WO2018137235A1 - 用于反馈信道状态信息的方法、终端设备和网络设备 - Google Patents

用于反馈信道状态信息的方法、终端设备和网络设备 Download PDF

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Publication number
WO2018137235A1
WO2018137235A1 PCT/CN2017/072731 CN2017072731W WO2018137235A1 WO 2018137235 A1 WO2018137235 A1 WO 2018137235A1 CN 2017072731 W CN2017072731 W CN 2017072731W WO 2018137235 A1 WO2018137235 A1 WO 2018137235A1
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matrix
terminal device
channel
information
dimension
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PCT/CN2017/072731
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English (en)
French (fr)
Inventor
杨烨
苏白龙
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华为技术有限公司
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Priority to PCT/CN2017/072731 priority Critical patent/WO2018137235A1/zh
Priority to EP17894492.2A priority patent/EP3565133B1/en
Priority to CN201780083321.4A priority patent/CN110168949B/zh
Priority to KR1020197023791A priority patent/KR102202364B1/ko
Priority to RU2019126633A priority patent/RU2720178C1/ru
Priority to JP2019540428A priority patent/JP6911129B2/ja
Publication of WO2018137235A1 publication Critical patent/WO2018137235A1/zh
Priority to US16/523,409 priority patent/US10778294B2/en
Priority to US17/009,383 priority patent/US20200403659A1/en

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    • 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
    • H04B7/0658—Feedback reduction
    • H04B7/066—Combined feedback for a number of channels, e.g. over several subcarriers like in orthogonal frequency division multiplexing [OFDM]
    • 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
    • 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
    • H04B7/0413—MIMO systems
    • H04B7/0456—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting
    • H04B7/046—Selection of precoding matrices or codebooks, e.g. using matrices antenna weighting taking physical layer constraints into account
    • 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
    • H04B7/06—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
    • H04B7/0634—Antenna weights or vector/matrix coefficients

Definitions

  • Embodiments of the present invention relate to the field of wireless communications, and more particularly, to a method, a terminal device, and a network device for feeding back channel state information.
  • Massive Multiple-Input Multiple-Output is the key technology recognized by the 5th Generation mobile communication (5G).
  • 5G 5th Generation mobile communication
  • the increase in system capacity of Massive MIMO technology stems from its use of a large amount of spatial freedom for multi-user space division multiplexing gain.
  • To better harvest the gain of space division multiplexing network equipment needs to obtain accurate Channel State Information (CSI).
  • CSI Channel State Information
  • the method for the network device to obtain the CSI includes: the network device sends a channel state information-reference signal (CSI-RS) to the terminal device, and the terminal device performs channel estimation according to the CSI-RS sent by the network device, according to the estimation result.
  • CSI-RS channel state information-reference signal
  • a precoding matrix is selected from the stored codebooks.
  • the index of the selected precoding matrix in the codebook is fed back to the network device through the uplink channel, and the index is recorded as a Precoding Matrix Indicator (PMI).
  • PMI Precoding Matrix Indicator
  • the precoding matrix selected by the terminal device is used to represent the CSI.
  • This mechanism limits the accuracy of the CSI characterized by the precoding matrix and is detrimental to the network device's acquisition of accurate CSI.
  • the embodiments of the present invention provide a method, a terminal device, and a network device for feeding back channel state information, which are beneficial to the network device to acquire accurate CSI.
  • the first aspect provides a method for feeding back channel state information, where the method includes: the terminal device sends matrix information of a dimensionality reduction matrix to a network device, where the first dimension of the dimensionality reduction matrix is sent by the network device The number of the antenna ports is the same, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix; the terminal device sends the vector information of the feature vector of the downlink equivalent channel to the network device, The feature vector of the downlink equivalent channel is obtained based on the dimensionality reduction matrix; wherein the matrix information includes a matrix index of the dimensionality reduction matrix, or the matrix information includes the terminal device by using the dimensionality reduction matrix The information obtained by the element is quantized; the vector information includes an index of the feature vector, or the vector information includes information obtained by the terminal device by quantizing an element of the feature vector.
  • the method of the embodiment of the present invention is not limited to the codebook technology, and the CSI is jointly characterized by the dimensionality reduction matrix and the feature vector, which is advantageous for accurate representation, compared with the prior art, which uses the precoding matrix determined from the codebook to characterize the CSI.
  • CSI to enable network devices to acquire accurate CSI.
  • the first dimension is a row dimension
  • the second dimension is a column dimension
  • the dimension reduction matrix is used to perform dimension reduction on a dimension of a transmit antenna port of the network device in a channel matrix of the network device.
  • the dimension reduction matrix is used to perform dimension reduction on a channel matrix corresponding to the downlink reference signal.
  • the dimension reduction matrix is used for the downlink parameter received in the second time period.
  • the channel matrix corresponding to the test signal is dimension reduced.
  • the feature vector of the downlink equivalent channel is used to represent a channel state of a downlink equivalent channel
  • the dimension reduction matrix and the feature vector of the downlink equivalent channel are used by Characterizing the channel state of the downlink channel.
  • At least one of the matrix information of the dimensionality reduction matrix and the vector information of the feature vector is sent by using an uplink data channel.
  • the dimension reduction information occupies more bits, and is more suitable for transmission through the uplink data channel.
  • the feature vector is calculated by the terminal device according to the actual situation of the downlink channel, the vector information is more suitable for transmission through the uplink data channel. Selecting a matching transmission channel according to the matrix information and the actual situation of the vector information is advantageous for the terminal device to send the matrix information and the vector information to the network device.
  • the dimension reduction matrix is determined by the terminal device according to a channel matrix corresponding to a downlink reference signal received in a first time period, where the The energy of the subspace corresponding to the dimensional matrix is the highest energy among the plurality of subspaces corresponding to the downlink channel in the same dimension, and the orthogonality is satisfied between the column vectors of the dimensionality reduction matrix.
  • the method further includes: determining, by the terminal device, the dimensionality reduction matrix according to a channel matrix corresponding to the downlink reference signal received in the first time period.
  • the terminal device can determine the dimension reduction matrix according to the statistical characteristics of the downlink channel in the time period, so that the dimension reduction matrix can reduce the dimension of the channel matrix with low loss.
  • the terminal device determines the dimensionality reduction matrix according to a channel matrix corresponding to the downlink reference signal received in the first time period, including: the terminal device according to the first time Calculating a first covariance matrix, where the first channel covariance matrix is used to represent a statistical characteristic of a downlink channel corresponding to the first time period; the terminal device is configured according to the channel matrix corresponding to the downlink reference signal received by the segment The first covariance matrix calculates the dimensionality reduction matrix.
  • the first channel covariance matrix can be used to characterize the statistical characteristics of the downlink channel corresponding to a time period, so that the dimension reduction matrix determined by the terminal device can be used to reduce the channel matrix corresponding to a certain time period, that is, the terminal device does not need to be frequent.
  • the dimension reduction matrix is determined.
  • the terminal device does not need to frequently send the dimension reduction matrix, thereby reducing the overhead of feedback CSI.
  • the terminal device calculates a first covariance matrix according to the channel matrix corresponding to the downlink reference signal received in the first time period, where the terminal device calculates the terminal device a covariance matrix of each channel matrix in the channel matrix corresponding to the downlink reference signal received in the first time period; the terminal device averages the covariance matrix corresponding to the downlink reference signal received at the same time to obtain a plurality of second And a plurality of second covariance matrices corresponding to the plurality of times included in the first time period; the terminal device performs average or temporal filtering on the plurality of second covariance matrices Obtaining the first covariance matrix.
  • the first covariance matrix obtained by the method can more accurately characterize the statistical characteristics of the downlink channel corresponding to the first time period, thereby facilitating the terminal device to determine the dimensionality reduction matrix.
  • the second covariance matrix is used to characterize the statistical characteristics of the downlink channel at the corresponding moment.
  • the terminal device determines, according to the channel matrix corresponding to the downlink reference signal received in the first time period, the dimension reduction matrix of the downlink channel, where the terminal device is configured according to the first time period. And determining, by the channel matrix corresponding to the received downlink reference signal, the dimension reduction matrix from the preset set of dimensionality reduction matrices, where the matrix information of the dimension reduction matrix includes the preset dimension reduction matrix set of the dimension reduction matrix index of.
  • the dimension reduction matrix is selected by the terminal device from a preset set of dimensionality reduction matrix, and the matrix information includes an index, which is beneficial to reduce feedback overhead. Further, the solution can reduce the complexity of determining the dimension reduction matrix of the terminal device, and is beneficial to the terminal device to feed back the matrix information.
  • each of the columns of the dimensionality reduction matrix has the same beam pattern.
  • the energy of the receiving channel on each beam is similar, and the subsequent transmission of the low-dimensional downlink equivalent channel vector information is beneficial to reduce the overhead of feedback CSI.
  • the method further includes: determining, by the terminal device, performing dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first time according to the dimension reduction matrix, determining the first A feature vector of a downlink equivalent channel corresponding to the downlink reference signal received at a time.
  • the feature vector is calculated by the terminal device in combination with the actual situation of the downlink channel, so that the feature vector can more accurately characterize the channel state of the downlink equivalent channel, which is beneficial for the network device to acquire an accurate downlink channel state.
  • the terminal device determines, according to the dimension reduction matrix, a dimension of a downlink equivalent channel by performing a dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first moment. And determining, by the terminal device, the feature vector of the downlink channel of the first time according to the dimension reduction matrix, by performing a dimensionality reduction on a channel matrix corresponding to the downlink reference signal received at the first time of the second time period The second time period is after the first time period.
  • the dimension reduction matrix determined by the terminal device may be used to perform dimension reduction on the channel matrix of the second time period, that is, the dimension reduction matrix determined by the terminal device may be used for multiple downlink reference received by the terminal device in a time period.
  • the channel matrix corresponding to the signal is dimension-reduced, that is, the terminal device does not need to frequently determine the dimensionality reduction matrix. Helps reduce the overhead of feedback CSI.
  • the terminal device determines, according to the dimension reduction matrix, a downlink reference signal received by the first time by performing a dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first time.
  • Corresponding eigenvectors of the downlink equivalent channel including: the terminal device performing dimension reduction on the channel matrix corresponding to the received downlink reference signal at the first moment according to the dimension reduction matrix, to obtain the first moment And an equivalent matrix corresponding to the received downlink reference signal; the terminal device calculates a covariance matrix of each equivalent matrix in the equivalent matrix corresponding to the downlink reference signal received at the first moment; the terminal device passes the first The covariance matrix corresponding to the frequency domain resource region is averaged to obtain a third covariance matrix corresponding to the first resource region, where the covariance matrix corresponding to the first frequency domain resource region is included in the first frequency domain a covariance matrix of an equivalent matrix corresponding to the downlink reference signal received at the first moment in the resource region; the terminal device according to the
  • the vector information may be used to represent a channel state of a downlink equivalent channel of a full bandwidth, and may also be used to represent a channel state of a downlink equivalent channel of a local bandwidth, and the scheme has high flexibility. It is beneficial for the network device to fully understand the channel state of the downlink equivalent channel, and fully understand the channel state of the downlink channel, which is beneficial to the network device to better harvest the gain of the space division multiplexing.
  • the terminal device determines, according to the dimension reduction matrix, a dimension of a downlink equivalent channel by performing a dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first moment. And determining, by the terminal device, the dimension of the downlink equivalent channel from the preset feature vector set by performing dimension reduction on the channel matrix corresponding to the downlink reference signal received at the first time according to the dimension reduction matrix a vector, the vector information including an index of the set of feature vectors of the feature vector.
  • the feature vector of the downlink equivalent channel is selected by the terminal device from a preset set of feature vectors, and the vector information includes an index, which is beneficial to reduce feedback overhead. Further, the solution can reduce the complexity of determining the feature vector of the downlink equivalent channel by the terminal device, and is beneficial to the terminal device to feed back the vector information.
  • the feature vector of the downlink equivalent channel includes r feature vectors, where r is configured by the network device or r is the same as the number of data streams supported by the terminal device, where The feature value corresponding to any one of the r feature vectors is greater than or equal to the feature value of the feature vector of the downlink equivalent channel except for any one of the r feature directions, r ⁇ 1.
  • the terminal device does not need to feed back all the feature vectors of the downlink equivalent channel to the network device, which can reduce the feedback overhead and enable the network device to acquire accurate CSI. Further, the feature values corresponding to the r feature vectors are large, so that the r feature vectors can accurately represent the channel state of the downlink equivalent channel.
  • the period in which the terminal device sends the matrix information is longer than the period in which the terminal device sends the vector information.
  • the two information are respectively fed back according to the long period short period, which can reduce the feedback overhead and enable the network device to acquire accurate CSI.
  • the period in which the terminal device sends the matrix information is 0.1-1 second; and/or the period in which the terminal device sends the vector information is 5-10 milliseconds.
  • a second aspect provides a method for feeding back channel state information, where the method includes: receiving, by a network device, matrix information of a dimensionality reduction matrix sent by a terminal device, where a first dimension of the dimensionality reduction matrix is related to the network device The number of the transmit antenna ports is the same, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix; the network device receives the vector information of the feature vector of the downlink equivalent channel sent by the terminal device; Determining, by the terminal device, the precoding matrix according to the matrix information and the vector information, where the matrix information includes a matrix index of the dimensionality reduction matrix, or the matrix information includes the terminal device The information obtained by quantizing the elements of the dimensionality reduction matrix; the vector information includes an index of the feature vector, or the vector information includes information obtained by the terminal device by quantizing the elements of the feature vector.
  • the method of the embodiment of the present invention jointly represents the CSI through the dimension reduction matrix (matrix information) and the feature vector (vector information), which is beneficial to the network device.
  • matrix information dimension reduction matrix
  • vector information feature vector
  • At least one of the matrix information and the vector information is not selected from the codebook according to a certain rule (if selected from the codebook, no need to quantize the element), which is beneficial for the terminal device to obtain matching according to the actual channel state of the downlink channel.
  • the dimensionality reduction matrix and/or feature vector is such that the matrix information as well as the vector information can be used to accurately characterize the CSI.
  • At least one of the matrix information of the dimensionality reduction matrix and the vector information of the feature vector is sent by using an uplink data channel.
  • the dimension reduction information occupies more bits, and is more suitable for transmission through the uplink data channel.
  • the feature vector is calculated by the terminal device according to the actual situation of the downlink channel, the vector information occupies more bits, which is more suitable for passing.
  • the uplink data channel is transmitted. Selecting an appropriate transmission channel according to the matrix information and the actual situation of the vector information is advantageous for the network device to acquire the matrix information and the vector information.
  • the period in which the network device receives the matrix information is longer than the period in which the network device receives the vector information.
  • the network device receives the dimensionality reduction information and the vector information according to the long period short period, which can save the transmission resources and enable the network equipment to acquire the accurate CSI.
  • a third aspect provides a method for feeding back channel state information, where the method includes: receiving, by a terminal device, a downlink reference signal sent by a network device according to a dimensionality reduction matrix, a first dimension of the dimensionality reduction matrix, and the network device The number of the transmit antenna ports is the same, and the second dimension of the dimension reduction matrix is smaller than the first dimension of the dimension reduction matrix; the terminal device sends the channel matrix corresponding to the downlink reference signal to the network device.
  • Vector information of the feature vector of the downlink equivalent channel is provided by the network device.
  • the dimension reduction matrix is determined by the network device, and the terminal device is not required to periodically report the dimension reduction matrix, which is beneficial to reducing the overhead of feedback CSI.
  • the method further includes: determining, by the terminal device, a feature vector of the downlink equivalent channel according to a channel matrix corresponding to the downlink reference signal; The feature vector is quantized to obtain the vector information.
  • the terminal device sends the vector information of the feature vector to the network device, where the terminal device sends the vector information to the network device by using an uplink data channel.
  • the vector information occupies more bits, and is more suitable for transmission through the uplink data channel. Selecting a matching transmission channel according to the actual situation of the vector information is advantageous for the terminal device to send the vector information to the network device.
  • the method further includes: determining, by the terminal device, a covariance matrix of each channel matrix in a channel matrix corresponding to the downlink reference signal; and using, by the terminal device, the first frequency domain resource The covariance matrix corresponding to the region is averaged to obtain a third covariance matrix, where the covariance matrix corresponding to the first frequency domain resource region includes a channel corresponding to the downlink reference signal in the first frequency domain resource region a covariance matrix of the matrix, the first frequency domain resource region includes a full bandwidth or a local bandwidth; and the terminal device determines, according to the third covariance matrix, the downlink equivalent in the first frequency domain resource region a feature vector of the channel, the first frequency domain resource region including full bandwidth or local bandwidth.
  • the vector information can be used to characterize the channel state of the downlink equivalent channel of the full bandwidth, and can also be used to characterize the channel state of the downlink equivalent channel of the local bandwidth.
  • the flexibility of the scheme is high, which is beneficial for the network device to fully understand the downlink equivalent.
  • the channel state of the channel, and then fully understand the channel state of the downlink channel is beneficial to the network device to better harvest the gain of space division multiplexing.
  • the feature vector of the downlink equivalent channel includes r feature vectors, where r is configured by the network device or r is the same as the number of data streams supported by the terminal device, where The feature value corresponding to any one of the r feature vectors is greater than or equal to the feature value of the feature vector of the downlink equivalent channel except for any one of the r feature directions, r ⁇ 1.
  • a fourth aspect provides a method for feeding back channel state information, the method comprising: the network device according to The dimension reduction matrix sends a downlink reference signal, the first dimension of the dimensionality reduction matrix is the same as the number of the transmit antenna ports of the network device, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix
  • the network device receives vector information of a feature vector of a downlink equivalent channel that is sent by the terminal device according to the downlink reference signal; and the network device determines a precoding matrix according to the dimensionality reduction matrix and the vector information.
  • the network device receives, by the network device, vector information of a feature vector of a downlink equivalent channel that is sent by the terminal device according to the downlink reference signal, where the network device receives the device by using an uplink data channel. Said vector information.
  • the method further includes: determining, by the network device, the dimension reduction matrix according to a channel matrix corresponding to the uplink reference signal received in the first time period.
  • the determining, by the network device, the dimension reduction matrix according to the channel matrix corresponding to the uplink reference signal received in the first time period including: the network device according to the Calculating a first covariance matrix, wherein the first channel covariance matrix is used to represent a statistical characteristic of the uplink channel corresponding to the first time period; the terminal is configured by using a channel matrix corresponding to the uplink reference signal received by the time period; The device calculates the dimensionality reduction matrix according to the first covariance matrix.
  • the network device calculates a first covariance matrix, including: the terminal device calculates the terminal device a covariance matrix of each channel matrix in the channel matrix corresponding to the downlink reference signal received in the first time period; the network device averages the covariance matrix corresponding to the uplink reference signal received at the same time to obtain a plurality of second a covariance matrix, wherein the plurality of second covariance matrices are in one-to-one correspondence with the plurality of times included in the first time period; and the network device performs average or temporal filtering on the plurality of second covariance matrices Obtaining the first covariance matrix.
  • the network device determines that a period of the dimensionality reduction matrix is longer than a period in which the network device receives the vector information.
  • a terminal device for performing the method of the first aspect and any possible implementation of the first aspect.
  • the terminal device may comprise means for performing the method of the first aspect and any possible implementation of the first aspect.
  • a network device for performing the method of any of the second aspect and the second aspect.
  • the network device may comprise means for performing the method of the second aspect and any possible implementation of the second aspect.
  • a terminal device for performing the method of any of the third aspect and the third aspect.
  • the terminal device may comprise means for performing the method in any of the third and third possible implementations.
  • a network device for performing the method of any of the fourth and fourth possible implementations.
  • the network device may comprise means for performing the method of any of the fourth aspect and any of the possible implementations of the fourth aspect.
  • a terminal device includes a memory and a processor, the memory is configured to store a computer program, the processor is configured to call and run the computer program from the memory, so that the terminal device performs the first aspect and A method in any of the possible implementations of the first aspect.
  • a network device comprising a memory and a processor, the memory being for storing a computer program, the processor for calling and running the computer program from the memory, such that the network device performs the second Aspects of the method and any of the possible implementations of the second aspect.
  • a terminal device comprising a memory and a processor, the memory for storing a computer program, the processor for calling and running the computer program from the memory, such that the terminal device performs the third aspect described above And a method in any of the possible implementations of the third aspect.
  • a network device including a memory and a processor, the memory is configured to store a computer program, the processor is configured to call and run the computer program from the memory, so that the network device performs the fourth aspect and A unit of a method in any of the possible implementations of the fourth aspect.
  • a computer program product comprising: computer program code, when the computer program code is processed by a processing unit, a transceiver unit or a processor, a transceiver of the terminal device in the first aspect
  • the terminal device is caused to perform the method of the first aspect and any possible implementation of the first aspect.
  • a computer program product comprising: computer program code, when the computer code is run by a processing unit, a transceiver unit or a processor, a transceiver of a network device in the second aspect
  • the network device is caused to perform the method of the second aspect and any possible implementation of the second aspect.
  • a computer program product comprising: computer program code, when the computer program code is processed by a processing unit, a transceiver unit or a processor, a transceiver of the terminal device in the third aspect
  • the terminal device is caused to perform the method of any of the third aspect and the third aspect.
  • a seventeenth aspect a computer readable storage medium for storing a computer program, the computer program comprising instructions for performing the method of the first aspect and any possible implementation of the first aspect.
  • a computer readable storage medium for storing a computer program, the computer program comprising instructions for performing the method of the second aspect and any possible implementation of the second aspect.
  • a nineteenth aspect a computer readable storage medium for storing a computer program, the computer program comprising instructions for performing the method of any of the third aspect and the third aspect.
  • the method, the terminal device, and the network device of the embodiments of the present invention jointly represent the CSI by using a dimensionality reduction matrix and a feature vector, which is beneficial for the network device to acquire accurate CSI.
  • Figure 1 shows a schematic diagram of a communication system suitable for use with embodiments of the present invention.
  • FIG. 2 is a schematic flow chart of an example of a method for feeding back channel state information according to an embodiment of the present invention.
  • FIG. 3 is a schematic flowchart of another example of a method for feeding back channel state information according to an embodiment of the present invention.
  • FIG. 4 is a schematic flow chart of still another example of a method for feeding back channel state information according to an embodiment of the present invention.
  • FIG. 5 is a schematic block diagram of an example of a terminal device according to an embodiment of the present invention.
  • FIG. 6 is a schematic block diagram of an example of a network device according to an embodiment of the present invention.
  • FIG. 7 is a schematic block diagram of another example of a terminal device according to an embodiment of the present invention.
  • FIG. 9 is a schematic block diagram of still another example of a terminal device according to an embodiment of the present invention.
  • FIG. 10 is a schematic block diagram of still another example of a network device according to an embodiment of the present invention.
  • FIG. 11 is a schematic block diagram of still another example of a terminal device according to an embodiment of the present invention.
  • FIG. 12 is a schematic block diagram of still another example of a network device according to an embodiment of the present invention.
  • MIMO can be divided into single-user multiple input multiple output (Single-User MIMO, referred to as "SU-MIMO") and multi-user multiple input multiple output (Multi-User MIMO, referred to as "MU-MIMO").
  • Single-User MIMO Single-user multiple input multiple output
  • Multi-User MIMO multi-user multiple input multiple output
  • Massive MIMO arranges hundreds of antennas at the transmitting end, modulates the respective beams for dozens of target receivers, and transmits dozens of signals simultaneously on the same frequency resource through spatial signal isolation. Therefore, Massive MIMO technology can make full use of the spatial freedom brought by large-scale antenna configuration to improve spectrum efficiency.
  • FIG. 1 shows a schematic diagram of a communication system suitable for use with embodiments of the present invention.
  • the communication system 100 includes a network device 102 that can include multiple antennas, such as antennas 104, 106, 108, 110, 112, and 114.
  • network device 102 may additionally include a transmitter chain and a receiver chain, as will be understood by those of ordinary skill in the art, which may include multiple components related to signal transmission and reception (eg, processor, modulator, multiplexer) , demodulator, demultiplexer or antenna, etc.).
  • Network device 102 can communicate with a plurality of terminal devices, such as terminal device 116 and terminal device 122. However, it will be appreciated that network device 102 can communicate with any number of terminal devices similar to terminal device 116 or 122.
  • Terminal devices 116 and 122 may be, for example, cellular telephones, smart phones, portable computers, handheld communication devices, handheld computing devices, satellite radios, global positioning systems, PDAs, and/or any other suitable for communicating over wireless communication system 100. device.
  • terminal device 116 is in communication with antennas 112 and 114, wherein antennas 112 and 114 transmit information to terminal device 116 over forward link 118 and receive information from terminal device 116 over reverse link 120.
  • terminal device 122 is in communication with antennas 104 and 106, wherein antennas 104 and 106 transmit information to terminal device 122 over forward link 124 and receive information from terminal device 122 over reverse link 126.
  • the forward link 118 can utilize a different frequency band than that used by the reverse link 120, and the forward link 124 can utilize the reverse link. 126 different frequency bands used.
  • FDD Frequency Division Duplex
  • the forward link 118 and the reverse link 120 can use a common frequency band, a forward link 124, and a reverse link.
  • Link 126 can use a common frequency band.
  • Network device 102 transmits the downlink signal through a precoding technique.
  • the basic idea of the precoding technology is that the network device designs the downlink signal transmission mode by analyzing the CSI, so that the downlink signal sent by the network device can use the characteristic structure of the channel matrix, so that the interference between the independent data streams is as small as possible.
  • the network device learns the exact CSI the network device can obtain the maximum gain when transmitting the downlink signal.
  • Channel-calibrated TDD system can pass the channel sounding reference because of the reciprocity of uplink and downlink channels.
  • the Signaling Reference Signal (SRS) signal estimates the more accurate CSI, so that the network device may obtain more accurate CSI.
  • the CSI can only be fed back to the terminal device through the uplink channel. Internet equipment.
  • the terminal device directly feeds back the channel matrix of the downlink channel, which can enable the network device to obtain the most accurate CSI, but the overhead of the method is too large to be applied to the actual communication system.
  • the terminal device quantizes the CSI by using a codebook matrix in the codebook, which is known to the terminal device and the network device.
  • the terminal device determines a codebook matrix that best matches the CSI as a precoding matrix and feeds back an index of the precoding matrix to the network device.
  • the codebook is pre-configured, and the terminal device can select the most matching precoding matrix from the codebook according to the channel estimation result, but the best matching precoding matrix still has a large difference from the actual channel condition, that is, precoding. Matrix does not accurately characterize CSI. Although this method can reduce the feedback overhead, this method limits the accuracy of the CSI fed back by the terminal device.
  • the embodiment of the present invention provides a method for feeding back channel state information.
  • the channel based on Massive MIMO has spatial sparsity, and adopts compression and dimensionality reduction, and the feedback overhead of CSI and the feedback precision of CSI are adopted. Make a better compromise.
  • the method for feeding back channel state information according to an embodiment of the present invention is described in detail below.
  • GSM Global System of Mobile communication
  • CDMA Code Division Multiple Access
  • WCDMA Wideband Code Division Multiple Access
  • GPRS General Packet Radio Service
  • LTE Long Term Evolution
  • LTE-A Advanced Long Term Evolution
  • UMTS Universal Mobile Telecommunication System
  • Next Generation Communication System for example, 5G.
  • the network device may be a device for communicating with the mobile device, and the network device may be an access point (ACCESS POINT, abbreviated as "AP") in the WLAN, and a base station in the GSM or CDMA (Base Transceiver Station) Abbreviated as "BTS”), which may also be a base station (NodeB, referred to as "NB") in WCDMA, or an evolved base station (Evolutional Node B, "eNB” or “eNodeB”) in LTE, or a relay station or An access point, or an in-vehicle device, a wearable device, and a network device in a future 5G network or a network device in a publicly-developed Public Land Mobile Network (PLMN).
  • ACCESS POINT abbreviated as "AP”
  • AP Access Point
  • AP Access Point
  • BTS Base Transceiver Station
  • NB base station
  • eNB evolved base station
  • LTE Long Term Evolutional Node B
  • PLMN Public Land
  • the terminal device may also be referred to as a user equipment, an access terminal, a subscriber unit, a subscriber station, a mobile station, a mobile station, a remote station, a remote terminal, a mobile device, a user terminal, a terminal, a wireless communication device, User agent or user device.
  • the terminal device may be a site (STAION, referred to as "ST") in a Wireless Local Area Networks ("WLAN”), and may be a cellular phone, a cordless phone, or a Session Initiation Protocol ("SIP").
  • ST Wireless Local Area Networks
  • SIP Session Initiation Protocol
  • WLL Wireless Local Loop
  • PDA Personal Digital Assistant
  • handheld device with wireless communication function computing device or other connected to wireless modem
  • a processing device an in-vehicle device, a wearable device, and a next-generation communication system, for example, a terminal device in a 5G network or a terminal device in a future evolved PLMN.
  • FIG. 2 and FIG. 4 are schematic flowcharts of feedback channel state information according to an embodiment of the present invention. It should be understood that FIGS. 2 and 4 illustrate detailed communication steps or operations of the method, but the steps or operations are merely examples, and other operations in the embodiments of the present invention or the operations in FIGS. 2 and 4 may be performed. The deformation. Furthermore, the various steps in FIGS. 2 and 4 may be performed in a different order than that presented in FIGS. 2 and 4, respectively, and it is possible to perform only some of the operations in FIGS. 2 and 4.
  • the terminal device sends the matrix information of the dimension reduction matrix to the network device, and correspondingly, the network device receives the dimension reduction matrix sent by the terminal device.
  • the first dimension of the dimensionality reduction matrix is the same as the number of the transmit antenna ports of the network device, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix.
  • the dimensionality reduction matrix is used to reduce the dimension of the channel matrix.
  • the terminal device may perform dimension reduction on the channel matrix corresponding to the downlink reference signal received at the first moment according to the dimension reduction matrix.
  • the dimension reduction matrix is described by taking the first dimension as the row dimension and the second dimension as the column dimension.
  • the terminal device may perform channel estimation on the received downlink reference signal to obtain a channel estimation result, where the channel estimation result includes a channel matrix.
  • the method 200 can also include:
  • the network device sends a downlink reference signal to the terminal device, and correspondingly, the terminal device receives the downlink reference signal sent by the network device.
  • the terminal device may determine a dimension reduction matrix of the downlink channel according to a channel matrix corresponding to the downlink reference signal received by the terminal device in the first time period. Further, the dimensionality reduction matrix may be used to perform dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first time of the second time period.
  • the second time period is after the first time period, and the first time time may include the end time of the first time period.
  • the network device may periodically send a downlink reference signal, and accordingly, the terminal device may periodically receive the downlink reference signal sent by the network device.
  • the terminal device may obtain a channel matrix corresponding to the downlink reference signal received in the first time period according to the downlink reference signal received in the first time period.
  • the terminal device receives the downlink reference signal for a period of 10 milliseconds, that is, the terminal device receives the downlink reference signal every 10 milliseconds.
  • the terminal device may acquire the channel matrix corresponding to the downlink reference signal received in the first time period according to the 10 downlink reference signals received in the 0.1 second period.
  • the downlink reference signal received by the terminal device each time in the first time period occupies at least one resource block (RB), and the at least one RB corresponds to at least one channel matrix one by one.
  • the channel matrix corresponding to the downlink reference signal received in the first time period includes multiple channel matrices, because the terminal device can receive the downlink reference signal multiple times in the first time period.
  • the “channel matrix corresponding to the downlink reference signal received in the first time period” may be referred to as “channel matrix set”.
  • the first time period is 0.1 second, and the receiving period of the downlink reference signal is 10 milliseconds.
  • the terminal device can acquire M channel matrices each time receiving the downlink reference signal, and the channel matrix set includes 10 ⁇ M channel matrices. .
  • the terminal device is in at least one lower reference signal received at the same time (ie, one cycle).
  • Each downlink reference signal corresponds to one antenna port, and each antenna port may correspond to one physical antenna or may correspond to one virtual antenna, wherein the virtual antenna may be a weighted combination of multiple physical antennas.
  • the terminal device may obtain a channel estimation result (ie, a channel matrix) between the terminal device and the antenna port according to the downlink reference signal corresponding to the antenna port.
  • the CSI-RS is used for the terminal to perform channel state information measurement, especially for multi-antenna transmission.
  • the CSI-RS is used as an example of the reference signal, and is only an exemplary description.
  • the embodiment of the present invention does not limit the measurement of the channel state by other reference signals.
  • the method 200 can also include:
  • the terminal device determines the dimension reduction matrix according to a channel matrix corresponding to the downlink reference signal received in the first time period.
  • the terminal device may acquire a channel matrix set according to the downlink reference signal received in the first time period.
  • Each dimension of the channel matrix H is the channel matrix for the set of N R ⁇ N T, where, N R represents the number of transmit antenna ports of the terminal device, N T denotes the number of receiving antenna ports of the network device.
  • the terminal device may determine, according to the set of channel matrices, a dimension reduction matrix P for performing dimensionality reduction on the channel matrix, the dimension of the dimensionality reduction matrix P being N T ⁇ N P , where N P ⁇ N T .
  • the dimensionality reduction matrix is used to reduce the dimension of the channel matrix, and the high-dimensional channel matrix H can be reduced by the dimensionality reduction matrix to obtain a low-dimensional equivalent matrix.
  • the channel matrix Dimension reduction matrix Equivalent matrix can be obtained after dimension reduction
  • the degree of loss of the high-dimensional channel matrix dimension reduction to the low-dimensional equivalent matrix is related to the dimension reduction matrix.
  • the energy of the subspace corresponding to the dimensionality reduction matrix in the first time period is the downlink in the same dimension.
  • the energy of the plurality of subspaces corresponding to the channel is the highest, and the orthogonality is satisfied between the column vectors of the dimensionality reduction matrix.
  • the "subspace corresponding to the dimensionality reduction matrix" is referred to as "the first subspace”.
  • the energy of the first subspace is the highest energy among the plurality of subspaces corresponding to the downlink channel in the same dimension. It can be understood that the energy of the downlink channel is mainly concentrated in the first subspace in the first time period.
  • the channel matrix set can be regarded as a space, and the energy of the downlink channel is non-uniformly distributed in the space.
  • the energy of the downlink channel is mainly concentrated in the first subspace, and the first subspace is Can be a feature subspace of the space.
  • a low-dimensional equivalent matrix can be obtained by projecting a high-dimensional channel matrix into the first subspace (ie, multiplied by a dimensionality reduction matrix corresponding to the first subspace).
  • the low dimensional channel matrix can be considered to be a concentrated representation of a high dimensional channel matrix.
  • the manner in which the terminal device determines the dimensionality reduction matrix may include at least the following:
  • the terminal device calculates the dimensionality reduction matrix.
  • the terminal device may calculate the first covariance matrix Calculate the dimensionality reduction matrix.
  • the first covariance matrix is used to characterize (or indicate) the statistical characteristics of the downlink channel corresponding to the first time period.
  • the terminal device can calculate the first covariance matrix in multiple manners.
  • the terminal device can calculate a covariance matrix of each channel matrix in the set of channel matrices to obtain a set of covariance matrices.
  • the covariance matrix included in the set of covariance matrices has a one-to-one correspondence with a channel matrix included in the channel matrix set.
  • the terminal device may divide the covariance matrix in the set of covariance matrices into multiple groups according to time, and the plurality of groups of covariance matrices may correspond to a plurality of times one by one, and the terminal device may average each set of covariance matrices to obtain corresponding moments.
  • the second covariance matrix the terminal device averages or temporally filters the second covariance matrix of the plurality of times to obtain the first covariance matrix.
  • the second covariance matrix is used to characterize the statistical characteristics of the downlink channel at the corresponding moment.
  • the terminal device may acquire M channel matrices H each time the downlink reference signal is received, the channel matrix set includes 10 ⁇ M channel matrices H, and the terminal device calculates each channel matrix H of the 10 ⁇ M channel matrices
  • the covariance matrix H H H yields a 10 ⁇ M covariance matrix H H H .
  • the terminal device may average the M covariance matrices at each moment to obtain a second covariance matrix at the moment, and the terminal device averages or temporally filters the 10 second covariance matrices to obtain the first covariance matrix. .
  • the terminal device may obtain the dimensionality reduction matrix according to the first covariance matrix by an eigenvalue decomposition method, a singular value decomposition (SVD) method, a power method or other algorithms.
  • the first subspace corresponding to the dimension reduction matrix may be a feature subspace of the first covariance matrix.
  • the terminal device may determine the dimensionality reduction matrix by a PAST algorithm, a Lanczos algorithm, and other algorithms according to a channel matrix set.
  • the dimension reduction matrix in the first method is adaptively calculated by the terminal device according to the downlink channel estimation result, and the channel reduction matrix of the downlink channel is reduced according to the calculated dimensionality reduction matrix, which can reduce the channel matrix dimensionality reduction of the downlink channel. loss.
  • the method 200 may further include: the terminal device acquiring the matrix information by performing quantization on an element of the dimensionality reduction matrix.
  • the terminal device sends the matrix information through an uplink data channel.
  • the terminal device can quantize the elements of the dimensionality reduction matrix in multiple ways. For example, the terminal device may quantize the amplitude and phase separately for each column of the dimensionality reduction matrix. Since both amplitude and phase can be regarded as unsigned numbers, the quantization overhead of the sign bits is eliminated, thereby saving feedback overhead. For another example, the terminal device may quantize the real part and the imaginary part separately for each column of the dimensionality reduction matrix. The quantization process will be described later.
  • the terminal device determines the dimensionality reduction matrix from a preset set of dimensionality reduction matrices.
  • a set of dimensionality reduction matrices may be preset, and the set of dimensionality reduction matrices is known to both the terminal device and the network device, and the reduced dimensional matrix includes a plurality of dimensionality reduction matrices.
  • the terminal device may select a dimensionality reduction matrix of the downlink channel from the set of dimensionality reduction matrices according to the channel matrix set.
  • the terminal device can select the dimension reduction matrix by using multiple criteria. For example, the terminal device may calculate the energy of the downlink channel corresponding to each dimension reduction matrix in the dimension reduction matrix set based on the channel matrix set, and select the dimension reduction matrix with the highest energy of the downlink channel as the dimension reduction matrix of the downlink channel. That is, it can be considered that the energy of the downlink channel is mainly concentrated in the first subspace corresponding to the dimensionality reduction matrix in the first time period,
  • the dimension reduction matrix is selected by the terminal device from the preset dimension reduction matrix set, which can reduce the feedback overhead of the terminal device feedback reduction dimension matrix. Further, the complexity of calculating the dimensionality reduction matrix of the terminal device can also be reduced.
  • the matrix information includes an index of the dimensionality reduction matrix in the preset dimensionality reduction matrix set.
  • the dimensionality reduction matrix corresponds to a plurality of orthogonal beams of the same beam pattern. That is to say, the corresponding beam pattern of each column of the dimensionality reduction matrix is the same.
  • the energy of the receiving channel on each beam is similar, and the feedback overhead is advantageously reduced when the related information of the downlink equivalent channel is subsequently transmitted.
  • the generation of the reduced dimension matrix set of the embodiment of the present invention may utilize a large-scale antenna array sub-array partition and/or a Kronecker product structure, but is not limited.
  • the terminal device sends vector information of a feature vector of a downlink equivalent channel to the network device; correspondingly, the network device receives vector information sent by the terminal device;
  • the feature vector of the downlink equivalent channel is obtained based on the dimension reduction matrix.
  • the downlink equivalent channel can be understood as a channel obtained by projecting the downlink channel into the first subspace (or a channel obtained by reducing the dimension of the downlink channel through the dimensionality reduction matrix).
  • the downlink equivalent channel can be considered as a concentrated representation of the downlink channel, and the channel state of the downlink equivalent channel and the dimensionality reduction matrix can be used to characterize the channel state of the downlink channel.
  • the eigenvector of the downlink equivalent channel may be used to characterize the channel state of the downlink equivalent channel (eg, the eigenvector of the downlink equivalent channel at the first moment is used to characterize the channel state of the downlink equivalent channel at the first moment).
  • the feature vector of the downlink equivalent channel may include r feature vectors, that is, the feature vector of the downlink equivalent channel may be recorded as r is configured by the network device or r is the same as the number of data streams supported by the terminal device (ie RANK), r ⁇ 1.
  • the feature value corresponding to any one of the r feature vectors is greater than or equal to a feature value corresponding to any feature vector of the plurality of feature vectors corresponding to the downlink equivalent channel except the r feature directions.
  • the feature vector of the downlink equivalent channel may include at least one of the following two types:
  • a full bandwidth eigenvector of a downlink equivalent channel the full bandwidth eigenvector being used to characterize a channel state of a downlink equivalent channel of a full bandwidth
  • a local bandwidth feature vector of the downlink equivalent channel the local bandwidth feature vector being used to characterize the channel state of the downlink equivalent channel of the local bandwidth.
  • the terminal device may feed back the full bandwidth feature vector or the local bandwidth feature vector of the current downlink equivalent channel to the network device according to the feedback granularity, where the feedback granularity may include full bandwidth or local bandwidth (eg, subband).
  • the feedback granularity may include full bandwidth or local bandwidth (eg, subband).
  • the terminal device can determine the first local bandwidth feature vector corresponding to 0-10M and/or the second local bandwidth feature vector corresponding to 10-20M. And feedback the corresponding vector information.
  • the method 200 can also include:
  • the terminal device performs a dimension reduction on a channel matrix corresponding to the downlink reference signal received at the first time according to the dimension reduction matrix, and determines a feature of a downlink equivalent channel corresponding to the downlink reference signal received at the first moment. vector.
  • the first time is after the first time period, and the first time time may include the end time of the first time period.
  • the channel state of the downlink equivalent channel corresponding to the downlink reference signal received at the first time is used to represent the channel state of the downlink channel corresponding to the downlink reference signal received at the first time, and the downlink corresponding to the downlink reference signal received at the first time.
  • the feature vector of the equivalent channel is used to represent the channel state of the downlink equivalent channel corresponding to the downlink reference signal received at the first moment.
  • the terminal device can determine the feature direction of the downlink equivalent channel by using at least the following methods: the amount.
  • the terminal device calculates a feature vector of the downlink equivalent channel.
  • the terminal device may multiply the channel matrix corresponding to the current downlink reference signal and the dimension reduction matrix to obtain an equivalent matrix corresponding to the current downlink reference signal, that is,
  • the channel matrix corresponding to the downlink reference signal received by the terminal device each time includes at least one channel matrix.
  • the terminal device may perform at least one equivalent matrix in one-to-one correspondence by performing dimensionality reduction on the at least one channel matrix. For example, it is assumed that the terminal device performs channel estimation on the currently received downlink reference signal to obtain M channel matrices, and the terminal device performs dimensionality reduction on the M channel matrices to obtain M equivalent matrices.
  • the “equivalent matrix corresponding to the current downlink reference signal” may be referred to as “equivalent matrix group”.
  • the terminal device may obtain a feature vector of a downlink equivalent channel of the first frequency domain resource region by calculating a third covariance matrix corresponding to the first frequency domain resource region according to the equivalent matrix group.
  • the third covariance matrix is used to characterize the statistical characteristics of the downlink equivalent channel of the first frequency domain resource region.
  • the first frequency domain resource region includes full bandwidth or partial bandwidth.
  • the terminal device may obtain a third covariance matrix of the first frequency domain resource region by averaging the covariance matrices corresponding to the first frequency domain resource region.
  • the covariance matrix corresponding to the first frequency domain resource region includes a covariance matrix of an equivalent matrix corresponding to the downlink reference signal received at the first moment in the first frequency domain resource region.
  • the terminal device may calculate a covariance matrix of each equivalent matrix in the equivalent matrix group, and average all the covariance matrices to obtain A third covariance matrix of the full bandwidth downlink equivalent channel, the third covariance matrix being used to characterize the statistical characteristics of the full bandwidth downlink equivalent channel.
  • the terminal device can obtain the feature vector of the third covariance matrix by using various algorithms. For details, refer to the related description above, which is not described here for brevity.
  • the terminal device obtains 100 equivalent matrices, and then obtains 100 covariance matrices according to the 100 equivalent matrices.
  • the terminal device may average the 100 covariance matrices to obtain a third covariance matrix, and the terminal device may calculate a feature vector of the third covariance matrix (ie, a full bandwidth feature vector).
  • the feature vector information can be used to characterize the channel state of the downlink equivalent channel of the full bandwidth.
  • the terminal device obtains 100 covariance matrices, wherein 50 covariance matrices of the 100 covariance matrices correspond to The bandwidth of 0-10M, and the other 50 covariance matrices correspond to the bandwidth of 10-20M.
  • the terminal device may average the 50 covariance matrices corresponding to the 0-10M bandwidth to obtain a third covariance matrix corresponding to the 0-10M bandwidth, and calculate a feature vector of the third covariance matrix (ie, the first local bandwidth feature vector) ).
  • the terminal device may average the 50 covariance matrices corresponding to the 10-20M bandwidth to obtain a third covariance matrix corresponding to the 10-20M bandwidth, and calculate a feature vector of the third covariance matrix (ie, the second part).
  • Bandwidth feature vector the vector information may include a first local bandwidth feature vector and/or a second local bandwidth feature vector.
  • the terminal device may calculate the channel matrix according to the PAST algorithm and Lanczos.
  • the method and other algorithms determine the eigenvectors of the downlink equivalent channel.
  • the feature vector in the first method is calculated by the terminal device according to the equivalent matrix, so that the feature vector can better characterize the channel state of the downlink equivalent channel at the first moment.
  • the method 200 may further include: the terminal device acquiring the vector information by performing quantization on the element of the feature vector.
  • the terminal device sends the vector information through a data channel.
  • the terminal device determines a feature vector of a downlink equivalent channel from a preset set of feature vectors.
  • a set of feature vectors may be preset, and the terminal device and the network device both know the feature vector set, and the terminal device may perform dimension reduction on the channel matrix corresponding to the currently received downlink reference signal according to the dimension reduction matrix, and according to a certain The criterion determines a feature vector of the downlink equivalent channel from the set of feature vectors.
  • the feature vector is selected by the terminal device from the preset feature vector set, and the vector information includes an index of the feature vector in the vector set, which can reduce the feedback overhead of the terminal device feedback vector.
  • the feature vector set may include at least the following two situations:
  • the feature vector set includes a plurality of feature vectors, and the terminal device may select two feature vectors from the plurality of feature vectors, and feed back two indexes corresponding to the two feature vectors.
  • the feature vector set includes a plurality of feature matrices, each of the plurality of feature matrices includes two columns (each of the feature matrices can be regarded as one feature vector), and the terminal device can be from the plurality of A feature matrix is selected in the feature matrix, and the index of the feature matrix is fed back.
  • the terminal device can determine and feed back matrix information and vector information, and how the terminal device feeds back the matrix information and the vector information is described in detail below.
  • the terminal device may periodically determine the dimension reduction matrix and the feature vector.
  • the terminal device periodically determines the dimension reduction matrix and the feature vector, which can be understood as periodic feedback matrix information and vector information of the terminal device.
  • the network device periodically receives and updates the matrix information, and uses the updated matrix information to obtain channel state information at a corresponding time.
  • the duration corresponding to the first time period may be a period in which the terminal device feeds back the matrix information, and the terminal device may determine the channel matrix of the second time period according to the dimension reduction matrix determined by the downlink reference signal received in the first time period. Perform dimensionality reduction.
  • the duration of the second time period and the second time period are equal, and the second time period is the next time period of the first time period.
  • the terminal device may perform dimension reduction on the channel matrix received in the (i+1)th time period according to the dimension reduction matrix determined by the downlink reference signal received in the ith time period.
  • the network device recovers the vector information received in the (i+1)th time period according to the dimensionality reduction information received at the end time of the i-th time period to obtain a high-dimensional matrix, where i is a positive integer greater than 0.
  • the period of the terminal device feedback matrix information is longer than the period of the terminal device feedback vector information. That is, the terminal device can perform long-period and short-period feedback on the matrix information and the vector information, respectively.
  • the terminal device can reduce the dimensionality of the high-dimensional channel matrix with spatial sparsity to obtain a low-dimensional equivalent matrix.
  • the low-dimensional equivalent matrix is a concentrated representation of a high-dimensional channel matrix, and the terminal device can feed back related information of the equivalent matrix of the downlink channel, that is, vector information, in a short period, so that the network device can immediately understand the channel state and do Processing accordingly.
  • the feedback period of the vector information may be 5 milliseconds, 10 milliseconds, or the like.
  • the terminal device In order to enable the network device to acquire a high-dimensional channel matrix based on the vector information, the terminal device also needs to send the matrix information to the network device.
  • the dimensionality reduction matrix is a kind of statistical information obtained by the terminal device based on continuous estimation of the channel state. Without real-time feedback, the feedback cycle can be appropriately extended.
  • the feedback period of the matrix information may be 0.1 second to 1 second.
  • FIG. 3 is a schematic flowchart of another example of a method for feeding back channel state information according to an embodiment of the present invention.
  • the time domain resource may be divided into basic units in units of short periods (ie, periods of vector information), and each short period may include at least one Transmission Time Interval (TTI).
  • TTI Transmission Time Interval
  • the period in which the terminal device receives the downlink reference signal is 10 1 millisecond TTI (1 millisecond TTI is equal to one subframe, and 10 subframes are one radio frame), and the short period may include 10 TTIs, in each short period,
  • the terminal device feeds back the instantaneous downlink channel state to the network device. Multiple short periods make up a long period.
  • the terminal device In each long period, the terminal device continuously performs channel estimation (that is, acquires a channel matrix set), and obtains a dimensionality reduction matrix, and the feedback of the dimensionality reduction period is performed in a long period. In the last short period of each long period, the terminal device not only feeds back the dimensionality reduction matrix, but also feeds back the vector information.
  • the terminal device uses the dimensionality reduction matrix determined in the previous cycle to reduce the channel matrix corresponding to the downlink reference signal received in the current cycle, and accordingly, the network device receives the dimensionality reduction according to the previous cycle.
  • the matrix and the currently received vector information determine the precoding matrix. That is, the S110 can include:
  • the network device may determine the precoding matrix according to the matrix information and the vector information.
  • the network device acquires the accurate CSI in order to determine the precoding matrix.
  • the network device can obtain the dimension reduction matrix according to the matrix information.
  • determining the eigenvector of the downlink equivalent channel according to the vector information The network device can determine the precoding matrix according to P ⁇ V.
  • a high-dimensional matrix is obtained by the dimensionality reduction matrix and the eigenvectors of the downlink equivalent channel.
  • the precoding matrix can be the high dimensional matrix.
  • the network device may determine the dimension reduction matrix according to the index of the dimension reduction matrix and the preset dimension reduction matrix set. If the vector information includes an index of the feature vector, the network device may determine the feature vector according to the index of the feature vector and the preset feature vector set.
  • the network device If the matrix information includes the quantized elements obtained by quantizing the elements of the dimensionality reduction matrix, in other words, if the matrix information is obtained by the terminal device by performing quantization on the elements of the dimensionality reduction matrix, the network device first receives the matrix information Restore the dimensionality reduction matrix corresponding to the matrix information. Similarly, if the vector information includes the quantized elements obtained by quantizing the elements of the feature vector, the network device first recovers the feature vector corresponding to the vector information after receiving the vector information.
  • phase and the amplitude of the feature vector of the downlink equivalent channel are separately quantified as an example, and the quantization process of the terminal device and the recovery process of the network device according to the vector information recovery feature are briefly described.
  • V 1 can be expressed in the following form:
  • Quantifying the amplitude means quantifying
  • , i 1...P. Assuming that the number of quantization bits of the amplitude is M A , then the quantization process can be expressed as:
  • network devices can restore the amplitude and phase of each element Then the constituent eigenvectors Perform 2 norm normalization.
  • the corresponding recovery process can be expressed as:
  • the above-mentioned quantization process of the feature vector V 1 is only an example, and the embodiment of the present invention may be used to quantize the elements of the feature vector and/or the dimensionality reduction matrix in other manners.
  • the CSI is jointly characterized by the dimension reduction information and the vector information, which is beneficial for the network device to acquire the accurate CSI. Further, the dimensionality reduction information and the vector information are fed back in a long period and a short period, respectively, which is advantageous for reducing feedback overhead.
  • the method of the embodiment of the present invention can be well compromised in the accuracy of feedback CSI and the overhead of feedback CSI.
  • the terminal device can send the reduced-dimensional information and the vector information to the network device, so that the network device can obtain the CSI more accurately. Further, the terminal device can separately perform the dimension reduction information and the vector information. The cycle and short-cycle feedback help to reduce the overhead of feedback CSI.
  • the uplink and downlink channels of the FDD system and the uncalibrated TDD have no channel reciprocity, and therefore, the channel state of the current downlink channel or the channel state of the downlink channel at the adjacent time cannot be directly estimated according to the current uplink reference signal. But in fact, there is a certain correlation between the FDD system and the uncalibrated TDD (over a period of time).
  • the CSI is jointly characterized by the dimensionality reduction matrix and the feature vector. Since the uplink and downlink channels of the FDD system and the uncalibrated TDD have no channel reciprocity, the terminal device needs to send the vector information of the feature vector to the network device.
  • the network device device may send the downlink reference signal based on the dimensionality reduction matrix, so that the terminal device does not need to feed back the matrix information of the dimensionality reduction matrix.
  • the method will be described in detail.
  • FIG. 4 is a schematic flow chart of still another example of a method for feeding back channel state information according to an embodiment of the present invention.
  • the method 300 can include:
  • the network device sends a downlink reference signal according to the dimension reduction matrix.
  • the terminal device receives the downlink reference signal that is sent by the network device according to the dimension reduction matrix.
  • the first dimension of the dimensionality reduction matrix is the same as the number of the transmit antenna ports of the network device, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix.
  • a precoding matrix for transmitting a downlink reference signal is If the precoding matrix A is used to send the downlink reference signal, the channel matrix obtained by the terminal device is The channel matrix H is a high dimensional channel matrix. Dimension reduction matrix Sending a downlink reference signal, and the channel matrix acquired by the terminal device is That is, the channel estimation result obtained by the terminal device estimating the downlink reference signal is a matrix that has undergone dimensionality reduction.
  • the network device can be a virtual antenna mapping method of mapping N S using downlink reference signal port to port N T transmit antennas, wherein, the mapping matrix is a transposed matrix of dimension reduction.
  • the terminal device sends an uplink reference signal to the network device, and correspondingly, the network device receives the uplink reference signal sent by the terminal device.
  • the network device determines the dimension reduction matrix according to a channel matrix corresponding to the uplink reference signal received in the first time period.
  • the network device may determine a dimension reduction matrix of the downlink channel according to a channel matrix corresponding to the uplink reference signal received by the network device in the first time period.
  • the dimensionality reduction matrix can reduce the channel matrix of the downlink channel.
  • the “channel matrix corresponding to the uplink reference signal received by the network device in the first time period” may be referred to as “channel matrix set”.
  • the network device can determine the dimensionality reduction matrix based on the set of channel matrices.
  • the terminal device sends vector information of a feature vector of a downlink equivalent channel to the network device according to a channel matrix corresponding to the downlink reference signal.
  • the network device receives the vector information.
  • the channel matrix corresponding to the downlink reference signal is a channel matrix with a reduced dimension (ie, an equivalent matrix corresponding to the downlink reference signal above).
  • the method can also include:
  • the terminal device determines a feature vector of a downlink equivalent channel according to a channel matrix corresponding to the downlink reference signal.
  • the network device determines the precoding matrix according to the dimension reduction matrix and the vector information.
  • the network device determines that the period of the dimension reduction matrix is longer than the period in which the network device receives the vector information. For example, the network device determines that the period of the dimensionality reduction matrix is 0.1 second to 1 second, and the period during which the network device receives the vector information is 5 milliseconds to 10 milliseconds.
  • the period in which the dimensionality reduction matrix is determined may be recorded as the first period, and the period in which the vector information is received may be recorded as the second period.
  • the dimension reduction matrix determined by the network device in the ith first period may be used to characterize the CSI together with the vector information received in the (i+1)th first period.
  • the network device determines the dimensionality reduction matrix at time T.
  • the “dimensionality reduction matrix determined by the T time” may be referred to as “the first dimensionality reduction matrix”.
  • the first dimensionality reduction matrix may be used to represent the CSI of the corresponding time with the received vector information of 0.1 seconds after the T time, and the first dimensionality reduction matrix may also be used to represent the corresponding time with the received vector information of 0.2 seconds after the T time. CSI.
  • the network device sends a downlink reference signal according to the dimension reduction matrix, and the terminal device estimates the downlink reference signal, and the obtained channel matrix is substantially an equivalent matrix.
  • the terminal device does not need to perform dimension reduction on the channel matrix corresponding to the downlink reference signal, and the terminal device does not need to feed back the matrix information to the network device.
  • the dimensionality reduction matrix and the feature vector collectively characterize the CSI, and the steps and operations performed in the method 200 and the method 300 have similarities, and the related description in the method 300 can be referred to the related description in the method 200.
  • a detailed description of S301 can be referred to the related description of S202.
  • I will not repeat them here
  • FIG. 5 is a schematic block diagram of an example of a terminal device according to an embodiment of the present invention. It should be understood that the terminal device 400 illustrated in FIG. 5 is only an example, and the terminal device 400 of the embodiment of the present invention may further include other modules or units, or include modules similar to those of the modules in FIG. 5, or are not to be included. All the modules in Figure 5.
  • the terminal device 400 includes:
  • a sending unit 410 configured to: send, to the network device, matrix information of a dimensionality reduction matrix, where a first dimension of the dimensionality reduction matrix is the same as a number of transmitting antenna ports of the network device, and the dimension reduction is performed.
  • Matrix The second dimension is smaller than the first dimension of the dimensionality reduction matrix; the vector information of the feature vector of the downlink equivalent channel is sent to the network device, and the feature vector of the downlink equivalent channel is obtained based on the dimensionality reduction matrix;
  • the matrix information includes a matrix index of the dimensionality reduction matrix, or the matrix information includes information obtained by the terminal device by quantizing elements of the dimensionality reduction matrix; the vector information includes an index of the feature vector Or, the vector information includes information obtained by the terminal device by quantizing elements of the feature vector.
  • the sending unit 410 is specifically configured to: send the matrix information to the network device by using an uplink data channel; and/or send the vector information to the network device by using an uplink data channel.
  • the dimension reduction matrix is determined by the terminal device 400 according to a channel matrix corresponding to the downlink reference signal received in the first time period, where the dimension reduction matrix corresponds to the child in the first time period.
  • the energy of the space is the highest energy among the plurality of subspaces corresponding to the downlink channel in the same dimension, and the orthogonality is satisfied between the column vectors of the dimensionality reduction matrix.
  • the terminal device 400 further includes: a first processing unit, configured to determine the dimensionality reduction matrix according to a channel matrix corresponding to the downlink reference signal received in the first time period.
  • the first processing unit is configured to: calculate, according to the channel matrix corresponding to the downlink reference signal received in the first time period, a first covariance matrix, where the first channel covariance matrix is used for characterization a statistical characteristic of the downlink channel corresponding to the first time period; and calculating the dimensionality reduction matrix according to the first covariance matrix.
  • the first processing unit is specifically configured to: calculate a covariance matrix of each channel matrix in a channel matrix corresponding to the downlink reference signal received by the terminal device 400 in the first time period; A plurality of second covariance matrices are obtained by averaging the covariance matrices corresponding to the downlink reference signals, and the plurality of second covariance matrices are in one-to-one correspondence with the plurality of times included in the first time period; The second covariance matrix performs averaging or temporal filtering to obtain the first covariance matrix.
  • the first processing unit is configured to: determine, according to the channel matrix corresponding to the downlink reference signal received in the first time period, the dimension reduction matrix from a preset set of dimensionality reduction matrices,
  • the matrix information of the dimensionality reduction matrix includes an index of the dimensionality reduction matrix in the preset dimensionality reduction matrix set.
  • each column of the dimensionality reduction matrix has the same beam pattern.
  • the terminal device 400 further includes: a second processing unit, configured to determine, according to the dimension reduction matrix, the first time by performing dimensionality reduction on a channel matrix corresponding to the downlink reference signal received at the first time A feature vector of a downlink equivalent channel corresponding to the received downlink reference signal.
  • a second processing unit configured to determine, according to the dimension reduction matrix, the first time by performing dimensionality reduction on a channel matrix corresponding to the downlink reference signal received at the first time A feature vector of a downlink equivalent channel corresponding to the received downlink reference signal.
  • the second processing unit is configured to: according to the dimension reduction matrix, perform channel reduction on a channel matrix corresponding to the received downlink reference signal at the first time, to obtain the first time received And an equivalent matrix corresponding to the downlink reference signal; calculating a covariance matrix of each equivalent matrix in the equivalent matrix corresponding to the downlink reference signal received at the first moment; performing the covariance matrix corresponding to the first frequency domain resource region And averaging, the third covariance matrix corresponding to the first resource region is obtained, where the covariance matrix corresponding to the first frequency domain resource region is received at the first time in the first frequency domain resource region a covariance matrix of an equivalent matrix corresponding to the downlink reference signal; determining, according to the third covariance matrix, a feature vector of the downlink equivalent channel in the first frequency domain resource region, the first frequency domain resource
  • the area includes full bandwidth or local bandwidth.
  • the feature vector of the downlink equivalent channel includes r feature vectors, where r is configured by the network device or r is the same as the number of data streams supported by the terminal device 400, the r feature vectors The feature value corresponding to any one of the feature vectors is greater than or equal to the feature value of the feature vector of the downlink equivalent channel except for any one of the r feature directions, r ⁇ 1.
  • the period in which the sending unit 410 sends the matrix information is longer than the period in which the sending unit 410 sends the vector information.
  • FIG. 6 is a schematic block diagram of an example of a network device according to an embodiment of the present invention. It should be understood that the network device 400 illustrated in FIG. 6 is merely an example, and the network device 500 of the embodiment of the present invention may further include other modules or units, or include units similar to those of the modules in FIG. 6, or are not to be included. All the cells in Figure 6.
  • the network device 500 includes: a receiving unit 510, configured to: receive matrix information of a dimensionality reduction matrix sent by a terminal device, a first dimension of the dimensionality reduction matrix, and the network device The number of the transmit antenna ports of the 500 is the same, and the second dimension of the dimensionality reduction matrix is smaller than the first dimension of the dimensionality reduction matrix; and the vector information of the feature vector of the downlink equivalent channel transmitted by the terminal device is received; 520, configured to determine a precoding matrix according to the matrix information and the vector information, where the matrix information includes a matrix index of the dimensionality reduction matrix, or the matrix information includes the terminal device Information obtained by quantizing an element of the dimensionality reduction matrix; the vector information includes an index of the feature vector, or the vector information includes information obtained by the terminal device by quantizing an element of the feature vector
  • the receiving unit 510 is specifically configured to: receive matrix information sent by the terminal device by using an uplink data channel; and/or receive the vector information sent by the network device 500 by using an uplink data channel.
  • the receiving unit 510 receives the matrix information for a period longer than the receiving unit 510 receives the vector information.
  • FIG. 7 is a schematic block diagram of another example of a terminal device according to an embodiment of the present invention. It should be understood that the terminal device 600 illustrated in FIG. 7 is only an example, and the terminal device 600 of the embodiment of the present invention may further include other units, or include units similar to those of the respective modules in FIG. 7, or not including FIG. 7. All the units in .
  • the terminal device 600 includes: a receiving unit 610, configured to: receive a downlink reference signal sent by a network device according to a dimensionality reduction matrix, a first dimension of the dimensionality reduction matrix, and the network The number of the transmit antenna ports of the device is the same, and the second dimension of the dimension reduction matrix is smaller than the first dimension of the dimension reduction matrix.
  • the sending unit 620 is configured to use the channel corresponding to the downlink reference signal received by the receiving unit 610. a matrix that transmits vector information of a feature vector of a downlink equivalent channel to the network device.
  • the terminal device 600 further includes: a processing unit, configured to: calculate a feature vector of the downlink equivalent channel according to a channel matrix corresponding to the downlink reference signal; by using the feature vector Quantization is performed to obtain the vector information.
  • a processing unit configured to: calculate a feature vector of the downlink equivalent channel according to a channel matrix corresponding to the downlink reference signal; by using the feature vector Quantization is performed to obtain the vector information.
  • the sending unit 620 is specifically configured to: send the vector information to the network device by using an uplink data channel.
  • the processing unit is specifically configured to: calculate a covariance matrix of each channel matrix in the channel matrix corresponding to the downlink reference signal; average the covariance matrix corresponding to the first frequency domain resource region, and obtain a third a covariance matrix, where the covariance matrix corresponding to the first frequency domain resource region includes a covariance matrix of a channel matrix corresponding to the downlink reference signal in the first frequency domain resource region, the first frequency domain
  • the resource region includes a full bandwidth or a local bandwidth; determining, according to the third covariance matrix, a feature vector of the downlink equivalent channel in the first frequency domain resource region, where the first frequency domain resource region includes full bandwidth Or local bandwidth.
  • the feature vector of the downlink equivalent channel includes r feature vectors, where r is configured by the network device or r is the same as the number of data streams supported by the terminal device, where the r feature vectors are The feature value corresponding to any one of the feature vectors is greater than or equal to the feature value of the feature vector of the downlink equivalent channel except for any one of the r feature directions, r ⁇ 1.
  • FIG. 8 is a schematic block diagram of another example of a network device according to an embodiment of the present invention. It should be understood that the network device 700 illustrated in FIG. 8 is only an example, and the network device 700 of the embodiment of the present invention may further include other units or modules, or include units similar to those of the modules in FIG. 8, or are not to be included. All the cells in Figure 5.
  • the network device 700 includes:
  • the sending unit 710 is configured to send, according to the dimensionality reduction matrix, a downlink reference signal, where a first dimension of the dimensionality reduction matrix is the same as a number of transmit antenna ports of the network device 700, and a second dimension of the dimensionality reduction matrix is smaller than a receiving unit 720, configured to receive vector information of a feature vector of a downlink equivalent channel sent by the terminal device according to the downlink reference signal, and a processing unit 730, configured to perform, according to the dimension reduction The matrix and the vector information determine a precoding matrix.
  • the processing unit 730 is further configured to: determine the dimensionality reduction matrix according to a channel matrix corresponding to the uplink reference signal received in the first time period.
  • the processing unit 730 is specifically configured to: calculate, according to the channel matrix corresponding to the uplink reference signal received in the first time period, a first covariance matrix, where the first channel covariance matrix is used to represent the a statistical characteristic of the uplink channel corresponding to the first time period; and calculating the dimensionality reduction matrix according to the first covariance matrix.
  • the processing unit 730 is specifically configured to: calculate a covariance matrix of each channel matrix in a channel matrix corresponding to the downlink reference signal received by the terminal device in the first time period; and use an uplink reference received at the same time
  • a covariance matrix corresponding to the signal is averaged to obtain a plurality of second covariance matrices, wherein the plurality of second covariance matrices are in one-to-one correspondence with the plurality of times included in the first time period;
  • the covariance matrix performs averaging or temporal filtering to obtain the first covariance matrix.
  • the processing unit 730 determines that the period of the dimensionality reduction matrix is longer than the period in which the receiving unit 720 receives the vector information.
  • the terminal device 800 may include: a transceiver 810 and a processor 820.
  • the processor is connected to the transceiver.
  • the device further includes a memory, where the memory may be integrated in the processor, or may be independent.
  • the memory can be used to store instructions for executing instructions stored in the memory to control transceivers to transmit information or signals, and the processor, the memory and the transceiver can communicate with each other through an internal connection path, and transfer control and/or Or data signal.
  • the processing unit in the terminal device 400 shown in FIG. 5 may correspond to the processor 820, and the terminal shown in FIG.
  • the transmitting unit and/or the receiving unit in the end device can correspond to the transceiver.
  • the network device 900 may include: a transceiver 910 and a processor 920.
  • the processor is connected to the transceiver.
  • the device further includes a memory, where the memory may be integrated in the processor, or may be independent.
  • the memory can be used to store instructions for executing instructions stored in the memory to control transceivers to transmit information or signals, and the processor, the memory and the transceiver can communicate with each other through an internal connection path, and transfer control and/or Or data signal.
  • the processing unit in the network device 500 shown in FIG. 6 may correspond to the processor 920.
  • the sending unit and/or the receiving unit of the network device 500 shown in FIG. 6 may correspond to the transceiver 910.
  • FIG. 11 is a schematic block diagram of still another example of a terminal device according to an embodiment of the present invention.
  • the terminal device 1000 may correspond to (for example, may be configured or be itself) the terminal device described in the foregoing method 300, and each module or unit in the terminal device 1000 is used to perform the execution of the terminal device in the method 300 described above. In the respective operations or processes, detailed descriptions thereof will be omitted herein to avoid redundancy.
  • the terminal device 1000 may include: a transceiver 1010 and a processor 1020.
  • the processor is connected to the transceiver.
  • the device further includes a memory, where the memory may be integrated in the processor, or may be independent.
  • the memory can be used to store instructions for executing instructions stored in the memory to control transceivers to transmit information or signals, and the processor, the memory and the transceiver can communicate with each other through an internal connection path, and transfer control and/or Or data signal.
  • the processing unit in the terminal device shown in FIG. 7 may correspond to the processor 1020, and the sending unit and/or the receiving unit in the terminal device shown in FIG. 7 may correspond to the transceiver 1010.
  • FIG. 12 is a schematic block diagram of still another example of a network device according to an embodiment of the present invention.
  • the network device 1100 can correspond to (for example, can be configured on or in itself) the network device described in the foregoing method 300, and each module or unit in the network device 1100 is used to perform the network device in the method 300 described above. In the respective operations or processes, detailed descriptions thereof will be omitted herein to avoid redundancy.
  • the network device 1100 can include a transceiver 1110 and a processor 1120.
  • the processor is coupled to the transceiver.
  • the device further includes a memory, which can be integrated in the processor or independently of the processor.
  • the memory can be used to store instructions for executing instructions stored in the memory to control transceivers to transmit information or signals, and the processor, the memory and the transceiver can communicate with each other through an internal connection path, and transfer control and/or Or data signal.
  • the processing unit in the network device 700 shown in FIG. 8 may correspond to the processor 1120.
  • the sending unit and/or the receiving unit of the network device 700 shown in FIG. 8 may correspond to the transceiver 1110.
  • the processor may be an integrated circuit chip with signal processing capabilities.
  • each step of the foregoing method embodiment may be completed by an integrated logic circuit of hardware in a processor or an instruction in a form of software.
  • the processor may be a general-purpose processor, a digital signal processor (DSP), an application specific integrated circuit (ASIC), a Field Programmable Gate Array (FPGA), or the like. Programming logic device, discrete gate or transistor logic Pieces, discrete hardware components.
  • DSP digital signal processor
  • ASIC application specific integrated circuit
  • FPGA Field Programmable Gate Array
  • the memory in the embodiments of the present invention may be a volatile memory or a non-volatile memory, or may include both volatile and non-volatile memory.
  • the non-volatile memory may be a read-only memory (ROM), a programmable read only memory (PROM), an erasable programmable read only memory (Erasable PROM, EPROM), or an electric Erase programmable read only memory (EEPROM) or flash memory.
  • the volatile memory can be a Random Access Memory (RAM) that acts as an external cache.
  • RAM Random Access Memory
  • many forms of RAM are available, such as static random access memory (SRAM), dynamic random access memory (DRAM), synchronous dynamic random access memory (Synchronous DRAM).
  • SDRAM Double Data Rate SDRAM
  • DDR SDRAM Double Data Rate SDRAM
  • ESDRAM Enhanced Synchronous Dynamic Random Access Memory
  • SLDRAM Synchronous Connection Dynamic Random Access Memory
  • DR RAM direct memory bus random access memory
  • the size of the serial numbers of the above processes does not mean the order of execution, and the order of execution of each process should be determined by its function and internal logic, and should not be taken to the embodiments of the present invention.
  • the implementation process constitutes any limitation.
  • the disclosed systems, devices, and methods may be implemented in other manners.
  • the device embodiments described above are merely illustrative.
  • the division of the unit is only a logical function division.
  • there may be another division manner for example, multiple units or components may be combined or Can be integrated into another system, or some features can be ignored or not executed.
  • the mutual coupling or direct coupling or communication connection shown or discussed may be an indirect coupling or communication connection through some interface, device or unit, and may be in an electrical, mechanical or other form.
  • the unit described as a separate component may or may not be physically separated as a unit display
  • the components may or may not be physical units, ie may be located in one place, or may be distributed over multiple network elements. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of the embodiment.
  • each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit.
  • the functions may be stored in a computer readable storage medium if implemented in the form of a software functional unit and sold or used as a standalone product.
  • the technical solution of the present application which is essential or contributes to the prior art, or a part of the technical solution, may be embodied in the form of a software product, which is stored in a storage medium, including
  • the instructions are used to cause a computer device (which may be a personal computer, server, or network device, etc.) to perform all or part of the steps of the methods described in various embodiments of the present application.
  • the foregoing storage medium includes: a U disk, a mobile hard disk, a read-only memory (ROM), a random access memory (RAM), a magnetic disk, or an optical disk, and the like. .

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Abstract

本发明实施例用于反馈信道状态信息的方法、终端设备和网络设备，有利于网络设备获取高精度的CSI。该方法包括：终端设备向网络设备发送降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；所述终端设备向所述网络设备发送下行等效信道的特征向量的向量信息，所述下行等效信道的特征向量基于所述降维矩阵得到；其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息，所述向量信息包括所述特征向量的向量索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。

Description

用于反馈信道状态信息的方法、终端设备和网络设备 技术领域
本发明实施例涉及无线通信领域，并且更具体地，涉及用于反馈信道状态信息的方法、终端设备和网络设备。
背景技术
大规模多输入多输出(Massive Multiple-Input Multiple-Output，简称“Massive MIMO”)是业界公认的5G(the 5th Generation mobile communication，第五代移动通信)关键技术。Massive MIMO技术对系统容量的提升源自于其对大量空间自由度的利用，从而进行多用户空分复用获取增益。要较好地收获空分复用的增益，网络设备需要获取精确地信道状态信息(Channel State Information，CSI)。
目前，网络设备获取CSI方法包括：网络设备向终端设备发送信道状态信息参考信号(Channel State Information-Reference signal，CSI-RS)，终端设备根据网络设备发送的CSI-RS进行信道估计，根据估计结果从存储的码本中选出一个预编码矩阵。并将选出的预编码矩阵在码本中的索引通过上行信道反馈到网络设备，该索引记为预编码矩阵索引(Precoding Matrix Indicator，简称为PMI)。其中，终端设备选择的预编码矩阵用于表征CSI。
这种机制会限制预编码矩阵所表征的CSI的精度，不利于网络设备获取精确地CSI。
发明内容
本发明实施例提供一种用于反馈信道状态信息的方法、终端设备和网络设备，有利于网络设备获取精确地CSI。
第一方面，提供一种用于反馈信道状态信息的方法，所述方法包括：终端设备向网络设备发送降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；所述终端设备向所述网络设备发送下行等效信道的特征向量的向量信息，所述下行等效信道的特征向量基于所述降维矩阵得到；其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
与现有技术中使用从码本中确定的预编码矩阵表征CSI相比，本发明实施例的方法不受限于码本技术，通过降维矩阵以及特征向量共同表征CSI，有利于精确地表征CSI，以使网络设备获取精确地CSI。
可选地，在第一方面可能的实现方式中，第一维度为行维度，第二维度为列维度。
可选地，在第一方面可能的实现方式中，降维矩阵用于对网络设备的信道矩阵中网络设备的发送天线端口所在的维度进行降维。
可选地，在第一方面可能的实现方式中，降维矩阵用于对下行参考信号对应的信道矩阵进行降维。
可选地，在第一方面可能的实现方式中，降维矩阵用于对第二时间段接收的下行参 考信号对应的信道矩阵进行降维。
可选地，在第一方面可能的实现方式中，所述下行等效信道的特征向量用于表征下行等效信道的信道状态，所述降维矩阵以及所述下行等效信道的特征向量用于表征下行信道的信道状态。
在第一方面可能的实现方式中，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道发送的。
若降维矩阵是由终端设备根据下行信道的实际情况计算得到的，该降维信息占用的比特数会较多，更适用于通过上行数据信道进行传输。同理，若特征向量是由终端设备根据下行信道的实际情况计算得到的，该向量信息更适用于通过上行数据信道进行传输。根据矩阵信息以及向量信息的实际情况选择匹配的传输信道，有利于终端设备向网络设备发送矩阵信息以及向量信息。
在第一方面可能的实现方式中，所述降维矩阵是由所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵确定的，在所述第一时间段中所述降维矩阵对应的子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，所述降维矩阵的各列向量之间满足正交性。
在第一时间段中，下行信道的能量主要集中在降维矩阵对应的子空间中，采用该降维矩阵进行降维能够使下行等效信道的信道状态更精确的表征下行信道的信道状态，以提高反馈CSI的精度。
在第一方面可能的实现方式中，所述方法还包括：终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵。
终端设备可以根据时间段内下行信道的统计特性，确定降维矩阵，以使降维矩阵可以低损耗地对信道矩阵进行降维。
在第一方面可能的实现方式中，所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵，包括：所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的下行信道的统计特性；所述终端设备根据所述第一协方差矩阵，计算所述降维矩阵。
第一信道协方差矩阵能够表征一个时间段对应的下行信道的统计特性，以使终端设备确定的降维矩阵能够用于对某个时间段对应的信道矩阵进行降维，即，终端设备无需频繁确定降维矩阵，与之相对地，终端设备无需频繁发送该降维矩阵，从而有利于降低反馈CSI的开销。
在第一方面可能的实现方式中，所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，包括：所述终端设备计算所述终端设备在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；所述终端设备通过对相同时刻接收的下行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；所述终端设备对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
采用该方法得到的第一协方差矩阵能够更精确的表征第一时间段对应的下行信道的统计特性，从而有利于终端设备确定降维矩阵。
可选地，第二协方差矩阵用于表征对应时刻的下行信道的统计特性。
在第一方面可能的实现方式中，终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定下行信道的降维矩阵，包括：所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，从预设的降维矩阵集合中确定所述降维矩阵，所述降维矩阵的矩阵信息包括所述降维矩阵在所述预设的降维矩阵集合的索引。
该降维矩阵是终端设备从预设的降维矩阵集合中选择的，该矩阵信息包括索引，该方案有利于降低反馈开销。进一步地，该方案可以降低终端设备确定降维矩阵的复杂度，有利于终端设备反馈矩阵信息。
在第一方面可能的实现方式中，所述降维矩阵的每一列对应的波束方向图相同。
由于降维矩阵的每一列对应的波束方向图相同，每个波束上接收信道的能量差不多，在后续传输低维的下行等效信道的向量信息时，有利于降低反馈CSI的开销。
在第一方面可能的实现方式中，所述方法还包括：所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量。
特征向量是终端设备结合下行信道的实际情况计算得来的，以使该特征向量能够更精确地表征下行等效信道的信道状态，有利于网络设备获取精确地下行信道状态。
可选地，在第一方面可能的实现方式中，所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定下行等效信道的特征向量，包括：所述终端设备根据所述降维矩阵，通过对第二时间段的第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻的下行信道的特征向量，第二时间段位于第一时间段之后。
终端设备确定的降维矩阵可以用于对第二时间段的信道矩阵进行降维，也就是说，终端设备确定的降维矩阵可以用于对一个时间段内终端设备接收到的多次下行参考信号对应的信道矩阵进行降维，即，终端设备无需频繁确定降维矩阵。有利于降低反馈CSI的开销。
在第一方面可能的实现方式中，所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量，包括：所述终端设备根据所述降维矩阵，通过对所述第一时刻的接收的下行参考信号对应的信道矩阵进行降维，得到所述第一时刻接收的下行参考信号对应的等效矩阵；所述终端设备计算所述第一时刻接收的下行参考信号对应的等效矩阵中每个等效矩阵的协方差矩阵；所述终端设备通过对第一频域资源区域对应的协方差矩阵进行平均，得到所述第一资源区域对应的第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述第一时刻接收的下行参考信号对应的等效矩阵的协方差矩阵；所述终端设备根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
在第一方面可能的实现方式中，该向量信息可以用于表征全带宽的下行等效信道的信道状态，也可以用于表征局部带宽的下行等效信道的信道状态，该方案灵活性高，有利于网络设备充分的了解下行等效信道的信道状态，进而充分的了解下行信道的信道状态，有利于网络设备较好的收获空分复用的增益。
可选地，在第一方面可能的实现方式中，所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定下行等效信道的特征向量，包括：所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，从预设的特征向量集合中确定所述下行等效信道的特征向量，所述向量信息包括所述特征向量的在所述预设的特征向量集合的索引。
该下行等效信道的特征向量是终端设备从预设的特征向量集合中选择的，该向量信息包括索引，该方案有利于降低反馈开销。进一步地，该方案可以降低终端设备确定下行等效信道的特征向量的复杂度，有利于终端设备反馈向量信息。
在第一方面可能的实现方式中，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
终端设备无需向网络设备反馈下行等效信道所有的特征向量，既可以降低反馈开销又可以使网络设备获取精确地CSI。进一步地，该r个特征向量对应的特征值较大，以使该r个特征向量能够精确地表征下行等效信道的信道状态。
在第一方面可能的实现方式中，所述终端设备发送所述矩阵信息的周期长于所述终端设备发送所述向量信息的周期。
根据降维信息和向量信息的不同特性，将该两个信息分别按照长周期短周期进行反馈，既可以降低反馈开销又可以使网络设备获取精确地CSI。
可选地，终端设备发送矩阵信息的周期为0.1-1秒；和/或终端设备发送向量信息的周期为5-10毫秒。
第二方面，提供一种用于反馈信道状态信息的方法，所述方法包括：网络设备接收终端设备发送的降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；所述网络设备接收所述终端设备发送的下行等效信道的特征向量的向量信息；所述终端设备根据所述矩阵信息和所述向量信息，确定预编码矩阵；其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
与现有技术中使用从码本中确定的预编码矩阵表征CSI相比，本发明实施例方法通过降维矩阵(矩阵信息)以及特征向量(向量信息)，共同表征CSI，有利于使网络设备获取精确地CSI。所述矩阵信息和向量信息中至少一个信息不是按照一定规则从码本中选择的(若从码本中选择，无需对元素进行量化)，有利于终端设备根据下行信道的实际信道状态得到匹配的降维矩阵和/或特征向量，以使该矩阵信息以及向量信息可以用于精确地表征CSI。
在第二方面可能的实现方式中，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道发送的。
若降维矩阵是由终端设备根据下行信道的实际情况计算得到的，该降维信息占用的比特数会较多，更适用于通过上行数据信道进行传输。同理，若特征向量是由终端设备根据下行信道的实际情况计算得到的，该向量信息占用的比特数会较多，更适用于通过 上行数据信道进行传输。根据矩阵信息以及向量信息的实际情况选择适宜的传输信道，有利于网络设备获取矩阵信息以及向量信息。
在第二方面可能的实现方式中，所述网络设备接收所述矩阵信息的周期长于所述网络设备接收所述向量信息的周期。
根据降维信息和向量信息的不同特性，网络设备分别按照长周期短周期接收降维信息和向量信息，既可以节省传输资源又可以使网络设备获取精确地CSI。
第三方面，提供一种用于反馈信道状态信息的方法，所述方法包括：终端设备接收网络设备根据降维矩阵发送的下行参考信号，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；所述终端设备根据所述下行参考信号对应的信道矩阵，向所述网络设备发送下行等效信道的特征向量的向量信息。
该降维矩阵由网络设备确定，无需终端设备周期性地上报降维矩阵，有利于降低反馈CSI的开销。
在第三方面可能的实现方式中，所述方法还包括：所述终端设备根据所述下行参考信号对应的信道矩阵，计算所述下行等效信道的特征向量；所述终端设备通过对所述特征向量进行量化得到所述向量信息。
终端设备可以根据实际的信道情况计算得到特征向量，该特征向量能够精准地表征下行等效信道的信道状态，有利于提高CSI反馈精度，进一步地，该方案可以在反馈CSI的精度以及反馈CSI的开销上做很好的折中。
在第三方面可能的实现方式中，所述终端设备向所述网络设备发送所述特征向量的向量信息，包括：所述终端设备通过上行数据信道向所述网络设备发送所述向量信息。
若特征向量是由终端设备根据下行信道的实际情况计算得到的，该向量信息占用的比特数会较多，更适用于通过上行数据信道进行传输。根据向量信息的实际情况选择匹配的传输信道，有利于终端设备向网络设备发送向量信息。
在第三方面可能的实现方式中，所述方法还包括：所述终端设备计算所述下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；所述终端设备对第一频域资源区域对应的协方差矩阵进行平均，得到第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述下行参考信号对应的信道矩阵的协方差矩阵，所述第一频域资源区域包括全带宽或局部带宽；所述终端设备根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
该向量信息可以用于表征全带宽的下行等效信道的信道状态，也可以用于表征局部带宽的下行等效信道的信道状态，该方案灵活性高，有利于网络设备充分的了解下行等效信道的信道状态，进而充分的了解下行信道的信道状态，有利于网络设备较好的收获空分复用的增益。
在第三方面可能的实现方式中，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
第四方面，提供一种用于反馈信道状态信息的方法，所述方法包括：网络设备根据 降维矩阵发送下行参考信号，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；所述网络设备接收所述终端设备根据所述下行参考信号发送的下行等效信道的特征向量的向量信息；所述网络设备根据所述降维矩阵和所述向量信息确定预编码矩阵。
在第四方面可能的实现方式中，所述网络设备接收所述终端设备根据所述下行参考信号发送的下行等效信道的特征向量的向量信息，包括：所述网络设备通过上行数据信道接收所述向量信息。
在第四方面可能的实现方式中，所述方法还包括：所述网络设备根据所述在第一时间段接收的上行参考信号对应的信道矩阵，确定所述降维矩阵。
在第四方面可能的实现方式中，所述网络设备根据所述在第一时间段接收的上行参考信号对应的信道矩阵，确定所述降维矩阵，包括：所述网络设备根据所述在第一时间段接收的上行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的所述上行信道的统计特性；所述终端设备根据所述第一协方差矩阵，计算所述降维矩阵。
在第四方面可能的实现方式中，所述网络设备根据所述在第一时间段接收的上行参考信号对应的信道矩阵，计算第一协方差矩阵，包括：所述终端设备计算所述终端设备在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；所述网络设备通过对相同时刻接收的上行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；所述网络设备对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
在第四方面可能的实现方式中，所述网络设备确定所述降维矩阵的周期长于所述网络设备接收所述向量信息的周期。
第五方面，提供了一种终端设备，用于执行第一方面及第一方面的任意可能的实现方式中的方法。具体地，该终端设备可以包括用于执行第一方面及第一方面的任意可能的实现方式中的方法的单元。
第六方面，提供了一种网络设备，用于执行第二方面及第二方面的任意可能的实现方式中的方法。具体地，该网络设备可以包括用于执行第二方面及第二方面的任意可能的实现方式中的方法的单元。
第七方面，提供了一种终端设备，用于执行第三方面及第三方面的任意可能的实现方式中的方法。具体地，该终端设备可以包括用于执行第三方面及第三方面的任意可能的实现方式中的方法的单元。
第八方面，提供了一种网络设备，用于执行第四方面及第四方面的任意可能的实现方式中的方法。具体地，该网络设备可以包括用于执行第四方面及第四方面的任意可能的实现方式中的方法的单元。
第九方面，提供了一种终端设备，包括存储器和处理器，该存储器用于存储计算机程序，该处理器用于从存储器中调用并运行该计算机程序，使得所述终端设备执行上述第一方面及第一方面的任意可能的实现方式中的方法。
第十方面，提供了一种网络设备，包括存储器和处理器，该存储器用于存储计算机程序，该处理器用于从存储器中调用并运行该计算机程序，使得所述网络设备执行第二 方面及第二方面的任意可能的实现方式中的方法的单元。
第十一方面，提供了一种终端设备，包括存储器和处理器，该存储器用于存储计算机程序，该处理器用于从存储器中调用并运行该计算机程序，使得所述终端设备执行上述第三方面及第三方面的任意可能的实现方式中的方法。
第十二方面，提供了一种网络设备，包括存储器和处理器，该存储器用于存储计算机程序，该处理器用于从存储器中调用并运行该计算机程序，使得所述网络设备执行第四方面及第四方面的任意可能的实现方式中的方法的单元。
第十三方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机程序代码被第一方面中的终端设备的处理单元、收发单元或处理器、收发器运行时，使得所述终端设备执行第一方面及第一方面的任意可能的实现方式中的方法。
第十四方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机代码被第二方面中的网络设备的处理单元、收发单元或处理器、收发器运行时，使得所述网络设备执行第二方面及第二方面的任意可能的实现方式中的方法。
第十五方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机程序代码被第三方面中的终端设备的处理单元、收发单元或处理器、收发器运行时，使得所述终端设备执行第三方面及第三方面的任意可能的实现方式中的方法。
第十六方面，提供了一种计算机程序产品，所述计算机程序产品包括：计算机程序代码，当所述计算机代码被第四方面中的网络设备的处理单元、收发单元或处理器、收发器运行时，使得所述网络设备执行第四方面及第四方面的任意可能的实现方式中的方法。
第十七方面，提供了一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于执行第一方面及第一方面的任意可能的实现方式中的方法的指令。
第十八方面，提供了一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于执行第二方面及第二方面的任意可能的实现方式中的方法的指令。
第十九方面，提供了一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于执行第三方面及第三方面的任意可能的实现方式中的方法的指令。
第二十方面，提供了一种计算机可读存储介质，用于存储计算机程序，该计算机程序包括用于执行第四方面及第四方面的任意可能的实现方式中的方法的指令。
本发明实施例的方法、终端设备以及网络设备，通过降维矩阵以及特征向量共同表征CSI，有利于网络设备获取精确地CSI。
附图说明
图1示出了适用于本发明实施例的通信系统的示意图。
图2是根据本发明实施例的用于反馈信道状态信息的方法的一例的示意性流程图。
图3是根据本发明实施例的用于反馈信道状态信息的方法的另一例的示意性流程图。
图4是根据本发明实施例的用于反馈信道状态信息的方法的又一例的示意性流程图。
图5是根据本发明实施例的终端设备的一例的示意性框图。
图6是根据本发明实施例的网络设备的一例的示意性框图。
图7是根据本发明实施例的终端设备的另一例的示意性框图。
图8是根据本发明实施例的网络设备的另一例的示意性框图。
图9是根据本发明实施例的终端设备的又一例的示意性框图。
图10是根据本发明实施例的网络设备的又一例的示意性框图。
图11是根据本发明实施例的终端设备的再一例的示意性框图。
图12是根据本发明实施例的网络设备的再一例的示意性框图。
具体实施方式
下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚地描述。
MIMO可以分为单用户多输入多输出(Single-User MIMO，简称“SU-MIMO”)和多用户多输入多输出(Multi-User MIMO，简称“MU-MIMO”)。Massive MIMO基于多用户波束成形的原理，在发送端设备布置几百根天线，对几十个目标接收机调制各自的波束，通过空间信号隔离，在同一频率资源上同时传输几十条信号。因此，Massive MIMO技术能够充分利用大规模天线配置带来的空间自由度，提升频谱效率。
图1示出了适用于本发明实施例的通信系统的示意图。如图1所示，该通信系统100包括网络设备102，网络设备102可包括多个天线例如，天线104、106、108、110、112和114。另外，网络设备102可附加地包括发射机链和接收机链，本领域普通技术人员可以理解，它们均可包括与信号发送和接收相关的多个部件(例如处理器、调制器、复用器、解调器、解复用器或天线等)。
网络设备102可以与多个终端设备(例如终端设备116和终端设备122)通信。然而，可以理解，网络设备102可以与类似于终端设备116或122的任意数目的终端设备通信。终端设备116和122可以是例如蜂窝电话、智能电话、便携式电脑、手持通信设备、手持计算设备、卫星无线电装置、全球定位系统、PDA和/或用于在无线通信系统100上通信的任意其它适合设备。
如图1所示，终端设备116与天线112和114通信，其中天线112和114通过前向链路118向终端设备116发送信息，并通过反向链路120从终端设备116接收信息。此外，终端设备122与天线104和106通信，其中天线104和106通过前向链路124向终端设备122发送信息，并通过反向链路126从终端设备122接收信息。
例如，在频分双工(FDD，Frequency Division Duplex)系统中，例如，前向链路118可利用与反向链路120所使用的不同频带，前向链路124可利用与反向链路126所使用的不同频带。
再例如，在时分双工(TDD，Time Division Duplex)系统和全双工(Full Duplex)系统中，前向链路118和反向链路120可使用共同频带，前向链路124和反向链路126可使用共同频带。
网络设备102通过预编码技术发送下行信号。预编码技术的基本思想是网络设备通过分析CSI来设计下行信号的发送方式，使网络设备发送的下行信号能使用信道矩阵的特征结构，使独立数据流之间的干扰尽可能小。当网络设备获知精确地CSI时，网络设备在发送下行信号时可以获得最大增益。
通道校准的TDD系统因为存在上下行信道互易性，网络设备可以通过信道探测参考 信号(Sounding Reference Signal，SRS)信号估计出较精确的CSI，从而网络设备有可能获得比较精确的CSI，但在FDD系统以及未校准的TDD系统中，CSI只能通过上行信道由终端设备反馈到网络设备。终端设备直接反馈下行信道的信道矩阵虽然可以使网络设备获取最精确的CSI，但是该方式的开销太大，无法应用于实际通信系统中。
为了降低CSI的反馈开销，终端设备利用码本中的码本矩阵对CSI进行量化，此码本为终端设备和网络设备共知的。终端设备确定与CSI最匹配的码本矩阵作为预编码矩阵并向网络设备反馈该预编码矩阵的索引。该码本是预配置好的，终端设备可以根据信道估计结果从码本中选择最匹配的预编码矩阵，但是该最匹配的预编码矩阵与实际信道情况仍然具有较大的差异，即预编码矩阵并不能精准地表征CSI。该方式虽然可以降低反馈开销，但是该方式会限制终端设备反馈的CSI的精度。
有鉴于此，本发明实施例提供了一种用于反馈信道状态信息的方法，基于Massive MIMO的信道具备空间稀疏性，通过采用压缩降维的方式，在CSI的反馈开销和CSI的反馈精度上做较好的折中。下面详细说明本发明实施例的用于反馈信道状态信息的方法。
应理解，本发明实施例的技术方案可以应用于各种通信系统，例如：全球移动通讯(Global System of Mobile communication，简称“GSM”)系统、码分多址(Code Division Multiple Access，简称“CDMA”)系统、宽带码分多址(Wideband Code Division Multiple Access，简称“WCDMA”)系统、通用分组无线业务(General Packet Radio Service，简称“GPRS”)、长期演进(Long Term Evolution，简称“LTE”)系统、先进的长期演进(Advanced long term evolution，简称“LTE-A”)系统、通用移动通信系统(Universal Mobile Telecommunication System，简称“UMTS”)或下一代通信系统(例如，5G)等。
在本发明实施例中，网络设备可以是用于与移动设备通信的设备，网络设备可以是WLAN中的接入点(ACCESS POINT，简称“AP”)，GSM或CDMA中的基站(Base Transceiver Station，简称“BTS”)，也可以是WCDMA中的基站(NodeB，简称“NB”)，还可以是LTE中的演进型基站(Evolutional Node B，简称“eNB”或“eNodeB”)，或者中继站或接入点，或者车载设备、可穿戴设备以及未来5G网络中的网络设备或者未来演进的公共陆地移动网络(Public Land Mobile Network，简称“PLMN”)中的网络设备等。
在本发明实施例中，终端设备也可以称为用户设备、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。终端设备可以是无线局域网(Wireless Local Area Networks，简称“WLAN”)中的站点(STAION，简称“ST”)，可以是蜂窝电话、无绳电话、会话启动协议(Session Initiation Protocol，简称“SIP”)电话、无线本地环路(Wireless Local Loop，简称“WLL”)站、个人数字处理(Personal Digital Assistant，简称“PDA”)设备、具有无线通信功能的手持设备、计算设备或连接到无线调制解调器的其它处理设备、车载设备、可穿戴设备以及下一代通信系统，例如，5G网络中的终端设备或者未来演进的PLMN中的终端设备等。
需要说明的是，本发明实施例中的情况和方式等的划分仅是为了描述的方便，不应构成特别的限定，各种情况和方式中的特征在不矛盾的情况下可以相结合。
还需要说明的是，在本发明实施例中“第一”“第二”等仅仅为了区分，不应对本发明实施例构成任何限定。
以下，结合图2至图4详细说明本发明实施例的用于反馈信道状态信息的方法。
应理解，图2和图4是本发明实施例的用于反馈信道状态信息的示意性流程图。应理解，图2和图4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，本发明实施例还可以执行其它操作或者图2和图4中的各种操作的变形。此外，图2和图4中的各个步骤可以分别按照与图2和图4所呈现的不同的顺序来执行，并且有可能仅执行图2和图4中的部分操作。
图2是根据本发明实施例的用于反馈信道状态信息的方法的一例的示意性流程图。具体地，图2示出了示出了从设备交互的角度描述的本发明实施例的用于反馈信道状态信息的方法200的示意性流程图。如图2所示，该方法200可以包括：
S210、终端设备向网络设备发送降维矩阵的矩阵信息，相应地，网络设备接收终端设备发送的降维矩阵；
其中，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度。
具体地，该降维矩阵用于对信道矩阵进行降维。例如，终端设备可以根据降维矩阵，对第一时刻接收的下行参考信号对应的信道矩阵进行降维。
以下，以第一维度为行维度第二维度为列维度为例，对降维矩阵进行说明。
应理解，终端设备可以对接收的下行参考信号进行信道估计，得到信道估计结果，该信道估计结果包括信道矩阵。
该方法200还可以包括：
S201、网络设备向终端设备发送下行参考信号，相应地，终端设备接收网络设备发送的下行参考信号；
具体地，该终端设备可以根据(所述终端设备)在第一时间段接收的下行参考信号对应的信道矩阵，确定下行信道的降维矩阵。进一步地，该降维矩阵可以用于对第二时间段的第一时刻接收的下行参考信号对应的信道矩阵进行降维。其中，第二时间段位于第一时间段之后，第一时刻可以包括第一时间段的结束时刻。
应理解，网络设备可以周期性地发送下行参考信号，相应地，终端设备可以周期性地接收网络设备发送的下行参考信号。终端设备可以根据第一时间段内接收的下行参考信号，获得第一时间段接收的下行参考信号对应的信道矩阵。
例如，假设该第一时间段为0.1秒，终端设备接收下行参考信号的周期为10毫秒，即，终端设备每隔10毫秒会接收一次下行参考信号。终端设备可以根据该0.1秒内接收的10次下行参考信号，获取该第一时间段接收的下行参考信号对应的信道矩阵。
终端设备在第一时间段中每次接收的下行参考信号占用至少一个资源块(RB)，该至少一个RB一一对应对应至少一个信道矩阵。由于在第一时间段内终端设备可以多次接收下行参考信号，该第一时间段接收的下行参考信号对应的信道矩阵包括多个信道矩阵。为了便于说明，可以将“第一时间段接收的下行参考信号对应的信道矩阵”记为“信道矩阵集合”
仍以第一时间段为0.1秒，下行参考信号的接收周期为10毫秒为例，假设，终端设备每次接收下行参考信号可以获取M个信道矩阵，该信道矩阵集合包括10·M个信道矩阵。
需要说明是，终端设备在同一时刻(即一个周期)接收的至少一个下参考信号中的 每个下行参考信号对应一个天线端口，每个天线端口可以与一个物理天线相对应，也可以与一个虚拟天线相对应，其中，该虚拟天线可以是多个物理天线的加权组合。终端设备可以根据天线端口对应的下行参考信号，获取终端设备和该天线端口之间的信道估计结果(即信道矩阵)。
可选地，网络设备发送下行参考信号的天线端口的数量与网络设备的发送天线端口的数量相同，换句话说，网络设备的所有发送天线端口均用于发送下行参考信号。即可以采用非预编码(non-precoded)CSI-RS，以便于终端设备可以估计完整的信道状态信息。
需要说明的是，CSI-RS用于终端进行信道状态信息测量，特别是用于多天线传输的情况。CSI-RS作为参考信号的一例，仅为示例性说明，不应对本发明实施例构成任何限定，本发明实施例不排除通过其他参考信号用于信道状态的测量。
该方法200还可包括：
S202、终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵；
具体地，终端设备可以根据第一时间段内接收到的下行参考信号，获取信道矩阵集合。信道矩阵集合中的每个信道矩阵H的维度为NR×NT，其中，NR表示终端设备的发射天线端口数量，NT表示网络设备的接收天线端口数量。终端设备可以根据该信道矩阵集合，确定用于对信道矩阵进行降维的降维矩阵P，该降维矩阵P的维度为NT×NP，其中，NP<NT。
降维矩阵用于对信道矩阵进行降维，高维的信道矩阵H经过降维矩阵降维之后可以得到低维的等效矩阵
Figure PCTCN2017072731-appb-000001
具体地，信道矩阵
Figure PCTCN2017072731-appb-000002
经过降维矩阵
Figure PCTCN2017072731-appb-000003
降维后可以得到等效矩阵
Figure PCTCN2017072731-appb-000004
进一步地，高维的信道矩阵降维至低维的等效矩阵的折损度与降维矩阵相关。为了使高维的信道矩阵低损地降维至低维的等效矩阵，可选地，在所述第一时间段中所述降维矩阵对应的子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，所述降维矩阵的各列向量之间满足正交性。为了便于说明，将“降维矩阵对应的子空间”记为“第一子空间”。
其中，第一子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，可以理解为在第一时间段中下行信道的能量主要集中在该第一子空间中。具体地，可以将该信道矩阵集合看成一个空间，下行信道的能量在该空间内非均匀分布，在第一时间段中下行信道的能量主要集中在第一子空间中，该第一子空间可以是该空间的特征子空间。
将高维的信道矩阵投影到该第一子空间(即与该第一子空间对应的降维矩阵相乘)中可以得到低维的等效矩阵。可以认为该低维的信道矩阵是高维的信道矩阵的浓缩表示。
可选地，在本发明实施例中，终端设备确定该降维矩阵的方式可以至少包括以下几种：
方式一、
所述终端设备计算所述降维矩阵。
作为可选地一例，终端设备可以通过计算第一协方差矩阵
Figure PCTCN2017072731-appb-000005
计算该降维矩阵。
所述第一协方差矩阵用于表征(或指示)所述第一时间段对应的所述下行信道的统计特性。其中，终端设备可以通过多种方式计算该第一协方差矩阵。
例如，终端设备可以计算信道矩阵集合中的每个信道矩阵的协方差矩阵，得到协方差矩阵集合。其中，该协方差矩阵集合包括的协方差矩阵与信道矩阵集合包括的信道矩阵一一对应。该终端设备可以按照时刻将该协方差矩阵集合中的协方差矩阵分为多组，多组协方差矩阵一一对应多个时刻，终端设备可以对每一组协方差矩阵进行平均得到对应时刻的第二协方差矩阵，终端设备将该多个时刻的第二协方差矩阵进行平均或时间上的滤波，得到该第一协方差矩阵。其中，该第二协方差矩阵用于表征对应的时刻的下行信道的统计特性。
示例地，假设，第一时间段为0.1秒，下行参考信号的接收周期为10毫秒(即终端设备在第一时间段接收10次下行参考信号，或在第一时间段的10个时刻接收下行参考信号)，终端设备每次接收下行参考信号可以获取M个信道矩阵H，该信道矩阵集合包括10·M个信道矩阵H，该终端设备计算该10·M个信道矩阵中每个信道矩阵H的协方差矩阵HHH，得到10·M协方差矩阵HHH。该终端设备可以将每个时刻的M个协方差矩阵进行平均得到该时刻的第二协方差矩阵，终端设备对10个第二协方差矩阵进行平均或时间上的滤波得到该第一协方差矩阵。
终端设备可以根据该第一协方差矩阵，通过特征值分解法、奇异值分解(Singular value decomposition，SVD)法、幂法或其他算法得到该降维矩阵。可选地，该降维矩阵对应的第一子空间可以为该第一协方差矩阵的特征子空间。
作为可选地另一例，终端设备可以根据信道矩阵集合，通过PAST算法、Lanczos算法以及其他算法确定该降维矩阵。
方式一中的降维矩阵是终端设备根据下行信道估计结果自适应计算得到的，根据该计算得到的降维矩阵对下行信道的信道矩阵进行降维，可以降低该下行信道的信道矩阵降维的损耗。
可选地，若终端设备计算该降维矩阵，该方法200还可以包括：所述终端设备通过对所述降维矩阵的元素进行量化获取所述矩阵信息。可选地，终端设备通过上行数据信道发送该矩阵信息。
其中，终端设备可以通过多种方式对降维矩阵的元素进行量化。例如，终端设备可以对该降维矩阵的每一列采用幅度和相位分别量化的方式。由于幅度与相位都可以看成是无符号数，从而省去了符号位的量化开销，从而节省反馈开销。又例如，终端设备可以对该降维矩阵的每一列采用实部和虚部分别量化的方式。后续会对量化流程进行描述。
方式二、
所述终端设备从预设的降维矩阵集合中确定所述降维矩阵。
具体地，可以预设一个降维矩阵集合，终端设备和网络设备均已知该降维矩阵集合，该降维矩阵集合中包括多个降维矩阵。终端设备可以根据信道矩阵集合，从降维矩阵集合中选择该下行信道的降维矩阵。
其中，终端设备可以通过多种准则选择该降维矩阵。例如，终端设备可以基于信道矩阵集合，计算降维矩阵集合中每个降维矩阵对应的下行信道的能量，选择具有下行信道的能量最高的降维矩阵作为该下行信道的降维矩阵。即，可以认为在第一时间段中下行信道的能量主要集中在降维矩阵对应的第一子空间中，
该降维矩阵是终端设备从预置的降维矩阵集合中选择的，可以降低终端设备反馈降维矩阵的反馈开销。进一步地，还可以降低终端设备计算降维矩阵的复杂度。
若该降维矩阵是终端设备从预设的降维矩阵中选择的，该矩阵信息包括所述降维矩阵在所述预设的降维矩阵集合的索引。
可选地，该降维矩阵对应波束方向图相同的多个正交波束。也就是说，该降维矩阵的每一列对应的波束方向图相同。
由于降维矩阵的每一列对应的波束方向图相同，每个波束上接收信道的能量差不多，在后续传输下行等效信道的相关信息时，有利于降低反馈开销。
可选地，本发明实施例的降维矩阵集合的生成可以利用大规模天线阵列子阵划分和/或Kronecker积的结构，但不局限。
S220、所述终端设备向所述网络设备发送下行等效信道的特征向量的向量信息；相应地，网络设备接收终端设备发送的向量信息；
其中，所述下行等效信道的特征向量基于所述降维矩阵得到。下行等效信道可以理解为下行信道投影到第一子空间得到的信道(或下行信道经过降维矩阵降维得到的信道)。该下行等效信道可以认为是下行信道的浓缩表示，下行等效信道的信道状态以及降维矩阵可以用于表征下行信道的信道状态。该下行等效信道的特征向量可以用于表征下行等效信道的信道状态(例如，第一时刻的下行等效信道的特征向量用于表征第一时刻的下行等效信道的信道状态)。该下行等效信道的特征向量可以包括r个特征向量，即该下行等效信道的特征向量可以记为
Figure PCTCN2017072731-appb-000006
r由所述网络设备配置或r与所述终端设备支持的数据流的数目(即RANK)相同，r≥1。
可选地，该r个特征向量中任一个特征向量对应的特征值大于或等于下行等效信道对应的多个特征向量除所述r个特征向之外的任一个特征向量对应的特征值。
可选地，该下行等效信道的特征向量可以包括以下两种中的至少一种：
1、下行等效信道的全带宽特征向量，该全带宽特征向量用于表征全带宽的下行等效信道的信道状态；
2、下行等效信道的局部带宽特征向量，该局部带宽特征向量用于表征局部带宽的下行等效信道的信道状态。
也就是说，终端设备可以根据反馈粒度向网络设备反馈当前的下行等效信道的全带宽特征向量或局部带宽特征向量，其中，该反馈粒度可以包括全带宽或局部带宽(例如，子带)。
以反馈粒度为局部带宽为例，假设全带宽为20M，反馈粒度为10M，终端设备可以确定0-10M对应的第一局部带宽特征向量和/或10-20M对应的第二局部带宽特征向量，并反馈相应的向量信息。
该方法200还可以包括：
S203、所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量。
其中，第一时刻位于第一时间段之后，且第一时刻可以包括第一时间段的结束时刻。应理解，第一时刻接收的下行参考信号对应的下行等效信道的信道状态用于表征第一时刻接收的下行参考信号对应的下行信道的信道状态，第一时刻接收的下行参考信号对应的下行等效信道的特征向量用于表征第一时刻接收的下行参考信号对应的下行等效信道的信道状态。可选地，终端设备至少可以通过以下几种方式确定下行等效信道的特征向 量。
方式一、
终端设备计算下行等效信道的特征向量。
具体地，终端设备可以将当前的下行参考信号对应的信道矩阵与降维矩阵相乘，得到该当前的下行参考信号对应的等效矩阵，即
Figure PCTCN2017072731-appb-000007
由上文可知，终端设备每次接收的下行参考信号对应的信道矩阵包括至少一个信道矩阵。该终端设备对该至少一个信道矩阵进行降维可以一一对应的得到至少一个等效矩阵。例如，假设终端设备对当前接收的下行参考信号进行信道估计，得到M个信道矩阵，终端设备对该M个信道矩阵进行降维可以得到M个等效矩阵。为了便于说明，可以将“当前的下行参考信号对应的等效矩阵”记为“等效矩阵组”。
该终端设备可以根据等效矩阵组，通过计算第一频域资源区域对应的第三协方差矩阵，获取第一频域资源区域的下行等效信道的特征向量。第三协方差矩阵用于表征第一频域资源区域的下行等效信道的统计特性。第一频域资源区域包括全带宽或部分带宽。
进一步地，终端设备可以通过对第一频域资源区域对应的协方差矩阵进行平均，得到第一频域资源区域的第三协方差矩阵。
应理解，第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述第一时刻接收的下行参考信号对应的等效矩阵的协方差矩阵。
具体地，若反馈粒度为全带宽(即第一频域资源为全带宽)，终端设备可以计算等效矩阵组中每个等效矩阵的协方差矩阵，对所有的协方差矩阵进行平均，获取全带宽的下行等效信道的第三协方差矩阵，该第三协方差矩阵用于表征全带宽的下行等效信道的统计特性。其中，终端设备可以通过多种算法得到该第三协方差矩阵的特征向量，具体可以参见上文相关描述，为了简洁不在此赘述。
例如，假设全带宽为20M(包括100个RB)，终端设备得到100个等效矩阵，进而根据该100个等效矩阵一一对应得到100个协方差矩阵。终端设备可以对该100个协方差矩阵进行平均得到第三协方差矩阵，终端设备可以计算该第三协方差矩阵的特征向量(即全带宽特征向量)。该特征向量信息可以用于表征全带宽的下行等效信道的信道状态。
具体地，若反馈粒度为局部带宽，终端设备可以计算等效矩阵组中每个等效矩阵的协方差矩阵，并以局部带宽为单位，对每个局部带宽对应的协方差矩阵进行平均，获取每个局部带宽对应的第三协方差矩阵，每个第三协方差矩阵用于表征对应的局部带宽的下行等效信道的信道状态。
例如，假设全带宽为20M(包括100个RB)，反馈粒度为10M(包括50个RB)，终端设备得到100个协方差矩阵，其中，该100个协方差矩阵中有50个协方差矩阵对应0-10M的带宽，另外50个协方差矩阵对应10-20M的带宽。终端设备可以将该0-10M带宽对应的50个协方差矩阵进行平均得到0-10M带宽对应的第三协方差矩阵，并计算该第三协方差矩阵的特征向量(即第一局部带宽特征向量)。同理，终端设备可以将该10-20M带宽对应的50个协方差矩阵进行平均得到10-20M带宽对应的第三协方差矩阵，并计算该第三协方差矩阵的特征向量(即第二局部带宽特征向量)。在此情况下，该向量信息可以包括第一局部带宽特征向量和/或第二局部带宽特征向量。
作为可选地另一例，终端设备可以根据信道矩阵集合，通过PAST算法、Lanczos算 法以及其他算法确定下行等效信道的特征向量。
方式一中的特征向量是终端设备根据等效矩阵计算得到的，以使该特征向量可以较好的表征第一时刻的下行等效信道的信道状态。
可选地，若终端设备计算该特征向量，该方法200还可以包括：终端设备通过对所述特征向量的元素进行量化获取向量信息。可选地，终端设备通过数据信道发送该向量信息。
方式二、
所述终端设备从预设的特征向量集合中确定下行等效信道的特征向量。
具体地，可以预设一个特征向量集合，终端设备和网络设备均已知该特征向量集合，终端设备可以根据降维矩阵，对当前接收的下行参考信号对应的信道矩阵进行降维，并按照一定准则从该特征向量集合中确定该下行等效信道的特征向量。
该特征向量是终端设备从预设的特征向量集合中选择的，该向量信息包括特征向量在该向量集合中的索引，该方式可以降低终端设备反馈向量的反馈开销。
需要说明是，若下行信道对应的特征向量的数量为多个，例如，r＝2，该特征向量集合可以至少包括以下两种情况：
(1)特征向量集合包括多个特征向量，终端设备可以从该多个特征向量中选择两个特征向量，并反馈该两个特征向量对应的两个索引。
(2)特征向量集合包括多个特征矩阵，该多个特征矩阵中的每个特征矩阵包括两列(可以将该特征矩阵的每一列看成一个特征向量)，该终端设备可以从该多个特征矩阵中选择一个特征矩阵，并反馈该特征矩阵的索引。
以上，描述了终端设备可以确定并反馈矩阵信息以及向量信息，以下详细描述终端设备如何反馈该矩阵信息以及向量信息。
可选地，在本发明实施例中，终端设备可以周期性地确定该降维矩阵以及该特征向量。其中，终端设备周期性地确定降维矩阵和特征向量可以理解为终端设备周期性的反馈矩阵信息和向量信息。相应地，网络设备会周期性地接收并更新矩阵信息，并使用更新的矩阵信息获取对应时刻的信道状态信息。
例如，该第一时间段对应的时长可以为终端设备反馈矩阵信息的周期，该终端设备可以根据该在第一时间段接收的下行参考信号确定的降维矩阵，对第二时间段的信道矩阵进行降维。其中，该第二时间段和第二时间段的时长相等，该第二时间段为第一时间段的下一个时间段。换句话说，终端设备可以根据第i时间段接收的下行参考信号确定的降维矩阵，对第i+1时间段接收的信道矩阵进行降维。相应地，网络设备根据第i个时间段的结束时刻接收的降维信息，对第i+1个时间段接收的向量信息进行恢复得到高维的矩阵，其中i为大于0的正整数。
可选地，终端设备反馈矩阵信息的周期长于终端设备反馈向量信息的周期。即，终端设备可以对矩阵信息以及向量信息分别进行长周期以及短周期反馈。
短周期：终端设备可以将具有空间稀疏性的高维的信道矩阵经过降维处理得到低维的等效矩阵。该低维的等效矩阵是高维的信道矩阵的浓缩表示，终端设备可以在较短的周期内反馈下行信道的等效矩阵的相关信息即向量信息，以便于网络设备即时了解信道状态并做相应处理。例如，该向量信息的反馈周期可以是5毫秒、10毫秒等。
可选地，终端设备反馈向量信息的反馈周期的时间大于或等于终端设备接收下行参考 信号(或网络设备发送下行参考信号)的周期。若反馈向量信息的周期与接收下行参考信号的周期相同，可以使网络设备获取每一次发送的下行参考信号的信道状态，有利于网络设备做相应处理。
长周期：为了使网络设备能够基于向量信息获取高维的信道矩阵，终端设备还需要将该矩阵信息发送给网络设备。不同与向量信息的实时反馈，降维矩阵是终端设备对信道状态进行持续估计的基础上得到的一种统计信息，不必实时反馈，可以适当拉长反馈周期。例如，该矩阵信息的反馈周期可以是0.1秒-1秒。
图3是根据本发明实施例的用于反馈信道状态信息的方法的另一例的示意性流程图。如图3所示，时域资源可以被划分为以短周期(即向量信息的周期)为单位的基本单元，每个短周期可以包括至少一个传输时间间隔(Transmission Time Interval，TTI)。假设，终端设备接收下行参考信号的周期为10个1毫秒TTI(1毫秒TTI等于一个子帧，10个子帧为一个无线帧)，该短周期可以包括10个TTI，在每个短周期中，终端设备向网络设备反馈即时的下行信道状态。多个短周期组成一个长周期。在每个长周期中，终端设备持续进行信道估计(即获取信道矩阵集合)，并得到降维矩阵，降维周期的反馈以长周期进行。在每个长周期的最后一个短周期中，终端设备不但会反馈降维矩阵，还可能反馈向量信息。
另外，从图1可以看出，终端设备使用上一个周期确定的降维矩阵对当前周期中接收的下行参考信号对应的信道矩阵进行降维，相应地，网络设备根据上一个周期接收的降维矩阵以及当前接收的向量信息确定预编码矩阵。即该S110可以包括：
所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定第二时间段对应的下行信道的降维矩阵。其中，第二时间段位于第一时间段之后，该第二时间段可以与第一时间段的时长相等。
S230、网络设备可以根据该矩阵信息以及向量信息确定预编码矩阵。
具体地，网络设备获取精确地CSI是为了确定预编码矩阵。网络设备可以根据矩阵信息获取降维矩阵
Figure PCTCN2017072731-appb-000008
并根据向量信息确定下行等效信道的特征向量
Figure PCTCN2017072731-appb-000009
网络设备可以根据P·V确定该预编码矩阵。通过该降维矩阵以及下行等效信道的特征向量得到高维的矩阵。该预编码矩阵可以为该高维的矩阵。
若矩阵信息包括降维矩阵的索引，网络设备可以根据该降维矩阵的索引以及预设的降维矩阵集合确定该降维矩阵。若向量信息包括特征向量的索引，网络设备可以根据该特征向量的索引以及预设的特征向量集合确定特征向量。
若矩阵信息包括降维矩阵的元素经过量化得到的量化后元素，换句话说，若矩阵信息由终端设备通过对所述降维矩阵的元素进行量化获取，网络设备接收到该矩阵信息之后先要恢复该矩阵信息对应的降维矩阵。同理，若向量信息包括特征向量的元素经过量化得到的量化后元素，网络设备接收到该向量信息之后先要恢复该向量信息对应的特征向量。
以下，以对下行等效信道的特征向量的相位和幅度分别量化为例，简述终端设备的量化流程以及网络设备根据向量信息恢复特征相连的恢复流程。
假设，假设待量化的特征向量为
Figure PCTCN2017072731-appb-000010
,该V1可以表示成如下形式：
Figure PCTCN2017072731-appb-000011
其中，
Figure PCTCN2017072731-appb-000012
表示元素乘，|vi|
Figure PCTCN2017072731-appb-000013
分别表示第i个元素vi的幅度以及相位。其中，i＝1，…，P。计算公式如下：
Figure PCTCN2017072731-appb-000014
Figure PCTCN2017072731-appb-000015
对做如下操作：
Figure PCTCN2017072731-appb-000016
其中，
Figure PCTCN2017072731-appb-000017
Figure PCTCN2017072731-appb-000018
Figure PCTCN2017072731-appb-000019
对幅度进行量化是指对|vi|，i＝1…P进行量化。假设幅度的量化比特数为MA，那么量化过程可以表示为：
Figure PCTCN2017072731-appb-000020
其中，floor(·)表示向下取整，min{·，·}用于饱和操作。
对相位进行量化是指对
Figure PCTCN2017072731-appb-000021
i＝2…P进行量化，其中，
Figure PCTCN2017072731-appb-000022
无需量化。假设向量的量化比特数为MB，那么量化过程可以表示为：
Figure PCTCN2017072731-appb-000023
终端设备将
Figure PCTCN2017072731-appb-000024
和
Figure PCTCN2017072731-appb-000025
发送给网络设备，网络设备可以恢复每个元素的幅度与相位
Figure PCTCN2017072731-appb-000026
然后对组成的特征向量
Figure PCTCN2017072731-appb-000027
进行2范数归一化。相应恢复过程可以表示为：
Figure PCTCN2017072731-appb-000028
对
Figure PCTCN2017072731-appb-000029
进行归一化等价于对幅度向量进行归一化，该幅度恢复过程可以表示为
Figure PCTCN2017072731-appb-000030
最终，将恢复的幅度与相位元素点成得到恢复的特征向量：
Figure PCTCN2017072731-appb-000031
需要说明是，以上对特征向量V1的量化过程仅为示例，不应对本发明实施例构成任何限定，本发明实施例还可以采用其他方式对特征向量和/或降维矩阵的元素进行量化。
本发明实施例的方法，通过降维信息以及向量信息共同表征CSI，有利于使网络设备获取精确地CSI。进一步地，降维信息以及向量信息分别采用长周期以及短周期的方式进行反馈，有利于降低反馈开销。本发明实施例的方法可以在反馈CSI的精度以及反馈CSI的开销上得到很好的折中。
以上，结合图2和图3描述了终端设备可以向网络设备发送降维信息以及向量信息，以使网络设备获取较精确地CSI，进一步地，终端设备可以对降维信息以及向量信息分别进行长周期以及短周期反馈，有利于降低反馈CSI的开销。
进一步地，FDD系统以及未校准的TDD的上下行信道没有信道互易性，因此，不能根据当前的上行参考信号直接估计当前的下行信道的信道状态或相邻时刻的下行信道的信道状态。但事实上，(在一段时间内)FDD系统以及未校准的TDD是存在一定相关性的。在本发明实施例中通过降维矩阵以及特征向量共同表征CSI，由于FDD系统以及未校准的TDD的上下行信道没有信道互易性，终端设备需要向网络设备发送特征向量的向量信息。然而，对于FDD系统以及未校准的TDD系统存在一定相关性，网络设备设备可以基于降维矩阵发送下行参考信号，以使终端设备无需反馈该降维矩阵的矩阵信息。以下，详细描述该方法。
图4是根据本发明实施例的用于反馈信道状态信息的方法的又一例的示意性流程图。
如图4所示，该方法300可以包括：
S310、网络设备根据降维矩阵发送下行参考信号；相应地，终端设备接收网络设备根据降维矩阵发送的下行参考信号；
其中，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度。
具体地，假设用于发送下行参考信号的预编码矩阵为
Figure PCTCN2017072731-appb-000032
,若采用该预编码矩阵A发送下行参考信号，终端设备获取的信道矩阵为
Figure PCTCN2017072731-appb-000033
该信道矩阵H为高维的信道矩阵。若根据降维矩阵
Figure PCTCN2017072731-appb-000034
发送下行参考信号，终端设备获取的信道矩阵为
Figure PCTCN2017072731-appb-000035
即终端设备对下行参考信号进行估计得到的信道估计结果为已经经过降维的矩阵。
在该方法中，网络设备可以采用虚拟天线映射的方法将NS个端口的下行参考信号映射到NT个天线端口进行发送，其中，该映射矩阵为降维矩阵的转置。
该方法300还可以包括：
S301、终端设备向网络设备发送上行参考信号，相应地，网络设备接收终端设备发送的上行参考信号；
S302、所述网络设备根据所述在第一时间段接收的上行参考信号对应的信道矩阵，确定所述降维矩阵；
具体地，网络设备可以根据该网络设备在第一时间段接收的上行参考信号对应的信道矩阵，确定下行信道的降维矩阵。该降维矩阵可以对下行信道的信道矩阵进行降维。为了便于说明，可以将“网络设备在第一时间段接收的上行参考信号对应的信道矩阵”记为“信道矩阵集合”。网络设备可以根据信道矩阵集合确定该降维矩阵。
S320、所述终端设备根据所述下行参考信号对应的信道矩阵，向所述网络设备发送下行等效信道的特征向量的向量信息；相应地，网络设备接收该向量信息。
需要说明是，该下行参考信号对应的信道矩阵为经过降维的信道矩阵(即相应于上文的下行参考信号对应的等效矩阵)。
该方法还可以包括：
S303、所述终端设备根据所述下行参考信号对应的信道矩阵，确定下行等效信道的特征向量。
S330、网络设备根据降维矩阵以及向量信息确定预编码矩阵。
可选地，网络设备确定降维矩阵的周期长于网络设备接收向量信息的周期。例如，该网络设备确定降维矩阵的周期为0.1秒-1秒，网络设备接收向量信息的周期为5毫秒-10毫秒。
为了便于说明，可以将确定降维矩阵的周期记为第一周期，将接收向量信息的周期记为第二周期。
网络设备在第i个第一周期确定的降维矩阵，可以用于与第i+1个第一周期接收的向量信息共同表征CSI。
例如，假设网络设备确定降维矩阵的周期为1秒，网络设备在T时刻确定降维矩阵，为了简洁可以将该“T时刻确定的降维矩阵”记为“第一降维矩阵”，该第一降维矩阵可以用于与T时刻之后的0.1秒接收的向量信息表征对应时刻的CSI，该第一降维矩阵还可以用于与T时刻之后的0.2秒接收的向量信息表征对应时刻的CSI。
该方法300中网络设备根据降维矩阵发送下行参考信号，终端设备对该下行参考信号估计，得到的信道矩阵实质为等效矩阵。与方法200相比，终端设备无需再对该下行参考信号对应的信道矩阵进行降维，终端设备也无需向网络设备反馈矩阵信息。
应理解，在方法200以及方法300中，降维矩阵以及特征向量共同表征CSI，方法200以及方法300中执行的步骤以及操作具有相似性，方法300中的相关描述可以参见方法200中的相关描述(例如，S301的具体描述可以参见S202的相关描述)。为了简洁此处不再赘述。
与现有技术中通过从码本中选择的预编码矩阵来表征CSI相比，本发明实施例的方法通过降维矩阵(矩阵信息)以及特征向量(向量信息)表征CSI，有利于网络设备获取精确地CSI。进一步地，与直接反馈高维的信道矩阵相比，在本发明实施例中，终端设备发送下行等效信道的特征向量，能够降低反馈开销。本发明实施例的方法，通过降维矩阵和特征向量表征CSI能够在CSI的反馈开销以及CSI的反馈精度上做很好的折中，有利于网络设备较好的收获空分复用的增益。
以上，结合图1至图4详细说明了本发明实施例的发送控制信息的方法和接收控制信息的方法。以下，结合图5和图12详细说明本发明实施例的终端设备和网络设备。
图5是根据本发明实施例的终端设备的一例的示意性框图。应理解，图5示出的终端设备400仅是示例，本发明实施例的终端设备400还可包括其他模块或单元，或者包括与图5中的各个模块的功能相似的模块，或者并非要包括图5中的所有模块。
如图5所示，该终端设备400包括：
发送单元410，所述发送单元410用于：向网络设备发送降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第 二维度小于所述降维矩阵的第一维度；向所述网络设备发送下行等效信道的特征向量的向量信息，所述下行等效信道的特征向量基于所述降维矩阵得到；其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
可选地，所述发送单元410具体用于：通过上行数据信道向所述网络设备发送所述矩阵信息；和/或通过上行数据信道向所述网络设备发送所述向量信息。
可选地，所述降维矩阵是由所述终端设备400根据在第一时间段接收的下行参考信号对应的信道矩阵确定的，在所述第一时间段中所述降维矩阵对应的子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，所述降维矩阵的各列向量之间满足正交性。
可选地，所述终端设备400还包括：第一处理单元，用于根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵。
可选地，所述第一处理单元具体用于：根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的下行信道的统计特性；根据所述第一协方差矩阵，计算所述降维矩阵。
可选地，所述第一处理单元具体用于：计算所述终端设备400在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；通过对相同时刻接收的下行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
可选地，所述第一处理单元具体用于：根据所述在第一时间段接收的下行参考信号对应的信道矩阵，从预设的降维矩阵集合中确定所述降维矩阵，所述降维矩阵的矩阵信息包括所述降维矩阵在所述预设的降维矩阵集合的索引。
可选地，所述降维矩阵的每一列对应的波束方向图相同。
可选地，所述终端设备400还包括：第二处理单元，用于根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量。
可选地，所述第二处理单元具体用于：根据所述降维矩阵，通过对所述第一时刻的接收的下行参考信号对应的信道矩阵进行降维，得到所述第一时刻接收的下行参考信号对应的等效矩阵；计算所述第一时刻接收的下行参考信号对应的等效矩阵中每个等效矩阵的协方差矩阵；通过对第一频域资源区域对应的协方差矩阵进行平均，得到所述第一资源区域对应的第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述第一时刻接收的下行参考信号对应的等效矩阵的协方差矩阵；根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
可选地，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备400支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
可选地，所述发送单元410发送所述矩阵信息的周期长于所述发送单元410发送所述向量信息的周期。
应理解，图5所示本发明实施例的终端设备中的各个单元的上述和其它操作和/或功能分别为了实现上述方法200中相应流程，为了简洁，在此不再赘述。
图6是根据本发明实施例的网络设备的一例的示意性框图。应理解，图6示出的网络设备400仅是示例，本发明实施例的网络设备500还可包括其他模块或单元，或者包括与图6中的各个模块的功能相似的单元，或者并非要包括图6中的所有单元。
如图6所示，该网络设备500包括：接收单元510，所述接收单元510用于：接收终端设备发送的降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备500的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；接收所述终端设备发送的下行等效信道的特征向量的向量信息；处理单元520，用于根据所述矩阵信息和所述向量信息，确定预编码矩阵；其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息
可选地，所述接收单元510具体用于：通过上行数据信道接收所述终端设备发送的矩阵信息；和/或通过上行数据信道接收所述网络设备500发送的所述向量信息。
可选地，所述接收单元510接收所述矩阵信息的周期长于所述接收单元510接收所述向量信息的周期。
应理解，图6所示网络设备中的各个单元的上述和其它操作和/或功能分别为了实现上述方法200中相应流程，为了简洁，在此不再赘述。
图7是根据本发明实施例的终端设备的另一例的示意性框图。应理解，图7示出的终端设备600仅是示例，本发明实施例的终端设备600还可包括其他单元，或者包括与图7中的各个模块的功能相似的单元，或者并非要包括图7中的所有单元。
如图5所示，该终端设备600包括：接收单元610，所述接收单元610用于：接收网络设备根据降维矩阵发送的下行参考信号，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；发送单元620，用于根据所述接收单元610接收的下行参考信号对应的信道矩阵，向所述网络设备发送下行等效信道的特征向量的向量信息。
可选地，所述终端设备600还包括：处理单元，所述处理单元用于：根据所述下行参考信号对应的信道矩阵，计算所述下行等效信道的特征向量；通过对所述特征向量进行量化得到所述向量信息。
可选地，所述发送单元620具体用于：通过上行数据信道向所述网络设备发送所述向量信息。
可选地，所述处理单元具体用于：计算所述下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；对第一频域资源区域对应的协方差矩阵进行平均，得到第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述下行参考信号对应的信道矩阵的协方差矩阵，所述第一频域资源区域包括全带宽或局部带宽；根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
可选地，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
应理解，图7所示本发明实施例的终端设备600中的各个单元的上述和其它操作和/或功能分别为了实现上述方法300中相应流程，为了简洁，在此不再赘述。
图8是根据本发明实施例的网络设备的另一例的示意性框图。应理解，图8示出的网络设备700仅是示例，本发明实施例的网络设备700还可包括其他单元或模块，或者包括与图8中的各个模块的功能相似的单元，或者并非要包括图5中的所有单元。
如图8所示，该网络设备700包括：
发送单元710，用于根据降维矩阵发送下行参考信号，所述降维矩阵的第一维度与所述网络设备700的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；接收单元720，用于接收所述终端设备根据所述下行参考信号发送的下行等效信道的特征向量的向量信息；处理单元730，用于根据所述降维矩阵和所述向量信息确定预编码矩阵。
可选地，所述接收单元720具体用于：通过上行数据信道接收所述向量信息。
可选地，所述处理单元730还用于：根据所述在第一时间段接收的上行参考信号对应的信道矩阵，确定所述降维矩阵。
可选地，所述处理单元730具体用于：根据所述在第一时间段接收的上行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的所述上行信道的统计特性；根据所述第一协方差矩阵，计算所述降维矩阵。
可选地，所述处理单元730具体用于：计算所述终端设备在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；通过对相同时刻接收的上行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
可选地，所述处理单元730确定所述降维矩阵的周期长于所述接收单元720接收所述向量信息的周期。
应理解，图8所示本发明实施例的网络设备700中的各个单元的上述和其它操作和/或功能分别为了实现上述方法300中相应流程，为了简洁，在此不再赘述。
图9是根据本发明实施例的终端设备的又一例的示意性框图。该终端设备800可以对应(例如，可以配置于或本身即为)上述方法200中描述的终端设备，并且，该终端设备800中各模块或单元分别用于执行上述方法200中终端设备所执行的各动作或处理过程，这里，为了避免赘述，省略其详细说明。
在本发明实施例中，该终端设备800可以包括：收发器810和处理器820，处理器和收发器相连，可选地，该设备还包括存储器，存储器可以集成在处理器中，也可以独立于处理器。其中，该存储器可以用于存储指令，该处理器用于执行该存储器存储的指令，以控制收发器发送信息或信号，该处理器、存储器和收发器可以通过内部连接通路互相通信，传递控制和/或数据信号。
其中，图5所示的终端设备400中的处理单元可以对应该处理器820，图5所示的终 端设备中的发送单元和/或接收单元可以对应该收发器。
图10是根据本发明实施例的网络设备的又一例的示意性框图。该网络设备900可以对应(例如，可以配置于或本身即为)上述方法200中描述的网络设备900，并且，该网络设备900中各模块或单元分别用于执行上述方法200中网络设备900所执行的各动作或处理过程，这里，为了避免赘述，省略其详细说明。
在本发明实施例中，该网络设备900可以包括：收发器910和处理器920，处理器和收发器相连，可选地，该设备还包括存储器，存储器可以集成在处理器中，也可以独立于处理器。其中，该存储器可以用于存储指令，该处理器用于执行该存储器存储的指令，以控制收发器发送信息或信号，该处理器、存储器和收发器可以通过内部连接通路互相通信，传递控制和/或数据信号。
其中，图6所示的网络设备500中的处理单元可以对应该处理器920，图6所示的网络设备500的发送单元和/或接收单元可以对应该收发器910。
图11是根据本发明实施例的终端设备的再一例的示意性框图。该终端设备1000可以对应(例如，可以配置于或本身即为)上述方法300中描述的终端设备，并且，该终端设备1000中各模块或单元分别用于执行上述方法300中终端设备所执行的各动作或处理过程，这里，为了避免赘述，省略其详细说明。
在本发明实施例中，该终端设备1000可以包括：收发器1010和处理器1020，处理器和收发器相连，可选地，该设备还包括存储器，存储器可以集成在处理器中，也可以独立于处理器。其中，该存储器可以用于存储指令，该处理器用于执行该存储器存储的指令，以控制收发器发送信息或信号，该处理器、存储器和收发器可以通过内部连接通路互相通信，传递控制和/或数据信号。
其中，图7所示的终端设备中的处理单元可以对应该处理器1020，图7所示的终端设备中的发送单元和/或接收单元可以对应该收发器1010。
图12是根据本发明实施例的网络设备的再一例的示意性框图。该网络设备1100可以对应(例如，可以配置于或本身即为)上述方法300中描述的网络设备，并且，该网络设备1100中各模块或单元分别用于执行上述方法300中网络设备所执行的各动作或处理过程，这里，为了避免赘述，省略其详细说明。
该网络设备1100可以包括：收发器1110和处理器1120，处理器和收发器相连，可选地，该设备还包括存储器，存储器可以集成在处理器中，也可以独立于处理器。其中，该存储器可以用于存储指令，该处理器用于执行该存储器存储的指令，以控制收发器发送信息或信号，该处理器、存储器和收发器可以通过内部连接通路互相通信，传递控制和/或数据信号。
其中，图8所示的网络设备700中的处理单元可以对应该处理器1120，图8所示的网络设备700的发送单元和/或接收单元可以对应该收发器1110。
应注意，本发明实施例上述方法实施例可以应用于处理器中，或者由处理器实现。处理器可能是一种集成电路芯片，具有信号的处理能力。在实现过程中，上述方法实施例的各步骤可以通过处理器中的硬件的集成逻辑电路或者软件形式的指令完成。上述的处理器可以是通用处理器、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。可以实现或者执行本发明实施例中的公开的各方法、步骤及逻辑框图。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。结合本发明实施例所公开的方法的步骤可以直接体现为硬件译码处理器执行完成，或者用译码处理器中的硬件及软件模块组合执行完成。软件模块可以位于随机存储器，闪存、只读存储器，可编程只读存储器或者电可擦写可编程存储器、寄存器等本领域成熟的存储介质中。该存储介质位于存储器，处理器读取存储器中的信息，结合其硬件完成上述方法的步骤。
可理解，本发明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(Dynamic RAM，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)。应注意，本文描述的存储器旨在包括但不限于这些和任意其它适合类型的存储器。
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。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。
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，而不应对本发明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，或者网络设备等)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(ROM，Read-Only Memory)、随机存取存储器(RAM，Random Access Memory)、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所述以权利要求的保护范围为准。

Claims (30)

  1. 一种用于反馈信道状态信息的方法，其特征在于，所述方法包括：
    终端设备向网络设备发送降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；
    所述终端设备向所述网络设备发送下行等效信道的特征向量的向量信息，所述下行等效信道的特征向量基于所述降维矩阵得到；
    其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；
    所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
  2. 根据权利要求1所述的方法，其特征在于，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道发送的。
  3. 根据权利要求1或2所述的方法，其特征在于，所述降维矩阵是由所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵确定的，在所述第一时间段中所述降维矩阵对应的子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，所述降维矩阵的各列向量之间满足正交性。
  4. 根据权利要求1至3中任一项所述的方法，其特征在于，所述方法还包括：
    所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵。
  5. 根据权利要求4所述的方法，其特征在于，所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵，包括：
    所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的下行信道的统计特性；
    所述终端设备根据所述第一协方差矩阵，计算所述降维矩阵。
  6. 根据权利要求5所述的方法，其特征在于，所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，包括：
    所述终端设备计算所述终端设备在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；
    所述终端设备通过对相同时刻接收的下行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；
    所述终端设备对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
  7. 根据权利要求4所述的方法，其特征在于，终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵，确定下行信道的降维矩阵，包括：
    所述终端设备根据所述在第一时间段接收的下行参考信号对应的信道矩阵，从预设的降维矩阵集合中确定所述降维矩阵，所述降维矩阵的矩阵信息包括所述降维矩阵在所述预设的降维矩阵集合的矩阵索引。
  8. 根据权利要求7所述的方法，其特征在于，所述降维矩阵的每一列对应的波束方向图相同。
  9. 根据权利要求1至8中任一项所述的方法，其特征在于，所述方法还包括：
    所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量。
  10. 根据权利要求9所述的方法，其特征在于，所述终端设备根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量，包括：
    所述终端设备根据所述降维矩阵，通过对所述第一时刻的接收的下行参考信号对应的信道矩阵进行降维，得到所述第一时刻接收的下行参考信号对应的等效矩阵；
    所述终端设备计算所述第一时刻接收的下行参考信号对应的等效矩阵中每个等效矩阵的协方差矩阵；
    所述终端设备通过对第一频域资源区域对应的协方差矩阵进行平均，得到所述第一资源区域对应的第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述第一时刻接收的下行参考信号对应的等效矩阵的协方差矩阵；
    所述终端设备根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
  11. 根据权利要求1至10中任一项所述的方法，其特征在于，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
  12. 根据权利要求1至11中任一项所述的方法，其特征在于，所述终端设备发送所述矩阵信息的周期长于所述终端设备发送所述向量信息的周期。
  13. 一种用于反馈信道状态信息的方法，其特征在于，所述方法包括：
    网络设备接收终端设备发送的降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；
    所述网络设备接收所述终端设备发送的下行等效信道的特征向量的向量信息；
    所述终端设备根据所述矩阵信息和所述向量信息，确定预编码矩阵；
    其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；
    所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
  14. 根据权利要求13所述的方法，其特征在于，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道接收的。
  15. 根据权利要求13或14所述的方法，其特征在于，所述网络设备接收所述矩阵信息的周期长于所述网络设备接收所述向量信息的周期。
  16. 一种终端设备，其特征在于，所述终端设备包括：
    发送单元，所述发送单元用于：
    向网络设备发送降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；
    向所述网络设备发送下行等效信道的特征向量的向量信息，所述下行等效信道的特征向量基于所述降维矩阵得到；
    其中，所述矩阵信息包括所述降维矩阵的矩阵索引，或者，所述矩阵信息包括所述终端设备通过对所述降维矩阵的元素进行量化得到的信息；
    所述向量信息包括所述特征向量的索引，或者，所述向量信息包括所述终端设备通过对所述特征向量的元素进行量化得到的信息。
  17. 根据权利要求16所述的终端设备，其特征在于，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道发送的。
  18. 根据权利要求16或17所述的终端设备，其特征在于，所述降维矩阵是由所述终端设备根据在第一时间段接收的下行参考信号对应的信道矩阵确定的，在所述第一时间段中所述降维矩阵对应的子空间的能量是相同维度下所述下行信道对应的多个子空间中能量最高的，所述降维矩阵的各列向量之间满足正交性。
  19. 根据权利要求16至18中任一项所述的终端设备，其特征在于，所述终端设备还包括：
    第一处理单元，用于根据在第一时间段接收的下行参考信号对应的信道矩阵，确定所述降维矩阵。
  20. 根据权利要求19所述的终端设备，其特征在于，所述第一处理单元具体用于：
    根据所述在第一时间段接收的下行参考信号对应的信道矩阵，计算第一协方差矩阵，所述第一信道协方差矩阵用于表征所述第一时间段对应的下行信道的统计特性；
    根据所述第一协方差矩阵，计算所述降维矩阵。
  21. 根据权利要求20所述的终端设备，其特征在于，所述第一处理单元具体用于：
    计算所述终端设备在第一时间段接收的下行参考信号对应的信道矩阵中每个信道矩阵的协方差矩阵；
    通过对相同时刻接收的下行参考信号对应的协方差矩阵进行平均，得到多个第二协方差矩阵，所述多个第二协方差矩阵与所述第一时间段包括的多个时刻一一对应；
    对所述多个第二协方差矩阵进行平均或时间上的滤波，得到所述第一协方差矩阵。
  22. 根据权利要求19所述的终端设备，其特征在于，所述第一处理单元具体用于：
    根据所述在第一时间段接收的下行参考信号对应的信道矩阵，从预设的降维矩阵集合中确定所述降维矩阵，所述降维矩阵的矩阵信息包括所述降维矩阵在所述预设的降维矩阵集合的矩阵索引。
  23. 根据权利要求22所述的终端设备，其特征在于，所述降维矩阵的每一列对应的波束方向图相同。
  24. 根据权利要求16至23中任一项所述的终端设备，其特征在于，所述终端设备还包括：
    第二处理单元，用于根据所述降维矩阵，通过对第一时刻接收的下行参考信号对应的信道矩阵进行降维，确定所述第一时刻接收的下行参考信号对应的下行等效信道的特征向量。
  25. 根据权利要求24所述的终端设备，其特征在于，所述第二处理单元具体用于：
    根据所述降维矩阵，通过对所述第一时刻的接收的下行参考信号对应的信道矩阵进行降维，得到所述第一时刻接收的下行参考信号对应的等效矩阵；
    计算所述第一时刻接收的下行参考信号对应的等效矩阵中每个等效矩阵的协方差矩阵；
    通过对第一频域资源区域对应的协方差矩阵进行平均，得到所述第一资源区域对应的第三协方差矩阵，其中，所述第一频域资源区域对应的协方差矩阵包括在所述第一频域资源区域中所述第一时刻接收的下行参考信号对应的等效矩阵的协方差矩阵；
    根据所述第三协方差矩阵，确定在所述第一频域资源区域中所述下行等效信道的特征向量，所述第一频域资源区域包括全带宽或局部带宽。
  26. 根据权利要求16至25中任一项所述的终端设备，其特征在于，所述下行等效信道的特征向量包括r个特征向量，其中，r由所述网络设备配置或r与所述终端设备支持的数据流的数目相同，所述r个特征向量中任一个特征向量对应的特征值大于或等于所述下行等效信道的特征向量除所述r个特征向之外的任一个特征向量对应的特征值，r≥1。
  27. 根据权利要求16至26中任一项所述的终端设备，其特征在于，所述发送单元发送所述矩阵信息的周期长于所述发送单元发送所述向量信息的周期。
  28. 一种网络设备，其特征在于，所述网络设备包括：
    接收单元，所述接收单元用于：
    接收终端设备发送的降维矩阵的矩阵信息，所述降维矩阵的第一维度与所述网络设备的发送天线端口的数量相同，且所述降维矩阵的第二维度小于所述降维矩阵的第一维度；
    接收所述终端设备发送的下行等效信道的特征向量的向量信息；
    处理单元，用于根据所述矩阵信息和所述向量信息，确定预编码矩阵；
    其中，所述矩阵信息包括所述处理单元通过对所述降维矩阵的元素进行量化得到的信息，和/或所述向量信息包括所述处理单元通过对所述特征向量的元素进行量化得到的信息。
  29. 根据权利要求28所述的网络设备，其特征在于，所述降维矩阵的矩阵信息和所述特征向量的向量信息中至少一个是通过上行数据信道接收的。
  30. 根据权利要求28或29所述的网络设备，其特征在于，所述接收单元接收所述矩阵信息的周期长于所述接收单元接收所述向量信息的周期。
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