联合特征基底包括空频联合特征基底的前P列，P为正整数。第二设备根据有效空频联合特征基底和第一反馈系数确定信道矩阵。如此，在空频联合特征基底中特征向量按照能量从大到小排列的情况下，可以使第一设备从空联合特征基底中选择能量较大的特征向量(列向量)用于恢复信道状态信息，从而兼顾上报开销和恢复的信道状态信息的精度。
第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中的元素的排列顺序，以及第一 空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
再进一步地，第一指示信息还可以用于指示：第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量。其中，P为正整数。如此，在第一空频联合协方差矩阵存在重根的情况下，第二设备可以唯一确定第一分解结果，从而使第二设备确定的空频联合特征基底与用于确定第一反馈系数的空频联合特征基底一致，从而提高信道状态信息的精度。
此外，第二设备可以将有效空频联合特征基底与第一反馈系数，即短周期系数结合以恢复完整的信道状态信息。
在此情况下，第二设备根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底，可以包括：第二设备根据第一分解规则和第一量化向量，确定第一空频联合协方差矩阵的有效空频联合特征基底。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量可以包括用于指示角度的第二信息。第二设备根据叠加系数和码本向量确定第一协方差矩阵，可以包括：第二设备根据第二叠加系数和第二信息确定第一空域协方差矩阵。
可选地，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示时延的第三信息。第二设备根据叠加系数和码本向量确定第一协方差矩阵，可以包括：第二设备根据第三叠加系数和第三信息确定第一频域协方差矩阵。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息。第二设备根据叠加系数和码本向量确定第一协方差矩阵，包括：第二设备根据第二叠加系数和第二信息确定第一空域协方差矩阵。第二设备根据第三叠加系数和第三信息确定第一频域协方差矩阵。
需要说明，第二设备接收来自第一设备的第一指示信息，可以包括：第二设备按照第三周期接收来自第一设备的第一指示信息。
进一步地，第二方面提供的方法还可以包括：第二设备按照第四周期接收来自第一设备的第三指示信息。其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
示例性地，第二反馈系数是根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定的。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。例如，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一空域协方差矩阵的特征基底的第一行元素的类型。第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型，如正实数。
更进一步地，第二方面提供的方法还可以包括：第二设备根据第二分解规则，确定有效空域特征基底。第二设备根据第三分解规则，确定有效频域特征基底。第二设备根据有效空域特征基底、有效频域特征基底和第二反馈系数确定信道状态信息。
再进一步地，第一指示信息还可以用于指示：第一空域协方差矩阵分解后的空域特征基底中前K列的第一行元素量化后的第二量化向量。
示例性地，第二设备根据第二分解规则，确定有效空域特征基底，包括：第二设备根据第二分解规则和第二量化向量，确定有效空域特征基底。其中，有效空域特征基底包括第一空域协方差矩阵的空域特征基底的前K列。如此，在第一空域协方差矩阵存在重根的情况下，第二设备可以唯一确定第二分解结果，使第二设备确定的空域特征基底与用于确定第二反馈系数的空域特征基底一致，从而提高信道状态信息的精度。
再进一步地，第一指示信息还可以用于指示：第一频域协方差矩阵分解后的频域特征基底中前D列的第一行元素量化后的第三量化向量。
在此情况下，第二方面提供的方法还可以包括：第二设备根据第三分解规则和第三量化向量，确定有效频域特征基底。其中，有效频域特征基底包括第一频域协方差矩阵的频域特征基底的前D列。如此，在第一频域协方差矩阵存在重根的情况下，可以唯一确定第三分解结果，从而可以使第二设备确定的频域特征基底与用于确定第二反馈系数的频域特征基底一致，从而提高信道状态信息的精度。
此外，第二设备可以将空域特征基底、频域特征基底与第二反馈系数，即短周期反馈系数结合，从 而恢复完整的信道状态信息。
第三方面，提供一种通信装置。该通信装置包括：处理模块和收发模块。其中，收发模块，用于接收来自第二设备的参考信号。处理模块，用于根据参考信号确定第一指示信息。其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵，信道矩阵用于指示通信装置与第二设备之间的信道的信道状态信息。收发模块，用于向第二设备发送第一指示信息。
一种可能的设计方案中，第一指示信息可以包括叠加系数和码本向量，叠加系数和码本向量用于确定第一协方差矩阵。
一种可能的设计中，第一协方差矩阵与信道矩阵对应的实际协方差矩阵之间满足预设的优化模型。
可选地，预设的优化模型可以包括：s.t.L≤Lmax。其中，min表示取最小值，“‖‖F”表示取F范数，R为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l<L，且l为整数。αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。
可选地，叠加系数可以包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量可以包括用于指示角度的第一信息，第一叠加系数和第一信息用于确定第一空频联合协方差矩阵，预设的优化模型包括：第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间满足的第一优化模型。
进一步地，第一优化模型可以包括： 其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l0<L0，且l0为整数。为第l0个第一叠加系数，为第l0个多径角度对应的导向矢量，为的共轭转置，为第l0个相位变化向量，为的共轭，为的转置，为第l0个第一信息，s.t.为约束条件，L0为信道多径数目，为L0的最大取值，L0、均为大于0的整数。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量包括用于指示角度的第二信息。其中，第二叠加系数和第二信息用于确定第一空域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型。
进一步地，第二优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算。为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。
可选地，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示时延的第三信息，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
进一步地，第三优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算。为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息，第二叠加系数和第二信息用于确定第一空域协方差矩阵，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足预设的第二优化模型，以及第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
进一步地，第二优化模型可以包括：其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算。为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。第三优化模型可以包括： 其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算。为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
需要说明，收发模块，具体用于按照第一周期向第二设备发送第一指示信息。
进一步地，收发模块，还可以用于按照第二周期向第二设备发送第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
示例性地，第一反馈系数根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
例如，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
需要说明，收发模块，具体用于按照第三周期向第二设备发送第一指示信息。
进一步地，收发模块，还可以用于按照第四周期向第二设备发送第三指示信息。其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
示例性地，第二反馈系数根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。
例如，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中元素的排列顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量。其中，K为正整数。
例如，第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中元素的排列顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型。
更进一步地，第一指示信息还可以用于指示：第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量。其中，D为正整数。
可选地，收发模块可以包括接收模块和发送模块。其中，收发模块用于实现第三方面所述的通信装置的发送功能和接收功能。
可选地，第三方面所述的通信装置还可以包括存储模块，该存储模块存储有程序或指令。当处理模块执行该程序或指令时，使得该通信装置可以执行第一方面所述的信道状态信息的上报方法。
需要说明的是，第三方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
此外，第三方面所述的通信装置的技术效果可以参考第一方面所述的信道状态信息的上报方法的技术效果，此处不再赘述。
第四方面，提供一种通信装置。该通信装置包括：处理模块和收发模块。收发模块，用于接收来自第一设备的第一指示信息。其中，第一指示信息用于构建信道矩阵对应的协方差矩阵，信道矩阵用于指示第一设备与第二设备之间的信道的信道状态信息。处理模块，用于根据第一指示信息确定信道矩阵对 应的第一协方差矩阵。
一种可能的设计方案中，第一指示信息可以包括叠加系数和码本向量。处理模块，具体用于根据叠加系数和码本向量确定第一协方差矩阵。
可选地，叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量包括用于指示角度的第一信息。处理模块，具体用于根据第一叠加系数和第一信息确定第一空频联合协方差矩阵。
需要说明，收发模块，具体用于按照第一周期接收来自第一设备的第一指示信息。
进一步地，收发模块，还可以用于按照第二周期接收来自第一设备的第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
示例性地，第一反馈系数是根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定的。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
更进一步地，处理模块，还可以用于根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底。其中，有效空频联合特征基底包括空频联合特征基底的前P列，P为正整数。以及，根据有效空频联合特征基底和第一反馈系数确定信道矩阵。
示例性地，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中的元素的排列顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
再进一步地，第一指示信息还可以用于指示：第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
在此情况下，处理模块，具体用于根据第一分解规则和第一量化向量，确定第一空频联合协方差矩阵的有效空频联合特征基底。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量包括用于指示角度的第二信息。处理模块，具体用于根据第二叠加系数和第二信息确定第一空域协方差矩阵。
可选地，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量包括用于指示时延的第三信息。处理模块，具体用于根据第三叠加系数和第三信息确定第一频域协方差矩阵。
可选地，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，码本向量包括用于指示角度的第二信息和用于指示时延的第三信息。处理模块，具体用于根据第二叠加系数和第二信息确定第一空域协方差矩阵。以及，根据第三叠加系数和第三信息确定第一频域协方差矩阵。
需要说明，收发模块，具体用于按照第一周期接收来自第一设备的第一指示信息。
进一步地，收发模块，还可以用于按照第四周期接收来自第一设备的第三指示信息。其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
示例性地，第二反馈系数是根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定的。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。例如，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素的类型。第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型，如正实数。
更进一步地，处理模块，还可以用于根据第二分解规则，确定有效空域特征基底。根据第三分解规则，确定有效频域特征基底。以及，根据有效空域特征基底、有效频域特征基底和第二反馈系数确定信道状态信息。
再进一步地，第一指示信息还可以用于指示：第一空域协方差矩阵分解后的空域特征基底中前K列的第一行元素量化后的第二量化向量。
示例性地，处理模块，具体用于根据第二分解规则和第二量化向量，确定有效空域特征基底。其中，有效空域特征基底包括第一空域协方差矩阵的空域特征基底的前K列。再进一步地，第一指示信息还可以用于指示：第一频域协方差矩阵分解后的频域特征基底中前D列的第一行元素量化后的第三量化向量。
在此情况下，处理模块，具体用于根据第三分解规则和第三量化向量，确定有效频域特征基底。其中，有效频域特征基底包括第一频域协方差矩阵的频域特征基底的前D列。
可选地，收发模块可以包括接收模块和发送模块。其中，收发模块用于实现第四方面所述的通信装置的发送功能和接收功能。
可选地，第四方面所述的通信装置还可以包括存储模块，该存储模块存储有程序或指令。当处理模块执行该程序或指令时，使得该通信装置可以执行第一方面所述的信道状态信息的上报方法。
需要说明的是，第四方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
此外，第四方面所述的通信装置的技术效果可以参考第一方面所述的信道状态信息的上报方法的技术效果，此处不再赘述。
第五方面，提供一种通信装置。该通信装置用于执行第一方面至第二方面中任意一种实现方式所述的信道状态信息的上报方法。
在本申请中，第五方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
应理解，第五方面所述的通信装置包括实现上述第一方面至第二方面中任一方面所述的信道状态信息的上报方法相应的模块、单元、或手段(means)，该模块、单元、或手段可以通过硬件实现，软件实现，或者通过硬件执行相应的软件实现。该硬件或软件包括一个或多个用于执行上述信道状态信息的上报方法所涉及的功能的模块或单元。
第六方面，提供一种通信装置。该通信装置包括：处理器，该处理器用于执行第一方面至第二方面中任意一种可能的实现方式所述的信道状态信息的上报方法。
在一种可能的设计方案中，第六方面所述的通信装置还可以包括收发器。该收发器可以为收发电路或接口电路。该收发器可以用于第六方面所述的通信装置与其他通信装置通信。
在一种可能的设计方案中，第六方面所述的通信装置还可以包括存储器。该存储器可以与处理器集成在一起，也可以分开设置。该存储器可以用于存储第一方面至第二方面中任一方面所述的信道状态信息的上报方法所涉及的计算机程序和/或数据。
在本申请中，第六方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
第七方面，提供一种通信装置。该通信装置包括：处理器，该处理器与存储器耦合，该处理器用于执行存储器中存储的计算机程序，以使得该通信装置执行第一方面至第二方面中任意一种可能的实现方式所述的信道状态信息的上报方法。
在一种可能的设计方案中，第七方面所述的通信装置还可以包括收发器。该收发器可以为收发电路或接口电路。该收发器可以用于第七方面所述的通信装置与其他通信装置通信。
在本申请中，第七方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
第八方面，提供了一种通信装置，包括：处理器和存储器。该存储器用于存储计算机程序，当该处理器执行该计算机程序时，以使该通信装置执行第一方面至第二方面中的任意一种实现方式所述的信道状态信息的上报方法。
在一种可能的设计方案中，第八方面所述的通信装置还可以包括收发器。该收发器可以为收发电路或接口电路。该收发器可以用于第八方面所述的通信装置与其他通信装置通信。
在本申请中，第八方面所述的通信装置可以为第一方面所述的第一设备或第二方面所述的第二设备，或者可设置于该第一设备或第二设备中的芯片(系统)或其他部件或组件，或者包含该第一设备或第二设备的装置。
第九方面，提供了一种通信装置，包括：处理器。该处理器用于与存储器耦合，并读取存储器中的计算机程序之后，根据该计算机程序执行如第一方面至第二方面中的任意一种实现方式所述的信道状态信息的上报方法。
在一种可能的设计方案中，第九方面所述的通信装置还可以包括收发器。该收发器可以为收发电路或接口电路。该收发器可以用于第十一方面所述的通信装置与其他通信装置通信。
在本申请中，第九方面所述的通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
此外，上述第五方面至第九方面所述的通信装置的技术效果，可以参考上述第一方面至第二方面所述的信道状态信息的上报方法的技术效果，此处不再赘述。
第十方面，提供一种处理器。其中，处理器用于执行第一方面至第二方面中任意一种可能的实现方式所述的信道状态信息的上报方法。
第十一方面，提供一种通信系统。该通信系统包括一个或多个第一设备，以及一个或多个第二设备。
第十二方面，提供一种计算机可读存储介质，包括：计算机程序或指令。当该计算机程序或指令在计算机上运行时，使得该计算机执行第一方面至第二方面中任意一种可能的实现方式所述的信道状态信息的上报方法。
第十三方面，提供一种计算机程序产品，包括计算机程序或指令，当该计算机程序或指令在计算机上运行时，使得该计算机执行第一方面至第二方面中任意一种可能的实现方式所述的信道状态信息的上报方法。
附图说明
图1为本申请实施例提供的通信系统的架构示意图；
图2为本申请实施例提供的信道状态信息的上报方法的一种流程示意图；
图3为本申请实施例提供的信道状态信息的上报方法的另一种流程示意图；
图4为本申请实施例提供的多径角度的示意图；
图5为本申请实施例提供的信道状态信息的上报方法的又一种流程示意图；
图6为本申请实施例提供的信道状态信息的上报方法的又一种流程示意图；
图7为本申请实施例提供的信道状态信息的上报方法的又一种流程示意图；
图8为本申请实施例提供的通信装置的结构示意图一；
图9为本申请实施例提供的通信装置的结构示意图二。
具体实施方式
为便于理解本申请实施例，下面对本申请实施例中涉及到的术语做简单介绍。
1、导向矢量：导向矢量是阵列天线的所有阵元对具有单位能量窄带信源的响应。
2、相位变化向量：表征相位变化的一组系数构成的向量。
3、角度时延功率谱：信道在角度时延域上的功率分布函数。
4、角度功率谱：信道在角度域上的功率分布函数。
5、时延功率谱：信道在时延域上的功率分布函数。
6、码本向量：码本中某一列元素构成的向量。
下面将结合附图，对本申请中的技术方案进行描述。
本申请实施例的技术方案可以应用于各种通信系统，例如无线保真(wireless fidelity，WiFi)系统，车到任意物体(vehicle to everything，V2X)通信系统、设备间(device-todevie，D2D)通信系统、车联网通信系统、第4代(4th generation，4G)移动通信系统，如长期演进(long term evolution，LTE)系统、全球互联微波接入(worldwide interoperability for microwave access，WiMAX)通信系统、第五代(5th generation，5G)移动通信系统，如新空口(new radio，NR)系统，以及未来的通信系统，如第六代(6th generation，6G)移动通信系统等。
本申请将围绕可包括多个设备、组件、模块等的系统来呈现各个方面、实施例或特征。应当理解和明白的是，各个系统可以包括另外的设备、组件、模块等，并且/或者可以并不包括结合附图讨论的所有设备、组件、模块等。此外，还可以使用这些方案的组合。
另外，在本申请实施例中，“示例地”、“例如”等词用于表示作例子、例证或说明。本申请中被描述为“示例”的任何实施例或设计方案不应被解释为比其它实施例或设计方案更优选或更具优势。确切而言，使用示例的一词旨在以具体方式呈现概念。
本申请实施例中，“信息(information)”，“信号(signal)”，“消息(message)”，“信道(channel)”、“信令(singaling)”有时可以混用，应当指出的是，在不强调其区别时，其所要表达的含义是一致的。“的(of)”，“相应的(corresponding，relevant)”和“对应的(corresponding)”有时可以混用，应当指出的是，在不强调其区别时，其所要表达的含义是一致的。
本申请实施例中，有时候下标如W1可能会笔误为非下标的形式如W1，在不强调其区别时，其所要表达的含义是一致的。
多输入多输出(multiple input and multiple output，MIMO)技术是长期演进(long term evolution，LTE)系统以及第五代(5th generation，5G)新空口(new radio，NR)的核心技术。在采用MIMO技术的通信系统中，若发送设备(如网络设备)向接收设备(如终端设备)发送数据，则需要根据下行信道状态信息(channel state information，CSI)进行信号预编码，以使经过预编码的信号与信道匹配。
现有相关技术中，终端设备接收来自网络设备的参考信号，并根据该参考信号确定信道矩阵对应的协方差矩阵，进而根据信道矩阵对应的协方差矩阵确定信道矩阵对应的特征基底和特征基底对应的叠加系数。终端设备向网络设备反馈信道矩阵对应的特征基底和特征基底对应的叠加系数。网络设备接收该特征基底和特征基底对应的叠加系数后，可以恢复信道状态信息。
上述方案利用了信道在空域(即角度域)和频域(即时延域)的稀疏特性，需要对不同子带(subband)上的空域信息相关特性进行反馈，因此需要上报特征基底和全带宽(full bandwidth)(包括所有子带)的叠加系数。其中，终端设备可以按照如下方式上报叠加系数：终端设备可以将叠加系数分成多个部分，其中，部分叠加系数按照长周期上报给网络设备，部分叠加系数按照短周期上报给网络设备。其中，按照长周期上报的叠加系数的数量，与特征基底中特征向量的数量以及特征基底中的每个特征向量对应的叠加系数的数量相关。
以终端设备按照长周期分别上报空域和频域的叠加系数为例，在信道对应的叠加系数矩阵为C，且C＝C1·C2·C3的情况下，终端设备可以将C1、C3按照长周期上报给网络设备，将C2按照短周期上报给网络设备，以用于恢复完整的信道状态信息。其中，C1为空域特征基底中每个特征向量对应的叠加系数所构成的系数矩阵，C1中元素数量为：空域特征基底中特征向量的数量与空域特征基底中每个特征向量对应的叠加系数的数量之积。C3为频域特征基底中每个特征向量对应的叠加系数所构成的系数矩阵，C3中元素数量为：频域特征基底中特征向量的数量与频域特征基底中每个特征向量对应的叠加系数的数量之积。C2为空域特征基底中每个特征向量和频域特征基底中中每个特征向量构成的一组空频向量对应的叠加系数所构成的系数矩阵，或者空域特征基底中每个特征向量和频域特征基底中每个特征向量对应的叠加系数所构成的系数矩阵。终端设备按照长周期上报的叠加系数的总量为C1和C3的总量。由此可见，终端设备以长周期反馈的叠加系数的开销大，反馈效率低。
应理解，长周期的时长大于短周期的时长，例如长周期的时长为短周期的时长的多个整数倍。需要说明的是，短周期上报是基于一次参考信号测量的上报，长周期上报是基于多次参考信号测量的上报，具体基于几次本申请在此不具体限定。此外，还要说明的是，参考信号可以是网络设备发送的信道状态信息-参考信号(channel state information-reference signal，CSI-RS)、同步信号和物理广播信道块(synchronization signal and physical broadcast channel block，简称SSB)、解调参考信号(demodulation reference signal，DMRS)等，本申请在此不具体限定。
为了解决终端设备长周期反馈的空口开销大的问题，本申请实施例提供了一种信道状态信息的上报方法，该信道状态信息的上报方法中，第一设备可以根据信道矩阵确定第一指示信息，并发送给第二设备。其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵。如此，上报用于构建信道矩阵对应的协方差矩阵的第一指示信息，以避免上报直接用于恢复信道状态信息的大量信息，从而可以降低反馈开销，提高CSI的反馈效率。此外，第二设备可以根据第一指示信息确定信道矩阵对应的第一协方差矩阵，并根据信道矩阵对应的第一协方差矩阵确定特征基底以及特征基底对应的叠加系数，进一步地，特征基底以及特征基底对应的叠加系数可以与短周期系数结合以恢复完整的信道状态信息。
本申请实施例描述的网络架构以及业务场景是为了更加清楚的说明本申请实施例的技术方案，并 不构成对于本申请实施例提供的技术方案的限定，本领域普通技术人员可知，随着网络架构的演变和新业务场景的出现，本申请实施例提供的技术方案对于类似的技术问题，同样适用。
为便于理解本申请实施例，首先以图1中示出的通信系统为例详细说明适用于本申请实施例的通信系统。示例性地，图1为本申请实施例提供的信道状态信息的上报方法所适用的一种通信系统的架构示意图。
如图1所示，该通信系统包括第一设备(101a、101b)和第二设备102。第二设备102与第一设备101a之间、第二设备102与第一设备101b之间可以通信。
其中，第二设备102为发送数据的设备，第一设备(101a、101b)为接收数据的设备。第二设备102可以是网络设备或终端设备，第一设备(101a、101b)可以是网络设备或终端设备。
示例性地，第一设备(101a、101b)为网络设备，第二设备102为网络设备。或者，第一设备(101a、101b)为终端设备，第二设备102为网络设备。或者，第一设备(101a、101b)为终端设备，第二设备102为终端设备。
可理解，本申请中，第一设备可以为更多个。
其中，上述网络设备为位于上述通信系统的网络侧，且具有无线收发功能的设备或可设置于该设备的芯片或芯片系统。网络设备包括但不限于：无线保真(wireless fidelity，WiFi)系统中的接入点(access point，AP)，如家庭网关、路由器、服务器、交换机、网桥等，演进型节点B(evolved Node B，eNB)、无线网络控制器(radio network controller，RNC)、节点B(Node B，NB)、基站控制器(base station controller，BSC)、基站收发台(base transceiver station，BTS)、家庭基站(例如，home evolved NodeB，或home Node B，HNB)、基带单元(baseband unit，BBU)，无线中继节点、无线回传节点、传输点(transmission and reception point，TRP或者transmission point，TP)等，还可以为5G，如，新空口(new radio，NR)系统中的gNB，或，传输点(TRP或TP)，5G系统中的基站的一个或一组(包括多个天线面板)天线面板，或者，还可以为构成gNB或传输点的网络节点，如基带单元(BBU)，或，分布式单元(distributed unit，DU)、具有基站功能的路边单元(road side unit，RSU)等。
上述终端设备为接入上述通信系统，且具有无线收发功能的终端或可设置于该终端的芯片或芯片系统。终端设备也可以称为接入终端、用户单元、用户站、移动站、移动台、远方站、远程终端、移动设备、用户终端、终端、无线通信设备、用户代理或用户装置。本申请的实施例中的第一设备可以是手机(mobile phone)、平板电脑(Pad)、带无线收发功能的电脑、虚拟现实(virtual reality，VR)第一设备、增强现实(augmented reality，AR)第一设备、工业控制(industrial control)中的无线终端、无人驾驶(self driving)中的无线终端、远程医疗(remote medical)中的无线终端、智能电网(smart grid)中的无线终端、运输安全(transportation safety)中的无线终端、智慧城市(smart city)中的无线终端、智慧家庭(smart home)中的无线终端、车载终端、具有终端功能的RSU等。本申请的第一设备还可以是作为一个或多个部件或者单元而内置于车辆的车载模块、车载模组、车载部件、车载芯片或者车载单元，车辆通过内置的所述车载模块、车载模组、车载部件、车载芯片或者车载单元可以实施本申请提供的信道状态信息的上报方法。
需要说明的是，本申请实施例提供的信道状态信息的上报方法，可以适用于图1所示的任意两个节点之间，如第一设备与第二设备之间，具体实现可以参考下述方法实施例，此处不再赘述。
应当指出的是，本申请实施例中的方案还可以应用于其他通信系统中，相应的名称也可以用其他通信系统中的对应功能的名称进行替代。
应理解，图1仅为便于理解而示例的简化示意图，该通信系统中还可以包括其他第二设备，和/或，其他第一设备，图1中未予以画出。
本文具体提供了如下几种实施例，下面结合图2、图3以及图5至图7，以具体的方法实施例对本申请的技术方案进行详细说明。下面这几个具体的实施例可以相互结合，对于相同或相似的概念或过程可能在某些实施例不再赘述。需要说明的是，图2、图3以及图5至图7是本申请的方法实施例的示意性流程图，示出了该方法的详细的通信步骤或操作，但这些步骤或操作仅是示例，本申请实施例还可以执行其它操作或者图2、图3以及图5至图7中的各种操作的变形。此外，图2、图3以及图5至图7中的各个步骤可以分别按照与图2、图3以及图5至图7所呈现的不同的顺序来执行，并且有可能并非要执行图2、图3以及图5至图7中的全部操作。
示例性地，图2为本申请实施例提供的信道状态信息的上报方法的一种流程示意图。该信道状态信息的上报方法可以适用于图1所示的第二设备与第一设备之间的通信。
如图2所示，该信道状态信息的上报方法包括如下步骤：
S201，第二设备发送参考信号。相应地，第一设备接收参考信号。
示例性地，参考信号可以是CSI-RS(例如第二设备是网络设备，第一设备是终端设备)或信道探测参考信号(sounding reference signal，SRS)(例如第一设备是终端设备，第二设备是网络设备)。应理解，参考信号还可以是其他信号，如小区参考信号(cell-specific reference signal，CRS)、SSB、DMRS、跟踪参考信号(tracking reference signal，TRS)等，本申请对此不做限定。
S202，第一设备根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵。信道矩阵用于指示第一设备与第二设备之间传输信道的CSI。信道矩阵对应的第一协方差矩阵可以包括如下一项或多项：信道矩阵对应的第一空频联合协方差矩阵、信道矩阵对应的第一空域协方差矩阵、信道矩阵对应的第一频域协方差矩阵。
示例性的，信道矩阵可以由第一设备根据接收到的参考信号(如CSI-RS)确定。信道矩阵的维度可以为M×N维。M≥1，N≥1，M和N均是整数，M为第二设备的发送天线端口数量，N为第二设备传输参考信号的频域单元数量。频域单元可以为子载波(subcarrier)、或资源块(resource block，RB)、或子带(subband)。
需要说明的是，在本申请中，“用于指示”可以包括用于直接指示和用于间接指示。当描述某一指示信息用于指示A时，可以包括该指示信息直接指示A或间接指示A，而并不代表该指示信息中一定携带有A。
将指示信息所指示的信息称为待指示信息，则具体实现过程中，对待指示信息进行指示的方式有很多种，例如但不限于，可以直接指示待指示信息，如待指示信息本身或者该待指示信息的索引等。也可以通过指示其他信息来间接指示待指示信息，其中该其他信息与待指示信息之间存在关联关系。还可以仅仅指示待指示信息的一部分，而待指示信息的其他部分则是已知的或者提前约定的。例如，还可以借助预先约定(例如协议规定)的各个信息的排列顺序来实现对特定信息的指示，从而在一定程度上降低指示开销。同时，还可以识别各个信息的通用部分并统一指示，以降低单独指示同样的信息而带来的指示开销。例如，本领域的技术人员应当明白，预编码矩阵是由预编码向量组成的，预编码矩阵中的各个预编码向量，在组成或者其他属性方面，可能存在相同的部分。
此外，具体的指示方式还可以是现有各种指示方式，例如但不限于，上述指示方式及其各种组合等。各种指示方式的具体细节可以参考现有技术，本文不再赘述。由上文所述可知，举例来说，当需要指示相同类型的多个信息时，可能会出现不同信息的指示方式不相同的情形。具体实现过程中，可以根据具体的需要选择所需的指示方式，本申请实施例对选择的指示方式不做限定，如此一来，本申请实施例涉及的指示方式应理解为涵盖可以使得待指示方获知待指示信息的各种方法。
待指示信息可以作为一个整体一起发送，也可以分成多个子信息分开发送，而且这些子信息的发送周期和/或发送时机可以相同，也可以不同。具体发送方法本申请不进行限定。其中，这些子信息的发送周期和/或发送时机可以是预先定义的，例如根据协议预先定义的，也可以是发射端设备通过向接收端设备发送配置信息来配置的。其中，该配置信息可以例如但不限于包括无线资源控制信令、介质接入控制(medium access control，MAC)层信令和物理层信令中的一种或者至少两种的组合。其中，无线资源控制信令例如包无线资源控制(radio resource control，RRC)信令；MAC层信令例如包括MAC控制元素(control element，CE)；物理层信令例如包括下行控制信息(downlink control information，DCI)。
第一设备根据参考信号确定第一指示信息，可以包括步骤2.1和步骤2.2。
步骤2.1第一设备根据参考信号确定信道矩阵。
步骤2.2，第一设备根据信道矩阵确定第一指示信息。
第一指示信息用于指示叠加系数和码本向量，叠加系数和码本向量用于确定第一协方差矩阵。也就是说，第一协方差矩阵为根据第一指示信息构建的信道矩阵所对应的协方差矩阵。
其中，第一协方差矩阵与信道矩阵对应的实际协方差矩阵之间可以满足预设的优化模型。
示例性地，预设的优化模型可以包括如下公式(1)和公式(2)。换言之，预设的优化模型可以根据如下公式(1)和公式(2)确定：

s.t.L≤Lmax；     (2)
其中，min表示取最小值，“‖‖F”表示取F范数，R为信道矩阵对应的实际协方差矩阵，Σ表示求和运算，0≤l<L，且l为整数。αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。
如此，在第一设备通过测量参考信号确定了信道矩阵并获得了R的情况下，可以通过上述优化模型获取相应的αl和wl，使得第一协方差矩阵与信道矩阵对应的实际协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的优化模型的求解结果确定。
需要说明，R的维度与R的类型相关。示例性地，若R为信道矩阵对应的实际空频联合协方差矩阵，则R为MN×MN的矩阵。若R为信道矩阵对应的实际空域协方差矩阵，则R为M×M的矩阵。若R为信道矩阵对应的实际频域协方差矩阵，则R为N×N的矩阵。
可理解，叠加系数可以是复数，码本向量可以是基底向量。基底向量可以是基底的某一行元素或某一列元素构成的向量。其中，基底可以包括如下一项或多项：空域基底、频域基底、空频联合基底、导向矢量构成的基底、相位变化向量构成的基底、或根据导向矢量和相位变化向量确定的基底。
假设预设的优化模型的求解结果中叠加系数为叠加系数码本向量为则第一指示信息指示的叠加系数可以为叠加系数第一指示信息指示的码本向量为其中，叠加系数为叠加系数量化得到。
关于步骤2.2的实现原理可以参考下述方法实施例中步骤3.2、步骤5.2、步骤6.2、或步骤7.2，此处不再赘述。
S203，第一设备发送第一指示信息。相应地，第二设备接收第一指示信息。
其中，第一指示信息可以承载于物理上行链路控制信道(physical uplink control channel，PUCCH)或物理层上行共享信道(physical uplink share channel，PUSCH)中。终端设备通过物理上行资源向网络设备发送第一指示信息的具体方法可以与现有技术相同，为了简洁，这里省略对其具体过程的详细说明。
关于S203的具体实现原理可以参考下述方法实施例中S303、S503、S603、或S703，此处不再赘述。
基于上述图2所提供的信道状态信息的上报方法，通过第一设备将用于构建信道矩阵对应的第一协方差矩阵的第一指示信息发送给第二设备，可以避免传输直接用于恢复信道状态信息的大量信息，从而可以降低反馈开销，提高CSI的反馈效率。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一协方差矩阵，并根据信道矩阵对应的协方差矩阵确定特征基底以及特征基底对应的长周期系数。进一步地，第二设备可以将特征基底以及特征基底对应的长周期系数可以与短周期系数结合以恢复完整的信道状态信息。
以下结合具体的实施例说明在不同情况下本申请实施例提供的信道状态信息的上报方法。在一种可能的实施方式中，第一设备可以在空频联合域进行处理并上报与恢复信道状态信息相关的第一指示信息。在此情况下，第一设备可以向第二设备发送用于确定第一空频联合协方差矩阵的第一指示信息。如图3所示，该信道状态信息的上报方法包括：
S301，第二设备发送参考信号。相应地，第一设备接收参考信号。
关于S301的实现原理可以参考上述S201的相关介绍，此处不再赘述。
S302，第一设备根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一空频联合协方差矩阵。
示例性地，第一指示信息用于指示叠加系数和码本向量，叠加系数和码本向量用于确定第一空频联合协方差矩阵。其中，第一空频联合协方差矩阵为信道矩阵对应的实际空频联合协方差矩阵的近似矩阵。在此情况下，前述S202中描述的第一协方差矩阵对应为第一空频联合协方差矩阵。
第一设备根据参考信号确定第一指示信息，可以包括步骤3.1和步骤3.2：
步骤3.1，第一设备根据参考信号确定信道矩阵。
关于步骤3.1的实现原理可以参考前述步骤2.1的相关介绍，此处不再赘述。
步骤3.2，第一设备根据信道矩阵确定第一指示信息。
其中，步骤3.2可以包括步骤3.2-1至步骤3.2-3。
步骤3.2-1，第一设备根据信道矩阵确定信道列向量。
一种示例中，示例性地，信道列向量可以满足如下公式(3)至公式(5)所示的关系：
H＝SCFH；     (3)

其中，H为信道矩阵，表示复数，M为第二设备的天线端口数目，N为频率单元个数，表示维度为M×N的矩阵，S为空域基底，L0为信道多径数目，表示维度为M×L0的矩阵，C为对角阵，表示维度为L0×L0的矩阵，F为频域基底，表示维度为N×L0的矩阵，FH为F的共轭转置矩阵，h为信道列向量，h的维度为MN×1，即h为MN行1列的向量，F*为F的共轭矩阵，⊙表示Khatri-Rao积。diag()表示构造对角矩阵，c为C的对角元素构成的向量。表示克罗内克尔(kronecker)积。表示维度为MN×1的矩阵。(F*⊙S)[:,l0]表示(F*⊙S)的第l0列构成的列向量，F(:,l0)表示F的第l0列构成的列向量，[F(:,l0)]*表示F(:,l0)的共轭，S(:,l0)表示S的第l0列构成的列向量，0<l0<L0。M、N均为正整数。
另一种示例中，信道列向量h与信道矩阵之间可以满足如下公式(6)所示的关系：
其中，n＝1，2，…，N。H(:,n)表示信道矩阵的第n列。
步骤3.2-2，第一设备根据信道列向量确定信道矩阵对应的实际空频联合协方差矩阵。
例如，对于双极化天线阵列而言，信道矩阵对应的实际空频联合协方差矩阵为极化间平均空频联合协方差矩阵信道列向量与信道矩阵对应的实际空频联合协方差矩阵之间满足如下公式(7)所示的关系：
其中，为信道矩阵对应的极化间平均空频联合协方差矩阵，h+为正极化方向(也称第一极化方向)对应的信道列向量，h-为负极化方向(也称第二极化方向)对应的信道列向量。为h+的共轭转置，为h-的共轭转置。
步骤3.2-3，第一设备根据信道矩阵对应的实际空频联合协方差矩阵确定第一指示信息。
示例性地，第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间满足预设的第一优化模型。关于第一优化模型的实现原理可以参考下述公式(13)和公式(14)的相关介绍，此处不再赘述。
在此情况下，上述公式(1)中的信道矩阵对应的实际协方差矩阵R对应为实际空频联合协方差矩阵Rh。
进一步地，叠加系数可以是用于指示角度时延功率谱的特征，如幅度和/或相位的第一叠加系数，第一叠加系数可以是通过对角度时延功率谱采样得到，或者通过对角度时延功率谱的采样结果进行量化得到。码本向量可以是根据多径对应的导向矢量和相位变化向量确定的向量。以下以双极化天线阵列为例，进一步说明步骤3.2-3。在双极化天线面板中，正极化方向的天线对应的信道列向量满足如下公式(8)所示的关系：
其中，为正极化方向信道对应的角度时延径上的叠加系数，为多径中第l0条径的俯仰角，为多径中第l0条径的水平角，为多径角度对应的导向矢量，为多径中第l0条径的时延，为时延对应的相位变化向量，为的共轭。
可理解，上述径的俯仰角可以指径与第一平面之间的夹角，第一平面为与天线面板(antenna panel)所在平面垂直的平面，上述径的水平角可以指径与第二平面之间的夹角，其中，第二平面为与天线面板所在平面以及第一平面均垂直的平面。以下结合三维坐标轴举例说明，如图4所示，x轴、y轴和z轴两两之间相互垂直，均匀面阵中天线面板所在平面与y轴、z轴所形成的平面平行，则径的俯仰角为径与x轴、 z轴所在平面之间的夹角，径的水平角为径在xOy平面上的投影与x轴之间的夹角。
负极化方向的天线对应的信道列向量满足如下公式(9)所示的关系：
其中，为负极化方向信道对应的角度时延径上的叠加系数。
若多径间随机相位相互独立，且天线阵列为双极化均匀面阵，则信道矩阵对应的实际空频联合协方差矩阵还可以满足如下公式(10)和公式(11)所示的关系：

其中，为的共轭转置，为的转置。
在此情况下，码本向量可以满足如下公式(12)所示的关系：
也就是说，第l0个码本向量根据第l0条径的多径角度对应的导向矢量和第l0条径的时延对应的相位变化向量确定。此时，公式(1)中的l对应为l0。
第一优化模型可以包括如下公式(13)和公式(14)。换言之，第一优化模型可以根据如下公式(13)和公式(14)确定：

其中，为第l0个第一叠加系数(即第l0条径对应的第一叠加系数)。0≤l0<L0，且l0为整数，L0为信道多径数目，为L0的最大取值，L0、均为大于0的整数。
如此，在第一设备通过测量参考信号确定了信道矩阵，并获得了的情况下，可以通过上述第一优化模型获取相应的以及和使得第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第一优化模型的求解结果确定。
在天线阵列为双极化天线阵列的情况下，假设第一优化模型的求解结果中，多径角度为导向矢量为第一导向矢量时延为时延对应的相位变化向量为第一相位变化向量表征和对应的角度时延功率谱的特征的第一叠加系数为第一空频联合叠加系数(即前述叠加系数)，则第一指示信息指示的码本向量为第一指示信息指示的叠加系数为第二空频联合叠加系数第二空频联合叠加系数为第一空频联合叠加系数量化后的系数，第二空频联合叠加系数也可以用于表征和对应的角度时延功率谱的特征。需要说明，可以是未经过量化或经过量化的多径角度，可以是未经过量化或经过量化的时延。
示例性地，第一指示信息用于指示上述第一导向矢量上述第一相位变化向量和上述第二空频联合叠加系数此时，第一指示信息指示的码本向量对应第一导向矢量和第一相位变化向量叠加系数(即叠加系数)对应第二空频联合叠加系数或者，第一指示信息用于指示上述多径角度上述时延和上述第二空频联合叠加系数此时，第一指示信息指示的码本向量对应多径角度和时延叠加系数(即叠加系数)对应第二空频联合叠加系数
需要说明，上述导向矢量和相位变化向量根据天线形态信息确定。在此情况下，图3所示的信道状态信息的上报方法还包括：如下步骤3.3至步骤3.5。
步骤3.3，第二设备发送用于指示天线阵列形态的信息，第一设备接收该信息。其中，该信息包括：水平阵子间距，垂直阵子间距，单极化水平阵子数目，单极化垂直阵子数目。
步骤3.4，第一设备根据天线阵列形态的指示信息，确定导向矢量
其中，当双极化天线为如图4所示的均匀面阵时，多径角度对应的导向矢量满足 如下公式(15)至公式(17)所示的关系：


其中，为垂直导向矢量，为水平导向矢量。Dh为水平阵子间距，Dv为垂直阵子间距，Mh为单极化水平阵子数目，Mv为单极化垂直阵子数目，总的阵子数目为M＝2MhMv。
步骤3.5，第一设备根据天线阵列形态的指示信息，确定相位变化向量
示例性地，相位变化向量满足如下公式(18)所示的关系：
其中，f0为第0个频率单元的频率，fN-1为第N-1个频率单元的频率，N为频率单元数目。
本申请实施例中，步骤3.1至步骤3.5的出现顺序并不具体限定。例如，步骤3.5可以在步骤3.4之前执行；步骤3.3至步骤3.5中的一项或多项，也可以在步骤3.2-3之前执行。
S303，第一设备发送第一指示信息。相应地，第二设备接收第一指示信息。
其中，第一指示信息可以承载于PUCCH或PUSCH中。
可选地，第一设备按照第一周期发送第一指示信息，第二设备按照第一周期接收第一指示信息。
S304，第二设备根据第一指示信息确定信道矩阵对应的第一空频联合协方差矩阵。
换言之，第一空频联合协方差矩阵为根据第一指示信息确定构建的信道矩阵所对应的空频联合协方矩阵。
以第一指示信息指示叠加系数和码本向量为例，则第一空频联合协方差矩阵可以满足如下公式(19)所示的关系：
其中，为第一空频联合协方差矩阵，为叠加系数，为码本向量，为的共轭转置。
示例性地，在天线阵列为双极化天线阵列，第一指示信息用于指示第一导向矢量第一相位变化向量和第二空频联合叠加系数即第一指示信息指示的码本向量对应第一导向矢量和第一相位变化向量叠加系数对应第二空频联合叠加系数的情况下，第一空频联合协方差矩阵可以满足如下公式(20)所示的关系：
其中，为的共轭转置，为的共轭，为的转置。
或者，在天线阵列为双极化天线阵列，第一指示信息用于指示多径角度时延和即第一指示信息指示的码本向量对应多径角度和时延叠加系数对应第二空频联合叠加系数的情况下，第二设备可以先根据公式(15)至公式(17)确定多径角度对应的导向矢量以及根据公式(18)确定相位变化向量然后，再根据公式(20)确定第一空频联合协方差矩阵。
基于上述图3所示的方法，通过第一设备确定用于构建第一空频联合协方差矩阵的第一指示信息，并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如空频联合特征基底对应的叠加系数。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一空频联合协方差矩阵，并根据信道矩阵对应的第一空频联合协方差矩阵确定特征基底，减少反馈的数据量，从而能够降低反馈开销，提高CSI的反馈效率。
需要说明的是，本申请实施例中，第一设备可以将部分叠加系数，如上述第一指示信息所指示的叠加系数按照长周期(即第一周期)上报给第二设备，将部分叠加系数，如下述的第一反馈系数按照短周期(即第二周期)上报给第二设备。第二设备则可以根据第一指示信息和第一反馈系数，确定完整的信道状态信息。
应理解，第一周期的时长大于第二周期的时长，例如第一周期的时长为第二周期的时长的多个整数 倍。需要说明的是，短周期上报是基于一次参考信号测量的上报，长周期上报是基于多次参考信号测量的上报，具体基于几次本申请在此不具体限定。
进一步地，为了第二设备能够确定出完整的信道状态信息，可选地，图3所提供的信道状态信息的上报方法还可以包括步骤3.6：
步骤3.6，第一设备发送第二指示信息。相应地，第二设备接收第二指示信息。
其中，第二指示信息用于指示第一反馈系数。
进一步地，第一反馈系数根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
示例性地，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，如从大到小的顺序或从小到大的顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
以下以举例说明第一设备获取第一反馈系数的原理。
假设第一指示信息指示第一导向矢量第一相位变化向量和第二空频联合叠加系数即第一指示信息指示的码本向量对应第一导向矢量和第一相位变化向量叠加系数对应第二空频联合叠加系数或者，第一指示信息指示多径角度时延和第二空频联合叠加系数即第一指示信息指示的码本向量对应多径角度和时延叠加系数对应第二空频联合叠加系数第一设备确定的信道矩阵为H。在此情况下，图3所提供的信道状态信息的上报方法还可以包括：步骤3.6-1至步骤3.6-5。
步骤3.6-1，第一设备根据第一指示信息确定第一空频联合协方差矩阵。其中，第一空频联合协方差矩阵与第一指示信息满足上述公式(19)或公式(20)所示的关系。
步骤3.6-2，第一设备对第一空频联合协方差矩阵进行分解，如奇异值分解(singular value decomposition，SVD)分解或特征值分解(eigen value decomposition，EVD)，从而得到空频联合特征基底。其中，第一空频联合协方差矩阵满足如下公式(21)所示的关系：
其中，U为第一空频联合协方差矩阵的空频联合特征基底，Λ为第一空频联合协方差矩阵进行SVD分解后的对角矩阵，UH为U的共轭转置。
为了兼顾上报开销和恢复的信道状态信息的精度，本申请实施例中，可以从空联合特征基底中选择能量较大的特征向量(列向量)构成有效空频联合特征基底。例如，在特征基底中特征向量按照能量从大到小排列的情况下，选择特征向量的列数可以根据特征向量的能量大小确定，优先选择列数靠前的特征向量，具体可以参考如下述步骤3.6-3所示。
步骤3.6-3，第一设备将空频联合特征基底U的前P列构成的矩阵确定为有效空频联合特征基底
换言之，有效空频联合特征基底包括空频联合特征基底的前P列。其中，P为正整数。
步骤3.6-4，第一设备根据有效空频联合特征基底确定空频联合短周期反馈系数，其中，空频联合短周期反馈系数为信道在空频联合域上的投影系数。其中，空频联合短周期反馈系数满足如下公式(22)所示的关系：
其中，C21为空频联合短周期反馈系数，I2为根据阵列天线的极化数量确定的单位矩阵，在阵列天线为双极化的阵列天线的情况下，
步骤3.6-5，第一设备对空频联合短周期反馈系数的部分元素或所有元素进行量化，得到第一反馈系数
如此，可以降低第一反馈系数的数据量，从而进一步降低空口开销，提高反馈效率。
更进一步地，第一指示信息还可以指示：第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
其中，第一量化向量由第一设备量化有效空频联合特征基底的第一行得到。
由于信道状态信息与空频联合特征基底相关，为了第二设备确定的空频联合特征基底与用于确定第一反馈系数的空频联合特征基底保持一致，从而提高信道状态信息的精度。进一步地，图3所提供的 方法还可以包括：
第二设备根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底。
关于第二设备确定有效空频联合特征基底的原理，可以参考步骤3.6-1至步骤3.6-3，此处不再赘述。
由于第一空频联合协方差矩阵可能存在重根，也就是说，第一空频联合协方差矩阵的分解结果不唯一，在此情况下，为了进一步确定的空频联合特征基底与用于确定第一反馈系数的空频联合特征基底保持一致，从而提高信道状态信息的精度，更进一步地，第一指示信息还用于指示：第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
如此，空频联合特征基底可以与第一反馈系数，即短周期系数结合以使第二设备能恢复完整的信道状态信息。
在此情况下，第二设备根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底，可以包括：第二设备根据第一分解规则和第一量化向量，确定第一空频联合协方差矩阵的有效空频联合特征基底。
第二设备根据有效空频联合特征基底和第一反馈系数确定信道状态信息，如信道矩阵对应的信道列向量。
示例性地，在UE为单天线的情况下，第二设备确定的信道矩阵对应的信道列向量可以满足如下公式(23)所示的关系：
其中，h′为第二设备确定的信道列向量，或者，也可以称为第二设备确定的信道状态信息。
在另一种可能的实施方式中，第一设备可以在空域进行处理并上报与恢复信道状态信息相关的第一指示信息。在此情况下，第一设备可以向第二设备发送用于确定第一空域协方差矩阵的第一指示信息。如图5所示，该信道状态信息的上报方法包括：
S501，第二设备发送参考信号。相应地，第一设备接收参考信号。
关于S501的实现原理可以参考上述S201的相关介绍，此处不再赘述。
S502，第一设备根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一空域协方差矩阵。
示例性地，第一指示信息用于指示叠加系数和码本向量。其中，叠加系数包括用于指示角度功率谱的特征，如幅度和/或相位的第二叠加系数，第二叠加系数可以是通过对角度功率谱采样得到，或者通过对角度功率谱的采样结果进行量化得到。码本向量包括用于指示角度的第二信息。第二叠加系数和第二信息用于确定第一空域协方差矩阵。
第一设备根据参考信号确定第一指示信息，可以包括步骤5.1至步骤5.2：
步骤5.1，第一设备根据参考信号确定信道矩阵。
关于步骤5.1的实现原理可以参考前述步骤2.1的相关介绍，此处不再赘述。
步骤5.2，第一设备根据信道矩阵确定第一指示信息。
示例性地，第一空域协方差矩阵为信道矩阵对应的实际空域协方差矩阵的近似矩阵，两者之间满足预设的第二优化模型。
在此情况下，上述公式(1)中的信道矩阵对应的实际协方差矩阵R对应为实际空域协方差矩阵
第二信息可以通过每个多径角度(多径中每个径的角度)对应的导向矢量，或者，多径中的每个径的多径角度来指示。也就是说，第一指示信息可以指示第二叠加系数和每个多径角度对应的导向矢量。或者，第一指示信息可以指示第二叠加系数和多径中每个径的多径角度。
可选地，第二优化模型可以包括公式(24)和公式(25)。换言之，第二优化模型可以根据公式(24)和公式(25)确定：

其中，为信道矩阵对应的实际空域协方差矩阵；为第l1个第二叠加系数，为第l1个 多径角度对应的导向矢量，为的共轭转置，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。
如此，在第一设备通过测量参考信号确定了信道矩阵并获得了的情况下，可以通过上述第二优化模型获取相应的和使得第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第一优化模型的求解结果确定。
第l1个多径角度对应的导向矢量的实现原理可以参考上述步骤3.3和步骤3.4的相关介绍，此处不再赘述。
需要说明，信道矩阵对应的实际空域协方差矩阵可以根据信道矩阵确定。
例如双极化天线中，信道矩阵对应的实际空域协方差矩阵满足如下公式(26)所示的关系：
其中，为信道矩阵对应的实际空域协方差矩阵，H+为正极化天线对应的信道矩阵，(H+)H为H+的共轭转置，H-为负极化天线对应的信道矩阵，(H-)H为H-的共轭转置。在此情况下，第一指示信息可以根据预设的第二优化模型的求解结果确定。
假设第二优化模型的求解结果中，多径角度为导向矢量为第二导向矢量用于指示对应的角度功率谱的特征的第二叠加系数为第一空域叠加系数则第一指示信息指示第二导向矢量和第二空域叠加系数即第一指示信息指示的码本向量对应第二导向矢量叠加系数对应第二空域叠加系数或者，第一指示信息指示多径角度和第二空域叠加系数即第一指示信息指示的码本向量对应多径角度叠加系数对应第二空域叠加系数第二空域叠加系数为第一空域叠加系数量化后的系数。其中，码本向量对应为叠加系数对应为第二空域叠加系数此时，公式(1)中的l对应为l1。需要说明，为量化后的多径角度。
S503，第一设备发送第一指示信息。相应地，第二设备接收第一指示信息。
其中，第一指示信息可以承载于PUCCH或PUSCH中。
S504，第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵。
第一指示信息指示第二导向矢量和第二空域叠加系数即第一指示信息指示的叠加系数对应第二空域叠加系数码本向量对应第二导向矢量或者，第一指示信息指示多径角度和第二空域叠加系数即第一指示信息指示的叠加系数对应码本向量对应多径角度在此情况下，第一空频协方差矩阵满足如下公式(27)关系：
其中，为第一空域协方差矩阵，为的共轭转置。
基于上述图5所示的方法，通过第一设备反馈用于构建第一空域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量的系数，如空域特征基底对应的叠加系数。例如，可以由第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵，并根据信道矩阵对应的第一空域协方差矩阵确定空域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
需要说明，空域特征基底可以与短周期反馈系数、频域特征基底结合，以使第二设备能恢复完整的信道状态信息。
在又一种可能的实施方式中，第一设备可以在频域进行处理并上报与恢复信道状态信息相关的第一指示信息。在此情况下，第一设备可以向第二设备发送用于确定频域协方差矩阵的第一指示信息。如图6所示，该信道状态信息的上报方法包括：
S601，第二设备向第一设备发送参考信号。相应地，第一设备接收来自第二设备的参考信号。
关于S601的实现原理可以参考上述S201的相关介绍，此处不再赘述。
S602，第一设备根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一频域协方差矩阵。
示例性地，第一指示信息用于指示叠加系数和码本向量。其中，叠加系数包括用于指示时延功率谱 的特征，如幅度和/或相位的第三叠加系数，第三叠加系数可以是通过对时延功率谱采样得到，或者通过对时延功率谱的采样结果进行量化得到。码本向量包括用于指示时延的第三信息。其中，第三叠加系数和第三信息用于确定第一频域协方差矩阵。
第一设备根据参考信号确定第一指示信息，可以包括步骤6.1至步骤6.2：
步骤6.1，第一设备根据参考信号确定信道矩阵。
关于步骤6.1的实现原理可以参考前述步骤2.1的相关介绍，此处不再赘述。
步骤6.2，第一设备根据信道矩阵确定第一指示信息。
示例性地，第一频域协方差矩阵为信道矩阵对应的实际频域协方差矩阵的近似矩阵，两者之间满足预设的第三优化模型。
在此情况下，上述公式(1)中的信道矩阵对应的实际协方差矩阵R对应为实际空域协方差矩阵
第三信息可以通过每个径的时延对应的相位变化向量，或者，每个径的时延来指示。也就是说，第一指示信息可以指示第三叠加系数和每个径对应的相位变化向量。或者，第一指示信息可以指示第三叠加系数和每个径的时延。
可选地，第三优化模型可以包括公式(28)和公式(29)。换言之，第三优化模型可以根据公式(28)和公式(29)确定：

其中，为信道矩阵对应的实际频域协方差矩阵；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
如此，在第一设备通过测量参考信号确定了信道矩阵并获得了的情况下，可以通过上述第二优化模型使得第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间的误差尽量小。也就是说，第一指示信息可以通过预设的第三优化模型的求解结果确定。
可理解，第l2个相位变化向量的实现原理可以参考上述图3所示步骤3.3和步骤3.5中的相关介绍，此处不再赘述。
此外，上述信道矩阵对应的实际频域协方差矩阵可以根据信道矩阵确定。
例如，在双极化天线中，信道矩阵对应的实际频域协方差矩阵满足如下公式(30)所示的关系：
其中，为信道矩阵对应的实际频域协方差矩阵，H为信道矩阵。
假设第三优化模型的求解结果中，时延为时延对应的相位变化向量为第二相位变化向量表征对应的时延功率谱的特征的系数为第一频域叠加系数第一指示信息用于指示第二相位变化向量第二频域叠加系数即第一指示信息指示的码本向量对应第二相位变化向量叠加系数对应第二频域叠加系数或者，第一指示信息用于指示时延和第二时延功率谱即第一指示信息指示的码本向量对应时延叠加系数对应第二频域叠加系数其中，第二频域叠加系数为第一频域叠加系数量化后的系数。此时，码本向量对应为叠加系数对应为第二频域叠加系数公式(1)中的l对应为l2。需要说明，为量化后的时延。
S603，第一设备发送第一指示信息。相应地，第二设备接收第一指示信息。
其中，第一指示信息可以承载于PUCCH或PUSCH中。
S604，第二设备根据第一指示信息确定信道矩阵对应的第一频域协方差矩阵。
其中，第一频域协方差矩阵满足如下公式(31)所示的关系：
其中，为第一频域协方差矩阵。为的共轭，为的转置。
基于上述图6所示的方法，通过第一设备反馈用于构建第一频域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如频域特征基底对应的叠加系数。 例如，可以由第二设备根据第一指示信息确定第一频域协方差矩阵，并根据信道矩阵对应的第一频域协方差矩阵确定频域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
需要说明外，频域特征基底可以与空域特征基底、短周期反馈系数结合以使第二设备能恢复完整的信道状态信息。
在再一种可能的实施方式中，第一设备可以在空域和频域进行处理并上报与恢复信道状态信息相关的第一指示信息。在此情况下，第一设备可以向第二设备发送用于确定频域协方差矩阵和空域协方差矩阵的第一指示信息。如图7所示，该信道状态信息的上报方法包括：
S701，第二设备发送参考信号。相应地，第一设备接收参考信号。
关于S701的实现原理可以参考上述S201的相关介绍，此处不再赘述。
S702，第一设备根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一空域协方差矩阵，以及构建信道矩阵对应的第一频域协方差矩阵。
示例性地，第一指示信息可以指示叠加系数和码本向量。其中，叠加系数可以包括用于指示角度功率谱的特征，如幅度和/或相位第二叠加系数和用于指示时延功率谱的特征，如幅度和/或相位的第三叠加系数。第二叠加系数可以是通过对角度功率谱采样得到，或者通过对角度功率谱的采样结果进行量化得到，第三叠加系数可以是通过对时延功率谱采样得到，或者通过对时延功率谱的采样结果进行量化得到。码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息。第二叠加系数和第二信息用于确定第一空域协方差矩阵，第三叠加系数和第三信息用于确定第一频域协方差矩阵。第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足预设的第二优化模型，第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足预设的第三优化模型。
在此情况下，上述公式(1)中的信道矩阵对应的协方差矩阵R包括信道矩阵对应的实际空域协方差矩阵和信道矩阵对应的实际频域协方差矩阵
如此，可以反馈空域协方差矩阵和频域协方差矩阵。
关于第二叠加系数、第二信息、第一空域协方差矩阵和第二优化模型可以参考S502中的相关介绍，关于第三叠加系数、第三信息、第一频域协方差矩阵和第三优化模型的具体实现可以参考S602中的相关介绍，此处不再赘述。
第一设备根据参考信号确定第一指示信息，可以包括步骤7.1和步骤7.2。
步骤7.1，第一设备根据参考信号确定信道矩阵。
关于步骤7.1的实现原理可以参考前述步骤2.1的相关介绍，此处不再赘述。
步骤7.2，第一设备根据信道矩阵确定第一指示信息。关于步骤7.2的实现原理，可以参考前述步骤5.2和前述步骤6.2的相关介绍，此处不再赘述。
S703，第一设备发送第一指示信息。相应地，第二设备接收第一指示信息。
其中，第一指示信息可以承载于PUCCH或PUSCH中。
示例性地，第一设备按照第三周期发送第一指示信息。相应地，第二设备按照第三周期接收第一指示信息。
关于S703的实现原理，可以参考S503或S603的相关介绍，此处不再赘述。
S704，第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵和第一频域协方差矩阵。
其中，S704可以包括步骤7.3和步骤7.4。
步骤7.3，第二设备根据第一指示信息确定信道矩阵对应的第一空域协方差矩阵。
关于步骤7.3的实现原理，可以参考S504的相关介绍，此处不再赘述。
步骤7.4，第二设备根据第一指示信息确定信道矩阵对应的第一频域协方差矩阵。
关于步骤7.4的实现原理，可以参考S604的相关介绍，此处不再赘述。
基于上述图7所示的方法，通过第一设备反馈用于构建第一空域协方差矩阵和第一频域协方差矩阵的第一指示信息并发送给第二设备，可以避免上报直接用于恢复信道状态信息的大量信息，如空域特征基底对应的叠加系数和频域特征基底对应的叠加系数。基于来自第一设备的第一指示信息确定第一空域协方差矩阵和第一频域协方差矩阵，例如，可以由第二设备根据第一指示信息确定信道矩阵对应的 第一空域协方差矩阵和第一频域协方差矩阵，并根据信道矩阵对应的第一空域协方差矩阵确定空域特征基底，根据信道矩阵对应的第一频域协方差矩阵确定频域特征基底，减少反馈的数据量，从而能够降低反馈开销，提高反馈效率。
需要说明，本申请实施例中，第一设备可以将部分叠加系数，如上述第一指示信息所指示的叠加系数以长周期(即第三周期)上报给第二设备；将部分叠加系数，如下述的第二反馈系数按照短周期(即第四周期)上报给第二设备。第二设备则可以根据第一指示信息和第二反馈系数，确定信道状态信息。
关于第三周期和第四周期的相关介绍可以参考上述图3所示方法实施例中关于第一周期和第二周期的相关介绍，此处不再赘述。
进一步地，为了第二设备能够确定信道状态信息，可选地，图7所提供的信道状态信息的上报方法还可以包括：第一设备按照第四周期发送第三指示信息。相应地，第二设备按照第四周期接收第三指示信息。
其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
进一步地，第二反馈系数根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。
示例性地，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中元素的排列顺序，如从小到大或从大到小的顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素均的类型，如正实数。
示例性地，第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中元素的排列顺序，如从小到大或从大到小的顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型，如正实数。
第一设备确定第二反馈系数的过程包括如下步骤7.5至步骤7.8。
步骤7.5，第一设备根据第三指示信息确定第一空域协方差矩阵以及第一频域协方差矩阵。
关于第一设备根据第三指示信息确定第一空域协方差矩阵的实现原理可以参上述S504，关于根据第三指示信息确定第一频域协方差矩阵的实现原理可以参考上述S604。
步骤7.6，第一设备根据第二分解规则对第一空域协方差矩阵进行SVD分解，得到空域特征基底。第一设备根据第三分解规则对第一频域协方差矩阵进行SVD分解，得到频域特征基底。
其中，第一空域协方差矩阵满足如下公式(32)所示的关系：
第一频域协方差矩阵满足如下公式(33)所示的关系：
其中，US为空域特征基底，ΛS为第一空域协方差矩阵的对角矩阵，为US的共轭转置矩阵，UF为频域特征基底，ΛF为第一频域协方差矩阵的对角矩阵，为UF的共轭转置矩阵。
为了兼顾上报开销和恢复的信道状态信息的精度，本申请实施例中，可以从空域特征基底中选择能量较大的特征向量(列向量)构成有效空域特征基底，从频域特征基底中选择能量较大的特征向量(列向量)构成有效频域特征基底，具体可以对应参考如下述步骤7.7所示。
步骤7.7，对于空域特征基底US，取空域特征基底US的前D列，便得到有效空域特征基底对于频域特征基底UF，取频域特征基底UF的前D列，便得到有效频域特征基底
步骤7.8，根据有效空域特征基底和有效频域特征基底确定空域和频域结合的反馈系数C22，并对空域和频域结合的短周期反馈系数进行量化(如用二进制数表示)得到第二反馈系数
其中，空域和频域结合的反馈系数C22为空域特征基底中每个特征向量和频域特征基底中中每个特征向量构成的一组空频向量对应的叠加系数所构成的系数矩阵，或者空域特征基底中每个特征向量和频域特征基底中每个特征向量对应的叠加系数所构成的系数矩阵。
空域和频域结合的短周期反馈系数满足如下公式(34)所示的关系：
更进一步地，第一指示信息还可以用于指示：第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量。其中，K为正整数。
在此情况下，图7所示的方法还可以包括：接收设备将空域特征基底US前K列的第一行元素量化后的向量确定为第二量化向量
更进一步地，第一指示信息还可以用于指示：第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量。其中，D为正整数。
在此情况下，图7所示的方法还可以包括：接收设备将频域特征基底UF前D列的第一行元素量化后的向量确定为第三量化向量
由于信道状态信息与空域特征基底和频域特征基底相关，为了使第二设备确定的空域特征基底与用于确定第二反馈系数的空域特征基底保持一致，提高信道状态信息的精度，进一步地，图7所提供的方法还可以包括步骤7.9：
步骤7.9，第二设备根据第二分解规则，确定有效空域特征基底。
更进一步地，第二设备根据第二分解规则，确定有效空域特征基底，包括：第二设备根据第二分解规则和第二量化向量，确定有效空域特征基底。其中，有效空域特征基底包括第一空域协方差矩阵的空域特征基底的前K列。此外，为了使第二设备确定的频域特征基底与用于确定第二反馈系数的频域特征基底保持一致，提高信道状态信息的精度，进一步地，图7所提供的方法还可以包括步骤7.10：
步骤7.10，第二设备根据第三分解规则，确定有效频域特征基底。第二设备根据有效空域特征基底、有效频域特征基底和第二反馈系数确定信道状态信息。
其中，信道状态信息可以通过第二设备估计的信道矩阵的形式表示。例如，在双极化天线阵列中，第二设备估计的信道矩阵满足如下公式(35)所示的关系：
其中，H′为第二设备确定的信道矩阵，或者，也可以称为第二设备确定的信道状态信息。
更进一步地，图7所提供的方法还可以包括：第二设备根据第三分解规则和第三量化向量，确定有效频域特征基底。其中，有效频域特征基底包括第一频域协方差矩阵的频域特征基底的前D列。如此，第二设备可以将空域特征基底、频域特征基底以及与第二反馈系数，即短周期反馈系数结合，从而恢复完整的信道状态信息。
对于反馈长周期系数量化而言，一次长周期反馈，在反馈空域特征基底和频域特征基底的方案中需要反馈和共计(B×K+D×T)个复系数，其中，B为第二设备或第一设备选择空域基底数目，T为第二设备或第一设备选取频域基底数目，K表示下行空域特征空间的有效维度、D表示下行频域特征空间的有效维度。而改进方案仅需要反馈个正实数。例如，B＝64，K＝4，D＝8，T＝48，反馈空域特征基底和频域特征基底的方案基线需要量化反馈640个复系数，本实施例需要量化反馈64个数据，如正实数，大幅度降低了反馈开销。换句话说，在相同的开销下，可以将开销用来增加K和D的值，以提升CSI量化精度，从而提升系统性能。
需要说明的是，上述图3、图5或图6中的导向矢量、相位变化向量均可以是过采样的离散傅里叶变换(discrete fourier transform，DFT)码本。
本申请中涉及的“量化”，可以是指将信号的连续取值(或者大量可能的离散取值)近似为有限多个(或较少的)离散值的过程，如均匀量化，还可以是将复数表示的数据转换为二进制表示的数据，此处不再赘述。
以上结合图3至图7详细说明了本申请实施例提供的信道状态信息的上报方法。以下结合图8至图9详细说明用于执行本申请实施例提供的信道状态信息的上报方法的通信装置。
示例性地，图8是本申请实施例提供的通信装置的结构示意图一。如图8所示，通信装置800包括：处理模块801和收发模块802。为了便于说明，图8仅示出了该通信装置的主要部件。
一些实施例中，通信装置800可适用于图1中所示出的通信系统中，执行图2、图3、或图5、或图6、或图7中所示出的信道状态信息的上报方法中第一设备的功能。
其中，收发模块，用于接收来自第二设备的参考信号。
处理模块801，用于根据参考信号确定第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵，信道矩阵用于指示通信装置与第二设备之间的信道的信道状态信息。
收发模块802，用于发送第一指示信息。
一种可能的设计方案中，第一指示信息可以用于指示叠加系数和码本向量，叠加系数和码本向量用于确定第一空频联合协方差矩阵。
一种可能的设计方案中，第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间满足第一优化模型。
可选地，第一优化模型可以包括：

s.t.L≤Lmax；
其中，min表示取最小值，“║║F”表示取F范数，R为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l<L，且l为整数；αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。
可选地，叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量包括用于指示角度时延的第一信息，第一叠加系数和第一指示信息用于确定第一空频联合协方差矩阵，预设的优化模型包括：第一空频联合协方差矩阵与信道矩阵对应的实际空频联合协方差矩阵之间满足的第一优化模型。
进一步地，第一优化模型包括：

其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l0<L0，且l0为整数；为第l0个第一叠加系数，为第l0个多径角度对应的导向矢量，为的共轭转置，为第l0个相位变化向量，为的共轭，为的转置，为第l0个第一信息，s.t.为约束条件，L0为信道多径数目，LFS max为L0的最大取值，L0、LFS max均为大于0的整数。
一种可能的设计方案中，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量可以包括用于指示角度的第二信息。其中，第二叠加系数和第二信息用于确定第一空域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型。
可选地，第二优化模型可以包括：

其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算；为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。
一种可能的设计方案中，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示时延的第三信息，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
可选地，第三优化模型可以包括：

其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
一种可能的设计方案中，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指 示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息，第二叠加系数和第二信息用于确定第一空域协方差矩阵，第三叠加系数和第三信息用于确定第一频域协方差矩阵。预设的优化模型包括：第一空域协方差矩阵与信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型，以及第一频域协方差矩阵与信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
可选地，第二优化模型可以包括：

其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算。为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。第三优化模型可以包括：

其中，min表示取最小值，“‖‖F”表示取F范数，为信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算。为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
需要说明，收发模块，具体用于按照第一周期向第二设备发送第一指示信息。可选地，收发模块802，还可以用于按照第二周期向第二设备发送第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
进一步地，第一反馈系数根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
示例性地，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
需要说明，收发模块，具体用于按照第三周期向第二设备发送第一指示信息。
可选地，收发模块802，还可以用于按照第四周期向第二设备发送第三指示信息；其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
进一步地，第二反馈系数根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定。其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。
示例性地，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中元素的排列顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素的类型，如正实数。第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中元素的排列顺序，以及第一频域协方差矩阵的空域特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量。其中，K为正整数。更进一步地，第一指示信息还可以用于指示：第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量。其中，D为正整数。
可选地，收发模块802可以包括接收模块和发送模块。其中，收发模块802用于实现通信装置800的发送功能和接收功能。
可选地，通信装置800还可以包括存储模块(图8中未示出)，该存储模块存储有程序或指 令。当处理模块801执行该程序或指令时，使得通信装置800可以执行图2、图3、或图5、或图6、或图7所示的信道状态信息的上报方法中第一设备的功能。
应理解，通信装置800中涉及的处理模块801可以由处理器或处理器相关电路组件实现，可以为处理器或处理单元；收发模块802可以由收发器或收发器相关电路组件实现，可以为收发器或收发单元。
需要说明的是，通信装置800可以是图1中所示出的第一设备或第二设备，也可以是设置于上述第一设备或第二设备中的芯片(系统)或其他部件或组件，或者包含该第一设备或第二设备的装置，本申请实施例对此不做限定。
此外，通信装置800的技术效果，可以分别参考图2、图3、或图5、或图6、或图7中任一项所示出的信道状态信息的上报方法的技术效果，此处不再赘述。
另一些实施例中，通信装置800可适用于图1中所示出的通信系统中，执行图2、图3、或图5、或图6、或图7中所示出的信道状态信息的上报方法中第二设备的功能。
其中，收发模块802，用于接收来自第一设备的第一指示信息。
其中，第一指示信息用于构建信道矩阵对应的第一协方差矩阵，信道矩阵用于指示第一设备与第二设备之间的信道的信道状态信息。
处理模块801，用于根据第一指示信息确定信道矩阵对应的第一协方差矩阵。
一种可能的设计方案中，第一指示信息可以包括叠加系数和码本向量。处理模块，具体用于根据叠加系数和码本向量确定第一协方差矩阵。
可选地，叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，码本向量包括用于指示角度时延的第一信息。处理模块，具体用于根据第一叠加系数和第一信息确定第一空频联合协方差矩阵。
需要说明，收发模块，具体用于按照第一周期接收来自第一设备的第一指示信息。
可选地，收发模块802，还可以用于按照第二周期接收来自第一设备的第二指示信息。其中，第二指示信息用于指示第一反馈系数，第二周期小于第一周期。
示例性地，第一反馈系数是根据第一空频联合协方差矩阵的第一分解结果和信道矩阵确定的。其中，第一分解结果由第一空频联合协方差矩阵按照第一分解规则分解得到。
进一步地，处理模块801，还可以用于根据第一分解规则，确定第一空频联合协方差矩阵的有效空频联合特征基底。其中，有效空频联合特征基底包括空频联合特征基底的前P列，P为正整数。以及，根据有效空频联合特征基底和第一反馈系数确定信道矩阵。
示例性地，第一分解规则可以包括：第一空频联合协方差矩阵分解的对角矩阵中的元素的排列顺序，以及第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型，如正实数。
更进一步地，第一指示信息还可以用于指示：第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量。其中，P为正整数。
在此情况下，处理模块801，具体用于根据第一分解规则和第一量化向量，确定第一空频联合协方差矩阵的有效空频联合特征基底。
一种可能的设计方案中，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数，码本向量可以包括用于指示角度的第二信息。处理模块801，具体用于根据第二叠加系数和第二信息确定第一空域协方差矩阵。
一种可能的设计方案中，叠加系数可以包括用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示时延的第三信息。处理模块801，具体用于根据第三叠加系数和第三信息确定第一频域协方差矩阵。
一种可能的设计方案中，叠加系数可以包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，码本向量可以包括用于指示角度的第二信息和用于指示时延的第三信息。处理模块801，具体用于根据第二叠加系数和第二信息确定第一空域协方差矩阵。以及，根据第三叠加系数和第三信息确定第一频域协方差矩阵。
需要说明，收发模块，具体用于按照第一周期接收来自第一设备的第一指示信息。
可选地，收发模块802，还可以用于按照第四周期接收来自第一设备的第三指示信息；其中，第三指示信息用于指示第二反馈系数，第四周期小于第三周期。
示例性地，第二反馈系数是根据第一空域协方差矩阵的第二分解结果、第一频域协方差矩阵的第三分解结果和信道矩阵确定的；其中，第二分解结果由第一空域协方差矩阵按照第二分解规则分解得到，第三分解结果由第一频域协方差矩阵按照第三分解规则分解得到。例如，第二分解规则可以包括：第一空域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一空域协方差矩阵的空域特征基底的第一行元素的类型。第三分解规则可以包括：第一频域协方差矩阵的对角矩阵中的元素的排列顺序，以及第一频域协方差矩阵的频域特征基底的第一行元素的类型，如正实数。
进一步地，处理模块801，还可以用于根据第二分解规则，确定有效空域特征基底。根据第三分解规则，确定有效频域特征基底。以及，根据有效空域特征基底、有效频域特征基底和第二反馈系数确定信道状态信息。进一步地，第一指示信息还可以用于指示：第一空域协方差矩阵分解后的空域特征基底中前K列的第一行元素量化后的第二量化向量。
更进一步地，处理模块801，具体用于根据第二分解规则和第二量化向量，确定有效空域特征基底。其中，有效空域特征基底包括第一空域协方差矩阵的空域特征基底的前K列。
进一步地，第一指示信息还可以用于指示：第一频域协方差矩阵分解后的频域特征基底中前D列的第一行元素量化后的第三量化向量。
更进一步地，处理模块801，具体用于根据第三分解规则和第三量化向量，确定有效频域特征基底；其中，有效频域特征基底包括第一频域协方差矩阵的频域特征基底的前D列。
可选地，收发模块802可以包括接收模块和发送模块。其中，收发模块802用于实现通信装置800的发送功能和接收功能。
应理解，通信装置800中涉及的处理模块801可以由处理器或处理器相关电路组件实现，可以为处理器或处理单元。收发模块802可以由收发器或收发器相关电路组件实现，可以为收发器或收发单元。
需要说明的是，通信装置800可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备中的芯片(系统)或其他部件或组件，还可以是包含第一设备或第二设备的装置，本申请对此不做限定。
此外，通信装置800的技术效果可以参考第图2、图3、或图5至图7中任一项所示出的信道状态信息的上报方法的技术效果，此处不再赘述。
示例性地，图9为本申请实施例提供的通信装置的结构示意图二。该通信装置可以是第一设备或第二设备，也可以是可设置于第一设备或第二设备的芯片(系统)或其他部件或组件。如图9所示，通信装置900可以包括处理器901。
可选地，通信装置900还可以包括存储器902和/或收发器903。其中，处理器901与存储器902和收发器903耦合，如可以通过通信总线连接。
下面结合图9对通信装置900的各个构成部件进行具体的介绍：
其中，处理器901是通信装置900的控制中心，可以是一个处理器，也可以是多个处理元件的统称。例如，处理器901是一个或多个中央处理器(central processing unit，CPU)，也可以是特定集成电路(application specific integrated circuit，ASIC)，或者是被配置成实施本申请实施例的一个或多个集成电路，例如：一个或多个数字信号处理器(digital signal processor，DSP)，或，一个或者多个现场可编程门阵列(field programmable gate array，FPGA)。
可选地，处理器901可以通过运行或执行存储在存储器902内的软件程序，以及调用存储在存储器902内的数据，执行通信装置900的各种功能。
在具体的实现中，作为一种实施例，处理器901可以包括一个或多个CPU，例如图9中所示出的CPU0和CPU1。
在具体实现中，作为一种实施例，通信装置900也可以包括多个处理器，例如图9中所示的处理器901和处理器904。这些处理器中的每一个可以是一个单核处理器(single-CPU)，也可以是一个多核处理器(multi-CPU)。这里的处理器可以指一个或多个设备、电路、和/或用于处理数据(例如计算机程序指令)的处理核。
其中，所述存储器902用于存储执行本申请方案的软件程序，并由处理器901来控制执行，具体实现方式可以参考上述方法实施例，此处不再赘述。
可选地，存储器902可以是只读存储器(read-only memory，ROM)或可存储静态信息和指令的其他类型的静态存储设备，随机存取存储器(random access memory，RAM)或者可存储信息和指令的其 他类型的动态存储设备，也可以是电可擦可编程只读存储器(electrically erasable programmable read-only memory，EEPROM)、只读光盘(compact disc read-only memory，CD-ROM)或其他光盘存储、光碟存储(包括压缩光碟、激光碟、光碟、数字通用光碟、蓝光光碟等)、磁盘存储介质或者其他磁存储设备、或者能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。存储器902可以和处理器901集成在一起，也可以独立存在，并通过通信装置900的接口电路(图9中未示出)与处理器901耦合，本申请实施例对此不作具体限定。
收发器903，用于与其他通信装置之间的通信。例如，通信装置900为第一设备，收发器903可以用于与第二设备通信，或者与另一个第一设备通信。又例如，通信装置900为第二设备，收发器903可以用于与第一设备通信，或者与另一个第二设备通信。
可选地，收发器903可以包括接收器和发送器(图9中未单独示出)。其中，接收器用于实现接收功能，发送器用于实现发送功能。
可选地，收发器903可以和处理器901集成在一起，也可以独立存在，并通过通信装置900的接口电路(图9中未示出)与处理器901耦合，本申请实施例对此不作具体限定。
需要说明的是，图9中示出的通信装置900的结构并不构成对该通信装置的限定，实际的通信装置可以包括比图示更多或更少的部件，或者组合某些部件，或者不同的部件布置。
此外，通信装置900的技术效果可以参考上述方法实施例所述的信道状态信息的上报方法的技术效果，此处不再赘述。
应理解，在本申请实施例中的处理器可以是中央处理单元(central processing unit，CPU)，该处理器还可以是其他通用处理器、数字信号处理器(digital signal processor，DSP)、专用集成电路(application specific integrated circuit，ASIC)、现成可编程门阵列(field programmable gate array，FPGA)或者其他可编程逻辑器件、分立门或者晶体管逻辑器件、分立硬件组件等。通用处理器可以是微处理器或者该处理器也可以是任何常规的处理器等。
还应理解，本申请实施例中的存储器可以是易失性存储器或非易失性存储器，或可包括易失性和非易失性存储器两者。其中，非易失性存储器可以是只读存储器(read-only memory，ROM)、可编程只读存储器(programmable ROM，PROM)、可擦除可编程只读存储器(erasable PROM，EPROM)、电可擦除可编程只读存储器(electrically EPROM，EEPROM)或闪存。易失性存储器可以是随机存取存储器(random access memory，RAM)，其用作外部高速缓存。通过示例性但不是限制性说明，许多形式的随机存取存储器(random access memory，RAM)可用，例如静态随机存取存储器(static RAM，SRAM)、动态随机存取存储器(DRAM)、同步动态随机存取存储器(synchronous DRAM，SDRAM)、双倍数据速率同步动态随机存取存储器(double data rate SDRAM，DDR SDRAM)、增强型同步动态随机存取存储器(enhanced SDRAM，ESDRAM)、同步连接动态随机存取存储器(synchlink DRAM，SLDRAM)和直接内存总线随机存取存储器(direct rambus RAM，DR RAM)。
上述实施例，可以全部或部分地通过软件、硬件(如电路)、固件或其他任意组合来实现。当使用软件实现时，上述实施例可以全部或部分地以计算机程序产品的形式实现。所述计算机程序产品包括一个或多个计算机指令或计算机程序。在计算机上加载或执行所述计算机指令或计算机程序时，全部或部分地产生按照本申请实施例所述的流程或功能。所述计算机可以为通用计算机、专用计算机、计算机网络、或者其他可编程装置。所述计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，所述计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。所述计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集合的服务器、数据中心等数据存储设备。所述可用介质可以是磁性介质(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质。半导体介质可以是固态硬盘。
应理解，本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况，其中A,B可以是单数或者复数。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系，但也可能表示的是一种“和/或”的关系，具体可参考前后文进行理解。
本申请中，“至少一个”是指一个或者多个，“多个”是指两个或两个以上。“以下至少一项(个)”或其 类似表达，是指的这些项中的任意组合，包括单项(个)或复数项(个)的任意组合。例如，a,b,或c中的至少一项(个)，可以表示：a,b,c,a-b,a-c,b-c,或a-b-c，其中a,b,c可以是单个，也可以是多个。
应理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
本领域普通技术人员可以意识到，结合本文中所公开的实施例描述的各示例的单元及算法步骤，能够以电子硬件、或者计算机软件和电子硬件的结合来实现。这些功能究竟以硬件还是软件方式来执行，取决于技术方案的特定应用和设计约束条件。专业技术人员可以对每个特定的应用来使用不同方法来实现所描述的功能，但是这种实现不应认为超出本申请的范围。
所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，上述描述的系统、装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。
在本申请所提供的几个实施例中，应该理解到，所揭露的系统、装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。
所述作为分离部件说明的单元可以是或者也可以不是物理上分开的，作为单元显示的部件可以是或者也可以不是物理单元，即可以位于一个地方，或者也可以分s布到多个网络单元上。可以根据实际的需要选择其中的部分或者全部单元来实现本实施例方案的目的。
另外，在本申请各个实施例中的各功能单元可以集成在一个处理单元中，也可以是各个单元单独物理存在，也可以两个或两个以上单元集成在一个单元中。
所述功能如果以软件功能单元的形式实现并作为独立的产品销售或使用时，可以存储在一个计算机可读取存储介质中。基于这样的理解，本申请的技术方案本质上或者说对现有技术做出贡献的部分或者该技术方案的部分可以以软件产品的形式体现出来，该计算机软件产品存储在一个存储介质中，包括若干指令用以使得一台计算机设备(可以是个人计算机，服务器，或者第二设备等)执行本申请各个实施例所述方法的全部或部分步骤。而前述的存储介质包括：U盘、移动硬盘、只读存储器(read-only memory，ROM)、随机存取存储器(random access memory，RAM)、磁碟或者光盘等各种可以存储程序代码的介质。
以上所述，仅为本申请的具体实施方式，但本申请的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本申请揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本申请的保护范围之内。因此，本申请的保护范围应以所述权利要求的保护范围为准。

Claims (99)

  1. 一种信道状态信息的上报方法，其特征在于，所述方法包括：
    第一设备接收来自第二设备的参考信号；
    第一设备根据所述参考信号确定第一指示信息；其中，所述第一指示信息用于构建信道矩阵对应的第一协方差矩阵，所述信道矩阵用于指示所述第一设备与所述第二设备之间的信道的信道状态信息；
    所述第一设备向所述第二设备发送所述第一指示信息。
  2. 根据权利要求1所述的方法，其特征在于，所述第一指示信息用于指示叠加系数和码本向量，所述叠加系数和所述码本向量用于确定所述第一协方差矩阵。
  3. 根据权利要求1或2所述的方法，其特征在于，所述第一协方差矩阵与所述信道矩阵对应的实际协方差矩阵之间满足预设的优化模型。
  4. 根据权利要求3所述的方法，其特征在于，所述预设的优化模型包括：

    s.t.L≤Lmax；
    其中，min表示取最小值，“‖‖F”表示取F范数，R为所述信道矩阵对应的实际协方差矩阵，Σ表示求和运算，0≤l<L，且l为整数；αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。
  5. 根据权利要求3所述的方法，其特征在于，所述叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，所述码本向量包括用于指示角度时延的第一信息，所述第一叠加系数和所述第一信息用于确定第一空频联合协方差矩阵；
    所述预设的优化模型包括：所述第一空频联合协方差矩阵与所述信道矩阵对应的实际空频联合协方差矩阵之间满足的第一优化模型。
  6. 根据权利要求5所述的方法，其特征在于，所述第一优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l0<L0，且l0为整数；为第l0个第一叠加系数，为第l0个多径角度对应的导向矢量，为的共轭转置，为第l0个相位变化向量，为的共轭，为的转置，为第l0个第一信息，s.t.为约束条件，L0为信道多径数目，为L0的最大取值，L0、均为大于0的整数。
  7. 根据权利要求3所述的方法，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数，所述码本向量包括用于指示角度的第二信息；其中，所述第二叠加系数和所述第二信息用于确定第一空域协方差矩阵；
    所述预设的优化模型包括：所述第一空域协方差矩阵与所述信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型。
  8. 根据权利要求7所述的方法，其特征在于，所述第二优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算；为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。
  9. 根据权利要求3所述的方法，其特征在于，所述叠加系数包括用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示时延的第三信息，所述第三叠加系数和所述第三信息用于确定第 一频域协方差矩阵；
    所述预设的优化模型包括：所述第一频域协方差矩阵与所述信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
  10. 根据权利要求9所述的方法，其特征在于，所述第三优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
  11. 根据权利要求3所述的方法，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示角度的第二信息和用于指示时延的第三信息，所述第二叠加系数和所述第二信息用于确定第一空域协方差矩阵，所述第三叠加系数和所述第三信息用于确定第一频域协方差矩阵；所述预设的优化模型包括：所述第一空域协方差矩阵与所述信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型，以及所述第一频域协方差矩阵与所述信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
  12. 根据权利要求11所述的方法，其特征在于，所述第二优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算；为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数；
    所述第三优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
  13. 根据权利要求5或6所述的方法，其特征在于，所述第一设备向所述第二设备发送所述第一指示信息，可以包括：
    所述第一设备按照第一周期向所述第二设备发送所述第一指示信息。
  14. 根据权利要求13所述的方法，其特征在于，所述方法还包括：
    所述第一设备按照第二周期向所述第二设备发送第二指示信息；其中，所述第二指示信息用于指示第一反馈系数，所述第二周期小于所述第一周期。
  15. 根据权利要求14所述的方法，其特征在于，所述第一反馈系数根据所述第一空频联合协方差矩阵的第一分解结果和所述信道矩阵确定；其中，所述第一分解结果由所述第一空频联合协方差矩阵按照第一分解规则分解得到。
  16. 根据权利要求15所述的方法，其特征在于，所述第一分解规则包括：所述第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，以及所述第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型。
  17. 根据权利要求15或16所述的方法，其特征在于，所述第一指示信息还用于指示：所述第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量；其中，P为正整数。
  18. 根据权利要求11或12所述的方法，其特征在于，所述第一设备向所述第二设备发送所述第一指示信息，包括：
    所述第一设备按照第三周期向所述第二设备发送所述第一指示信息。
  19. 根据权利要求18所述的方法，其特征在于，所述方法还包括：
    所述第一设备按照第四周期向所述第二设备发送第三指示信息；其中，所述第三指示信息用于指示第二反馈系数，所述第四周期小于所述第三周期。
  20. 根据权利要求19所述的方法，其特征在于，所述第二反馈系数根据第一空域协方差矩阵的第二分解结果、所述第一频域协方差矩阵的第三分解结果和所述信道矩阵确定；其中，所述第二分解结果由所述第一空域协方差矩阵按照第二分解规则分解得到，所述第三分解结果由所述第一频域协方差矩阵按照第三分解规则分解得到。
  21. 根据权利要求20所述的方法，其特征在于，所述第二分解规则包括：所述第一空域协方差矩阵的对角矩阵中元素的排列顺序，以及所述第一空域协方差矩阵的空域特征基底的第一行元素的类型。
  22. 根据权利要求20或21所述的方法，其特征在于，所述第一指示信息还用于指示：所述第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量；其中，K为正整数。
  23. 根据权利要求20-22中任一项所述的方法，其特征在于，所述第三分解规则可以包括：所述第一频域协方差矩阵的对角矩阵中元素的排列顺序，以及所述第一频域协方差矩阵的频域特征基底的第一行元素的类型。
  24. 根据权利要求23所述的方法，其特征在于，所述第一指示信息还用于指示：所述第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量；其中，D为正整数。
  25. 一种信道状态信息的上报方法，其特征在于，所述方法包括：
    第二设备接收来自第一设备的第一指示信息；其中，所述第一指示信息用于构建信道矩阵对应的第一协方差矩阵，所述信道矩阵用于指示所述第一设备与所述第二设备之间的信道的信道状态信息；
    所述第二设备根据所述第一指示信息确定所述信道矩阵对应的第一协方差矩阵。
  26. 根据权利要求25所述的方法，其特征在于，所述第一指示信息用于指示叠加系数和码本向量；所述第二设备根据所述第一指示信息确定所述信道矩阵对应的第一协方差矩阵，包括：
    所述第二设备根据所述叠加系数和所述码本向量确定所述第一协方差矩阵。
  27. 根据权利要求26所述的方法，其特征在于，所述叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，所述码本向量包括用于指示角度时延的第一信息；所述第二设备根据所述叠加系数和所述码本向量确定所述信道矩阵对应的第一协方差矩阵，包括：
    所述第二设备根据所述第一叠加系数和所述第一信息确定第一空频联合协方差矩阵。
  28. 根据权利要求27所述的方法，其特征在于，所述第二设备接收来自第一设备的第一指示信息，包括：
    所述第二设备按照第一周期接收来自所述第一设备的所述第一指示信息。
  29. 根据权利要求28所述的方法，其特征在于，所述方法还包括：
    所述第二设备按照第二周期接收来自所述第一设备的第二指示信息；其中，所述第二指示信息用于指示第一反馈系数，所述第二周期小于所述第一周期。
  30. 根据权利要求29所述的方法，其特征在于，所述第一反馈系数是根据所述第一空频联合协方差矩阵的第一分解结果和信道矩阵确定的；其中，所述第一分解结果由所述第一空频联合协方差矩阵按照第一分解规则分解得到。
  31. 根据权利要求30所述的方法，其特征在于，所述方法还包括：
    所述第二设备根据所述第一分解规则，确定所述第一空频联合协方差矩阵的有效空频联合特征基底；其中，所述有效空频联合特征基底包括空频联合特征基底的前P列，P为正整数；
    所述第二设备根据所述有效空频联合特征基底和所述第一反馈系数确定所述信道矩阵。
  32. 根据权利要求31所述的方法，其特征在于，所述第一分解规则包括：所述第一空频联合协方差矩阵分解的对角矩阵中的元素的排列顺序，以及所述第一空频联合协方差矩阵分解的空频联合特征基 底的第一行元素的类型。
  33. 根据权利要求32所述的方法，其特征在于，所述第一指示信息还用于指示：所述第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量；其中，P为正整数。
  34. 根据权利要求33所述的方法，其特征在于，所述第二设备根据所述第一分解规则，确定所述第一空频联合协方差矩阵的有效空频联合特征基底，包括：
    所述第二设备根据所述第一分解规则和所述第一量化向量，确定所述第一空频联合协方差矩阵的有效空频联合特征基底。
  35. 根据权利要求26所述的方法，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数，所述码本向量包括用于指示角度的第二信息；所述第二设备根据所述叠加系数和所述码本向量确定第一协方差矩阵，包括：
    所述第二设备根据所述第二叠加系数和所述第二信息确定第一空域协方差矩阵。
  36. 根据权利要求26所述的方法，其特征在于，所述叠加系数包括用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示时延的第三信息；所述第二设备根据所述叠加系数和所述码本向量确定第一协方差矩阵，包括：
    所述第二设备根据所述第三叠加系数和所述第三信息确定第一频域协方差矩阵。
  37. 根据权利要求26所述的方法，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示角度的第二信息和用于指示时延的第三信息；所述第二设备根据所述叠加系数和所述码本向量确定第一协方差矩阵，包括：
    所述第二设备根据所述第二叠加系数和所述第二信息确定第一空域协方差矩阵；
    所述第二设备根据所述第三叠加系数和所述第三信息确定第一频域协方差矩阵。
  38. 根据权利要求37所述的方法，其特征在于，所述第二设备接收来自第一设备的第一指示信息，包括：
    所述第二设备按照第三周期接收来自所述第一设备的所述第一指示信息。
  39. 根据权利要求38所述的方法，其特征在于，所述方法还包括：
    所述第二设备按照第四周期接收来自所述第一设备的第三指示信息；其中，所述第三指示信息用于指示第二反馈系数，所述第四周期小于所述第三周期。
  40. 根据权利要求39所述的方法，其特征在于，所述第二反馈系数是根据所述第一空域协方差矩阵的第二分解结果、所述第一频域协方差矩阵的第三分解结果和所述信道矩阵确定的；其中，所述第二分解结果由所述第一空域协方差矩阵按照第二分解规则分解得到，所述第三分解结果由所述第一频域协方差矩阵按照第三分解规则分解得到。
  41. 根据权利要求40所述的方法，其特征在于，所述方法还包括：
    所述第二设备根据所述第二分解规则，确定有效空域特征基底；
    所述第二设备根据所述第三分解规则，确定有效频域特征基底；
    所述第二设备根据所述有效空域特征基底、所述有效频域特征基底和所述第二反馈系数确定信道状态信息。
  42. 根据权利要求41所述的方法，其特征在于，所述第二分解规则包括：所述第一空域协方差矩阵的对角矩阵中的元素的排列顺序，以及所述第一空域协方差矩阵的特征基底的第一行元素的类型。
  43. 根据权利要求42所述的方法，其特征在于，所述第一指示信息还用于指示：所述第一空域协方差矩阵分解后的空域特征基底中前K列的第一行元素量化后的第二量化向量。
  44. 根据权利要求43所述的方法，其特征在于，所述第二设备根据所述第二分解规则，确定有效空域特征基底，包括：
    所述第二设备根据所述第二分解规则和所述第二量化向量，确定所述有效空域特征基底；其中，所述有效空域特征基底包括所述第一空域协方差矩阵的空域特征基底的前K列。
  45. 根据权利要求41所述的方法，其特征在于，所述第三分解规则包括：所述第一频域协方差矩阵的对角矩阵中的元素的排列顺序，以及所述第一频域协方差矩阵的频域特征基底的第一行元素的类型。
  46. 根据权利要求45所述的方法，其特征在于，所述第一指示信息还用于指示：所述第一频域协方差矩阵分解后的频域特征基底中前D列的第一行元素量化后的第三量化向量。
  47. 根据权利要求46所述的方法，其特征在于，所述方法还包括：
    所述第二设备根据所述第三分解规则和所述第三量化向量，确定有效频域特征基底；其中，所述有效频域特征基底包括所述第一频域协方差矩阵的频域特征基底的前D列。
  48. 一种通信装置，其特征在于，所述装置包括：处理模块和收发模块；
    所述收发模块，用于接收来自第二设备的参考信号；
    所述处理模块，用于根据参考信号确定第一指示信息；其中，所述第一指示信息用于构建信道矩阵对应的第一协方差矩阵，所述信道矩阵用于指示所述第一设备与所述第二设备之间的信道的信道状态信息；
    所述收发模块，用于向所述第二设备发送所述第一指示信息。
  49. 根据权利要求48所述的装置，其特征在于，所述第一指示信息用于指示叠加系数和码本向量，所述叠加系数和所述码本向量用于确定所述第一协方差矩阵。
  50. 根据权利要求48或49所述的装置，其特征在于，所述第一协方差矩阵与所述信道矩阵对应的实际协方差矩阵之间满足预设的优化模型。
  51. 根据权利要求50所述的装置，其特征在于，所述预设的优化模型包括：

    s.t.L≤Lmax；
    其中，min表示取最小值，“‖‖F”表示取F范数，R为所述信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l<L，且l为整数；αl为第l个叠加系数，wl为第l个码本向量，为wl的共轭转置，s.t.为约束条件，L为信道多径数目，Lmax为L的最大取值，L、Lmax均为大于0的整数。
  52. 根据权利要求50所述的装置，其特征在于，所述叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，所述码本向量包括用于指示角度时延的第一信息，所述第一叠加系数和所述第一信息用于确定第一空频联合协方差矩阵；
    所述预设的优化模型包括：所述第一空频联合协方差矩阵与所述信道矩阵对应的实际空频联合协方差矩阵之间满足的第一优化模型。
  53. 根据权利要求52所述的装置，其特征在于，所述第一优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空频联合协方差矩阵，Σ表示求和运算，0≤l0<L0，且l0为整数；为第l0个第一叠加系数，为第l0个多径角度对应的导向矢量，为的共轭转置，为第l0个相位变化向量，为的共轭，为的转置，为第l0个第一信息，s.t.为约束条件，L0为信道多径数目，为L0的最大取值，L0、均为大于0的整数。
  54. 根据权利要求50所述的装置，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数，所述码本向量包括用于指示角度的第二信息；其中，所述第二叠加系数和所述第二信息用于确定第一空域协方差矩阵；
    所述预设的优化模型包括：所述第一空域协方差矩阵与所述信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型。
  55. 根据权利要求54所述的装置，其特征在于，所述第二优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空域协方差矩阵， Σ表示求和运算；为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数。
  56. 根据权利要求50所述的装置，其特征在于，所述叠加系数包括用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示时延的第三信息，所述第三叠加系数和所述第三信息用于确定第一频域协方差矩阵；
    所述预设的优化模型包括：所述第一频域协方差矩阵与所述信道矩阵对应的实际频域协方差矩阵之间满足第三优化模型。
  57. 根据权利要求56所述的装置，其特征在于，所述预设的第三优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
  58. 根据权利要求50所述的装置，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示角度的第二信息和用于指示时延的第三信息，所述第二叠加系数和所述第二信息用于确定第一空域协方差矩阵，所述第三叠加系数和所述第三信息用于确定第一频域协方差矩阵；所述第一空域协方差矩阵与所述信道矩阵对应的实际空域协方差矩阵之间满足的第二优化模型，所述第一频域协方差矩阵与所述信道矩阵对应的实际频域协方差矩阵之间满足的第三优化模型。
  59. 根据权利要求58所述的装置，其特征在于，所述第二优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际空域协方差矩阵，Σ表示求和运算；为第l1个第二叠加系数，为第l1个多径角度对应的导向矢量，为的共轭转置，s.t.为约束条件，L1为空域上信道多径数目，为L1的最大取值，L1、均为大于0的整数，0≤l1<L1，且l1为整数；
    所述第三优化模型包括：

    其中，min表示取最小值，“‖‖F”表示取F范数，为所述信道矩阵对应的实际频域协方差矩阵，Σ表示求和运算；为第l2个第三叠加系数，为第l2个相位变化向量，为的共轭转置，s.t.为约束条件，L2为频域上信道多径的数目，为L2的最大取值，L2、均为大于0的整数，0≤l2<L2，且l2为整数。
  60. 根据权利要求52或53所述的装置，其特征在于，
    所述收发模块，还用于按照第一周期向所述第二设备发送所述第一指示信息。
  61. 根据权利要求60所述的装置，其特征在于，
    所述收发模块，还用于按照第二周期向所述第二设备发送第二指示信息；其中，所述第二指示信息用于指示第一反馈系数，所述第二周期小于所述第一周期。
  62. 根据权利要求61所述的装置，其特征在于，所述第一反馈系数根据所述第一空频联合协方差矩 阵的第一分解结果和所述信道矩阵确定；其中，所述第一分解结果由所述第一空频联合协方差矩阵按照第一分解规则分解得到。
  63. 根据权利要求62所述的装置，其特征在于，所述第一分解规则包括：所述第一空频联合协方差矩阵分解的对角矩阵中元素的排列顺序，以及所述第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型。
  64. 根据权利要求62或63所述的装置，其特征在于，所述第一指示信息还用于指示：所述第一分解结果的空频联合特征基底中前P列的第一行元素量化后的第一量化向量；其中，P为正整数。
  65. 根据权利要求58或59所述的装置，其特征在于，
    所述收发模块，还用于按照第三周期向所述第二设备发送所述第一指示信息。
  66. 根据权利要求65所述的装置，其特征在于，
    所述收发模块，还用于按照第四周期向所述第二设备发送第三指示信息；其中，所述第三指示信息用于指示第二反馈系数，所述第四周期小于所述第三周期。
  67. 根据权利要求66所述的装置，其特征在于，所述第二反馈系数根据第一空域协方差矩阵的第二分解结果、所述第一频域协方差矩阵的第三分解结果和所述信道矩阵确定；其中，所述第二分解结果由所述第一空域协方差矩阵按照第二分解规则分解得到，所述第三分解结果由所述第一频域协方差矩阵按照第三分解规则分解得到。
  68. 根据权利要求67所述的装置，其特征在于，所述第二分解规则包括：所述第一空域协方差矩阵的对角矩阵中元素的排列顺序，以及所述第一空域协方差矩阵的空域特征基底的第一行元素的类型。
  69. 根据权利要求67或68所述的装置，其特征在于，所述第一指示信息还用于指示：所述第二分解结果的空域特征基底中前K列的第一行元素量化后的第二量化向量；其中，K为正整数。
  70. 根据权利要求67-69中任一项所述的装置，其特征在于，所述第三分解规则可以包括：所述第一频域协方差矩阵的对角矩阵中元素的排列顺序，以及所述第一频域协方差矩阵的频域特征基底的第一行元素的类型。
  71. 根据权利要求70所述的装置，其特征在于，所述第一指示信息还用于指示：所述第三分解结果的频域特征基底中前D列的第一行元素量化后的第三量化向量；其中，D为正整数。
  72. 一种通信装置，其特征在于，所述装置包括：处理模块和收发模块；
    所述收发模块，用于接收来自第一设备的第一指示信息；其中，所述第一指示信息用于构建信道矩阵对应的协方差矩阵，所述信道矩阵用于指示所述第一设备与所述第二设备之间的信道的信道状态信息；
    所述处理模块，用于根据所述第一指示信息确定所述信道矩阵对应的第一协方差矩阵。
  73. 根据权利要求72所述的装置，其特征在于，所述第一指示信息用于指示叠加系数和码本向量；
    所述处理模块，具体用于根据所述叠加系数和所述码本向量确定所述第一协方差矩阵。
  74. 根据权利要求73所述的装置，其特征在于，所述叠加系数包括用于指示角度时延功率谱的特征的第一叠加系数，所述码本向量包括用于指示角度时延的第一信息；
    所述处理模块，具体用于根据所述第一叠加系数和所述第一信息确定第一空频联合协方差矩阵。
  75. 根据权利要求74所述的装置，其特征在于，
    所述收发模块，还用于按照第一周期接收来自所述第一设备的所述第一指示信息。
  76. 根据权利要求75所述的装置，其特征在于，
    所述收发模块，还用于按照第二周期接收来自所述第一设备的第二指示信息；其中，所述第二指示信息用于指示第一反馈系数，所述第二周期小于所述第一周期。
  77. 根据权利要求76所述的装置，其特征在于，所述第一反馈系数是根据所述第一空频联合协方差矩阵的第一分解结果和信道矩阵确定的；其中，所述第一分解结果由所述第一空频联合协方差矩阵按照第一分解规则分解得到。
  78. 根据权利要求77所述的装置，其特征在于，
    所述处理模块，还用于根据所述第一分解规则，确定所述第一空频联合协方差矩阵的有效空频联合特征基底；其中，所述有效空频联合特征基底包括空频联合特征基底的前P列，P为正整数；
    所述处理模块，还用于根据所述有效空频联合特征基底和所述第一反馈系数确定所述信道矩阵。
  79. 根据权利要求78所述的装置，其特征在于，所述第一分解规则包括：所述第一空频联合协方差矩阵分解的对角矩阵中的元素的排列顺序，以及所述第一空频联合协方差矩阵分解的空频联合特征基底的第一行元素的类型。
  80. 根据权利要求79所述的装置，其特征在于，所述第一指示信息还用于指示：所述第一空频联合协方差矩阵分解后的空频联合特征基底中，前P列的第一行元素量化后的第一量化向量；其中，P为正整数。
  81. 根据权利要求80所述的装置，其特征在于，
    所述处理模块，还用于根据所述第一分解规则和所述第一量化向量，确定所述第一空频联合协方差矩阵的有效空频联合特征基底。
  82. 根据权利要求73所述的装置，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数，所述码本向量包括用于指示角度的第二信息；
    所述处理模块，具体用于根据所述第二叠加系数和所述第二信息确定第一空域协方差矩阵。
  83. 根据权利要求73所述的装置，其特征在于，所述叠加系数包括用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示时延的第三信息；
    所述处理模块，具体用于根据所述第三叠加系数和所述第三信息确定第一频域协方差矩阵。
  84. 根据权利要求73所述的装置，其特征在于，所述叠加系数包括用于指示角度功率谱的特征的第二叠加系数和用于指示时延功率谱的特征的第三叠加系数，所述码本向量包括用于指示角度的第二信息和用于指示时延的第三信息；
    所述处理模块，具体用于根据所述第二叠加系数和所述第二信息确定第一空域协方差矩阵；以及，
    根据所述第三叠加系数和所述第三信息确定第一频域协方差矩阵。
  85. 根据权利要求84所述的装置，其特征在于，
    所述收发模块，还用于按照第三周期接收来自所述第一设备的所述第一指示信息。
  86. 根据权利要求85所述的装置，其特征在于，
    所述收发模块，还用于按照第四周期接收来自所述第一设备的第三指示信息；其中，所述第三指示信息用于指示第二反馈系数，所述第四周期小于所述第三周期。
  87. 根据权利要求85所述的装置，其特征在于，所述第二反馈系数是根据所述第一空域协方差矩阵的第二分解结果、所述第一频域协方差矩阵的第三分解结果和所述信道矩阵确定的；其中，所述第二分解结果由所述第一空域协方差矩阵按照第二分解规则分解得到，所述第三分解结果由所述第一频域协方差矩阵按照第三分解规则分解得到。
  88. 根据权利要求87所述的装置，其特征在于，
    所述处理模块，还用于根据所述第二分解规则，确定有效空域特征基底；
    所述处理模块，还用于根据所述第三分解规则，确定有效频域特征基底；
    所述处理模块，还用于根据所述有效空域特征基底、所述有效频域特征基底和所述第二反馈系数确定信道状态信息。
  89. 根据权利要求88所述的装置，其特征在于，所述第二分解规则包括：所述第一空域协方差矩阵的对角矩阵中的元素的排列顺序，以及所述第一空域协方差矩阵的特征基底的第一行元素的类型。
  90. 根据权利要求89所述的装置，其特征在于，所述第一指示信息还用于指示：所述第一空域协方差矩阵分解后的空域特征基底中前K列的第一行元素量化后的第二量化向量。
  91. 根据权利要求90所述的装置，其特征在于，
    所述处理模块，还用于根据所述第二分解规则和所述第二量化向量，确定所述有效空域特征基底；其中，所述有效空域特征基底包括所述第一空域协方差矩阵的空域特征基底的前K列。
  92. 根据权利要求88所述的装置，其特征在于，所述第三分解规则包括：所述第一频域协方差矩阵的对角矩阵中的元素的排列顺序，以及所述第一频域协方差矩阵的频域特征基底的第一行元素的类型。
  93. 根据权利要求92所述的装置，其特征在于，所述第一指示信息还用于指示：所述第一频域协方差矩阵分解后的频域特征基底中前D列的第一行元素量化后的第三量化向量。
  94. 根据权利要求93所述的装置，其特征在于，
    所述处理模块，还用于根据所述第三分解规则和所述第三量化向量，确定有效频域特征基底；其中， 所述有效频域特征基底包括所述第一频域协方差矩阵的频域特征基底的前D列。
  95. 一种通信装置，其特征在于，包括：处理器，所述处理器与存储器耦合；
    所述处理器，用于执行所述存储器中存储的计算机程序，以使得所述通信装置执行如权利要求1-24中任一项所述的信道状态信息的上报方法，或者，以使得所述通信装置执行如权利要求25-47中任一项所述的方法。
  96. 一种通信装置，其特征在于，包括：处理器和接口电路；其中，
    所述接口电路，用于接收代码指令并传输至所述处理器；
    所述处理器用于运行所述代码指令以执行如权利要求1-24中任一项所述的方法，或者，以执行如权利要求25-47中任一项所述的方法。
  97. 一种通信装置，其特征在于，所述通信装置包括处理器和收发器，所述收发器用于所述通信装置和其他通信装置之间进行信息交互，所述处理器执行程序指令，用以执行如权利要求1-24中任一项所述的信道状态信息的上报方法，或者，用以执行如权利要求25-47中任一项所述的信道状态信息的上报方法。
  98. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质包括计算机程序或指令，当所述计算机程序或指令在计算机上运行时，使得所述计算机执行如权利要求1-24中任一项所述的信道状态信息的上报方法，或者，使得所述计算机执行如权利要求25-47中任一项所述的信道状态信息的上报方法。
  99. 一种计算机程序产品，其特征在于，所述计算机程序产品包括：计算机程序或指令，当所述计算机程序或指令在计算机上运行时，使得所述计算机执行如权利要求1-24中任一项所述的信道状态信息的上报方法，或者，使得所述计算机执行如权利要求25-47中任一项所述的信道状态信息的上报方法。
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