WO2020248108A1 - 数据传输方法及装置 - Google Patents

数据传输方法及装置 Download PDF

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Publication number
WO2020248108A1
WO2020248108A1 PCT/CN2019/090618 CN2019090618W WO2020248108A1 WO 2020248108 A1 WO2020248108 A1 WO 2020248108A1 CN 2019090618 W CN2019090618 W CN 2019090618W WO 2020248108 A1 WO2020248108 A1 WO 2020248108A1
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Prior art keywords
matrix
nss
noise ratio
channel
unitary
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PCT/CN2019/090618
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English (en)
French (fr)
Inventor
阮卫
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华为技术有限公司
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Application filed by 华为技术有限公司 filed Critical 华为技术有限公司
Priority to CN201980097036.7A priority Critical patent/CN113906696B/zh
Priority to PCT/CN2019/090618 priority patent/WO2020248108A1/zh
Publication of WO2020248108A1 publication Critical patent/WO2020248108A1/zh

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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
    • H04B7/08—Diversity systems; Multi-antenna system, i.e. transmission or reception using multiple antennas using two or more spaced independent antennas at the receiving station
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L1/00—Arrangements for detecting or preventing errors in the information received
    • H04L1/02—Arrangements for detecting or preventing errors in the information received by diversity reception
    • H04L1/06—Arrangements for detecting or preventing errors in the information received by diversity reception using space diversity
    • H—ELECTRICITY
    • H04—ELECTRIC COMMUNICATION TECHNIQUE
    • H04L—TRANSMISSION OF DIGITAL INFORMATION, e.g. TELEGRAPHIC COMMUNICATION
    • H04L25/00—Baseband systems
    • H04L25/02—Details ; arrangements for supplying electrical power along data transmission lines

Definitions

  • This application relates to the field of communication technology, and in particular to a data transmission method and device.
  • TxBF transmit beamforming
  • the transmitting end when multiple antennas at the transmitting end are weighted, the transmitting end sends a channel assessment frame (sounding) to the receiving end.
  • the receiving end After the receiving end receives the channel assessment frame, it performs fast Fourier transformation (FFT)
  • FFT fast Fourier transformation
  • U and V are unitary matrices
  • S is a diagonal matrix
  • the receiving end sends V as a weight feedback matrix to the sending end
  • the sending end uses the V matrix to weight the transmission signal.
  • the embodiments of the present application provide a data transmission method and device, which provide an alternative solution for determining the assignment matrix of the transmitting end for improving the quality of the received signal at the receiving end.
  • an embodiment of the present application provides a data transmission method, including:
  • the detection signal is received through M receiving antennas; where the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2; the channel matrix is calculated according to the detection signal; the first matrix is obtained according to the channel matrix ;
  • the first matrix includes: the first Nss column of the first unitary matrix, Nss is the smaller value of M and N; the first unitary matrix is: N*N obtained by performing singular value decomposition SVD on the channel matrix
  • the detection signal is first received through M receiving antennas; wherein the detection signal is sent by the transmitting end through N transmitting antennas; both M and N are greater than or Equal to 2; then calculate the channel matrix according to the detection signal; perform singular value decomposition SVD on the channel matrix to obtain the first matrix; where the first matrix includes: the first Nss column of the first unitary matrix, and Nss is the smaller value of M and N ;
  • the first unitary matrix is: the N*N matrix obtained by performing SVD on the channel matrix; unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used for the transmitting end to assign weights to N transmitting antennas;
  • the sending end sends the second matrix; the sending end can use the second matrix to assign values to multiple sending antennas to improve the quality of the received signal at the receiving end.
  • performing a unitary transformation on the first matrix to obtain the second matrix includes:
  • the preset matrix includes: a normalized discrete Fourier transform DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the preset matrix includes: Givens transformation Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi, where:
  • Np (Nss-1)/2
  • I n,n represents a unit matrix with n rows and n columns
  • I m,m represents a unit matrix with m rows and m columns
  • 0 m,1 represents m rows and 1 column
  • S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • performing a unitary transformation on the first matrix to obtain the second matrix includes: when the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition, Unitary transformation is performed on the first matrix to obtain the second matrix; wherein, the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset Supposing conditions include: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas;
  • the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the ratio of the signal-to-noise ratio between the spatial streams formed by the sending end through the weight assignment of the first unitary matrix Maximum difference.
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel can further improve the signal quality.
  • the method further includes:
  • the fourth matrix includes: the first Nss rows and the first Nss columns of the diagonal matrix, and the diagonal matrix is : The singular value matrix obtained by performing SVD on the channel matrix; send the output signal-to-noise ratio of each spatial stream to the sending end.
  • determining, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment includes: the channel state satisfies the first preset condition, the second preset condition, and In the case of at least one of the third preset conditions, determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment according to the fourth matrix; wherein, the first preset The conditions include: the received signal strength indicator RSSI of the M receiving antennas is greater than the first threshold and less than the second threshold; the second preset condition includes: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where , The condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas; the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold; The maximum ratio difference is the maximum difference in the signal-to-noise ratio between the spatial streams formed
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment it is determined whether to determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment, which avoids blindly determining that the sending end uses the second matrix for weight assignment.
  • the output signal-to-noise ratio of each spatial stream consumes computing resources.
  • determining, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment includes:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same, so the MIMO system equalizes the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sending end and the receiving end.
  • Package rate the MIMO system equalizes the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sending end and the receiving end.
  • determining the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment according to the fourth matrix includes:
  • the output signal-to-noise ratio of each spatial stream formed by the sending end using the second matrix for weight assignment is:
  • the second matrix is obtained by performing Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is between
  • the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art is lower than the maximum difference between the output signal-to-noise ratios of any two spatial streams in the prior art. Therefore, the signal processing of each spatial stream by the MIMO system is more balanced compared to the prior art, which can solve the problem to a greater extent
  • the corner effect reduces the packet error rate between the sending end and the receiving end.
  • condition number CN of the channel matrix is calculated by the following formula:
  • S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • obtaining the first matrix according to the channel matrix includes: performing SVD on the channel matrix to obtain the first unitary matrix; and selecting the first Nss columns of the first unitary matrix to obtain the first matrix.
  • an embodiment of the present application provides a data transmission device, including:
  • the detection signal receiving module is used to receive the detection signal through M receiving antennas; wherein, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2.
  • the channel matrix calculation module is used to calculate the channel matrix according to the detection signal.
  • the matrix obtaining module is configured to obtain a first matrix according to the channel matrix; wherein, the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: The N*N matrix obtained by performing SVD on the channel matrix.
  • the unitary transformation module is used to perform unitary transformation on the first matrix to obtain the second matrix
  • the matrix sending module is configured to send the second matrix to the sending end to instruct the sending end to use the second matrix to perform weight assignment on the N sending antennas.
  • the detection signal is first received through M receiving antennas; among them, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2; then the channel matrix is calculated according to the detection signal;
  • the singular value decomposition SVD obtains the first matrix; where the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: N obtained by SVD on the channel matrix *N matrix; Unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used by the transmitting end to assign weights to N transmitting antennas; the second matrix is sent to the transmitting end; the transmitting end can use the second matrix Assign values to multiple transmit antennas to improve the quality of the received signal at the receiving end.
  • the unitary transformation module includes:
  • the first unitary transformation sub-module is configured to multiply the first matrix by the preset matrix to obtain a third matrix; replace the first Nss column of the first unitary matrix with the third matrix to obtain the second matrix.
  • the preset matrix includes: a normalized discrete Fourier transform DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the preset matrix includes: Givens transformation Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi, where:
  • Np (Nss-1)/2
  • I n,n represents a unit matrix with n rows and n columns
  • I m,m represents a unit matrix with m rows and m columns
  • 0 m,1 represents m rows and 1 column
  • S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • the unitary transformation module includes: a second unitary transformation sub-module, which is configured to perform a correction when the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition.
  • the first matrix is subjected to unitary transformation to obtain the second matrix; wherein, the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset The conditions include: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas;
  • Three preset conditions include: the maximum difference in signal-to-noise ratio is greater than the fifth threshold; the maximum difference in signal-to-noise ratio is the maximum signal-to-noise ratio between the spatial streams formed by the sending end through the first unitary matrix weight assignment Difference.
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel can further improve the signal quality.
  • the device further includes:
  • the output signal-to-noise ratio determining module is configured to determine, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment; the fourth matrix includes: the first Nss rows of the diagonal matrix In the first Nss column, the diagonal matrix is: the singular value matrix obtained by performing SVD on the channel matrix.
  • the output signal-to-noise ratio sending module is used to send the output signal-to-noise ratio of each spatial stream to the sending end.
  • the output signal-to-noise ratio determination module includes: a first output signal-to-noise ratio determination submodule, configured to satisfy at least one of a first preset condition, a second preset condition, and a third preset condition when the channel state
  • the fourth matrix is used to determine the output signal-to-noise ratio of each spatial stream formed by the transmitting end using the second matrix for weight assignment
  • the first preset condition includes: The received signal strength indicator RSSI is greater than the first threshold and less than the second threshold
  • the second preset condition includes: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, wherein the condition number is used to identify the N
  • the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold
  • the maximum difference of the signal-to-noise ratio is that the transmitting end passes The maximum difference in the signal-to-noise ratio
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment it is determined whether to determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment, which avoids blindly determining that the sending end uses the second matrix for weight assignment.
  • the output signal-to-noise ratio of each spatial stream consumes computing resources.
  • determining, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment includes:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same. Therefore, the MIMO system balances the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sender and the receiver. Package rate.
  • the output signal-to-noise ratio determination module includes: a second output signal-to-noise ratio determination sub-module, configured to determine, according to the fourth matrix, the output signal of each spatial stream formed after the sending end uses the second matrix to perform weight assignment.
  • the noise ratio is:
  • the second matrix is obtained by performing Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is between
  • the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art is lower than the maximum difference between the output signal-to-noise ratios of any two spatial streams in the prior art. Therefore, the signal processing of each spatial stream by the MIMO system is more balanced compared to the prior art, which can solve the problem to a greater extent
  • the corner effect reduces the packet error rate between the sending end and the receiving end.
  • condition number CN of the channel matrix is calculated by the following formula:
  • S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • the matrix acquisition module includes: a matrix acquisition sub-module configured to perform SVD on the channel matrix to obtain the first unitary matrix; and select the first Nss columns of the first unitary matrix to obtain the first matrix.
  • an embodiment of the present application provides a communication device, including a processor, and a transceiver coupled to the processor.
  • the transceiver is used for receiving detection signals through M receiving antennas; wherein, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2.
  • the processor is configured to calculate the channel matrix according to the detection signal.
  • the processor is configured to obtain a first matrix according to the channel matrix; wherein, the first matrix includes: the first Nss columns of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: The N*N matrix obtained by performing singular value decomposition SVD on the channel matrix.
  • the processor is configured to perform unitary transformation on the first matrix to obtain a second matrix
  • the transceiver is configured to send the second matrix to the sending end to instruct the sending end to use the second matrix to perform weight assignment on the N sending antennas.
  • the detection signal is first received through M receiving antennas; among them, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2; then the channel matrix is calculated according to the detection signal;
  • the singular value decomposition SVD obtains the first matrix; where the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: N obtained by SVD on the channel matrix *N matrix; Unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used by the transmitting end to assign weights to N transmitting antennas; the second matrix is sent to the transmitting end; the transmitting end can use the second matrix Assign values to multiple transmit antennas to improve the quality of the received signal at the receiving end.
  • the processor is configured to right-multiply the first matrix by a preset matrix to obtain a third matrix; replace the first Nss columns of the first unitary matrix with the third matrix to obtain the second matrix.
  • the preset matrix includes: a normalized discrete Fourier transform DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the preset matrix includes: Givens transformation Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi, where:
  • Np (Nss-1)/2
  • I n,n represents a unit matrix with n rows and n columns
  • I m,m represents a unit matrix with m rows and m columns
  • 0 m,1 represents m rows and 1 column
  • S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • the processor is configured to perform a unitary transformation on the first matrix when the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition, Obtain the second matrix; wherein, the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset condition includes: the maximum value of the channel matrix The condition number is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas; the third preset condition includes: signal noise The maximum difference of the ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the maximum difference of the signal-to-noise ratio between the spatial streams formed after the sending end performs the weight assignment through the first unitary matrix.
  • the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel can further improve the signal quality.
  • the processor is configured to determine, according to a fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment;
  • the fourth matrix includes: the first Nss of the diagonal matrix In the Nss column before the row, the diagonal matrix is: the singular value matrix obtained by performing SVD on the channel matrix.
  • the transceiver is used to send the output signal-to-noise ratio of each spatial stream to the sending end.
  • the processor is configured to determine the sending end according to the fourth matrix when the channel state satisfies at least one of a first preset condition, a second preset condition, and a third preset condition
  • the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than the first threshold and less than the second threshold
  • the second preset condition includes: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the spatial flow between the N transmit antennas and the M receive antennas
  • the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the value of the spatial stream formed by the sending end through the weight assignment of the first unitary matrix The maximum difference between the signal-to-noise ratio.
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment it is determined whether to determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment, which avoids blindly determining that the sending end uses the second matrix for weight assignment.
  • the output signal-to-noise ratio of each spatial stream consumes computing resources.
  • the processor is used to:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same. Therefore, the MIMO system balances the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sender and the receiver. Package rate.
  • the processor is configured to determine, according to the fourth matrix, that the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment is:
  • the second matrix is obtained by performing Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is between
  • the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art is lower than the maximum difference between the output signal-to-noise ratios of any two spatial streams in the prior art. Therefore, the signal processing of each spatial stream by the MIMO system is more balanced compared to the prior art, which can solve the problem to a greater extent
  • the corner effect reduces the packet error rate between the sending end and the receiving end.
  • condition number CN of the channel matrix is calculated by the following formula:
  • S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • the processor is configured to perform SVD on the channel matrix to obtain the first unitary matrix; select the first Nss columns of the first unitary matrix to obtain the first matrix.
  • an embodiment of the present application provides a device, including: a processor and a memory; wherein the memory is used to store program instructions; the processor is used to call and execute the program instructions stored in the memory to implement such Any of the methods of the first aspect.
  • an embodiment of the present application provides a communication system, including a receiving end and a sending end, the receiving end is configured to perform the method according to any one of the first aspect, and the sending end is configured to use the second matrix to N transmitting antennas perform weight assignment.
  • an embodiment of the present application provides a computer-readable storage medium that stores an instruction, and when the instruction is executed, the computer executes the method as in any one of the first aspect of the present application.
  • an embodiment of the present application provides a computer program product.
  • the computer program product includes an instruction.
  • the instruction executes the method described in any one of the first aspect of the present application.
  • the data transmission method and device of the embodiments of the present application provide an alternative solution for determining the assignment matrix of the transmitting end.
  • the detection signal is first received through M receiving antennas; where the detection signal is that the transmitting end passes through N
  • the transmission antenna is sent; M and N are both greater than or equal to 2; then the channel matrix is calculated according to the detection signal; the channel matrix is subjected to singular value decomposition SVD to obtain the first matrix; where the first matrix includes: the first Nss columns of the first unitary matrix , Nss is the smaller value of M and N; the first unitary matrix is: the N*N matrix obtained by SVD on the channel matrix; unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used for sending
  • the terminal performs weight assignment on the N transmitting antennas; sends the second matrix to the transmitting terminal; the transmitting terminal can use the second matrix to assign values to multiple transmitting antennas to improve the quality of the received signal at the receiving terminal.
  • FIG. 1 is a schematic diagram of channels of an antenna array of a MIMO system according to an embodiment of the application
  • FIG. 2 is an architecture diagram of a MIMO system applied in an embodiment of the application
  • FIG. 3 is a schematic flowchart of a data transmission method provided by an embodiment of the application.
  • FIG. 4 is a schematic diagram of another process of a data transmission method provided by an embodiment of the application.
  • FIG. 5 is a schematic diagram of the functional structure of a device provided by an embodiment of the application.
  • Fig. 6 is a schematic structural diagram of a device provided by an embodiment of the application.
  • the data transmission method and device provided in the embodiments of this application can be applied to a MIMO system.
  • the MIMO system can specifically refer to the use of multiple transmitting antennas and receiving antennas at the transmitting end and the receiving end respectively, so that signals are transmitted through multiple antennas on the transmitting end and the receiving end. And receive.
  • Figure 1 is a schematic diagram of the channels of the antenna array of the MIMO system.
  • the transmitting end may have N transmitting antennas
  • the receiving end may have M receiving antennas.
  • the values of M and N may be the same or different.
  • M may be greater than N or less than N, which is not limited in this application.
  • orthogonal frequency division multiplexing when data transmission is performed between N transmitting antennas and M receiving antennas, orthogonal frequency division multiplexing (OFDM) can be used.
  • OFDM is multi-carrier modulation (MCM).
  • MCM multi-carrier modulation
  • the main idea of OFDM is: divide the channel into several orthogonal sub-channels, convert high-speed data signals into parallel low-speed sub-data streams, modulate them to be transmitted on each sub-channel, and orthogonal signals can pass through at the receiving end
  • Relevant technology is used to separate, which can reduce the mutual interference between sub-channels, and the signal bandwidth on each sub-channel is less than the relevant bandwidth of the channel, so each sub-channel can be regarded as flat fading, which can eliminate inter-symbol interference.
  • the bandwidth of each sub-channel is only a small part of the original channel bandwidth, channel equalization becomes relatively easy.
  • Fig. 2 is an architecture diagram of a MIMO system applied in an embodiment of the application.
  • the MIMO system may specifically include a base station 110 and a terminal device 120.
  • the base station 110 and the terminal device 120 may establish uplink and/or downlink connections, and these connections are used to transmit data from the terminal device 120 to the base station 110, and vice versa.
  • the data transmitted through the uplink/downlink connection may include data transmitted between the terminal devices 120 and the like. It can be understood that in practical applications, there may be multiple terminal devices 120.
  • the communication process between each terminal device 120 and the base station 110 is similar, in the embodiment of the present application, the communication between any terminal device 120 and the base station 110 is used. The communication process is explained as an example.
  • the base station involved in the embodiments of the present application may also be referred to as a radio access network (radio access network, RAN) device.
  • the base station can be a base station (BTS) in global system of mobile communication (GSM) or code division multiple access (CDMA), or it can be a wideband code division multiple access (wideband code).
  • the base station (nodeB, NB) in division multiple access (WCDMA) can also be an evolved base station (evolutional node B, eNB or eNodeB) in long term evolution (LTE), or a relay station or access point, or
  • the base stations in the future 5G network are not limited here. Among them, the base station in the 5G network can also be called gNB.
  • the terminal device involved in the embodiment of the present application may be a wired terminal or a wireless terminal.
  • the wireless terminal may be a device with a wireless transceiver function.
  • the terminal devices involved in the embodiments of this application can be deployed on land, including indoor or outdoor, handheld or vehicle-mounted; they can also be deployed on water (such as ships); they can also be deployed in the air (such as airplanes, balloons, and satellites). ).
  • the terminal device involved in the embodiment of the present application may be a user equipment (UE), where the UE includes a handheld device with a wireless communication function, a vehicle-mounted device, a wearable device, or a computing device.
  • UE user equipment
  • the UE may be a mobile phone, a tablet computer, or a computer with wireless transceiver function.
  • Terminal equipment can also be virtual reality (VR) terminal equipment, augmented reality (augmented reality, AR) terminal equipment, wireless terminals in industrial control, wireless terminals in unmanned driving, wireless terminals in telemedicine, and smart Wireless terminals in power grids, wireless terminals in smart cities, wireless terminals in smart homes, and so on.
  • the device that implements the function of the terminal may be a terminal or a device that supports the terminal to implement the function.
  • the terminal device or base station involved in the embodiments of the present application may include a hardware layer, an operating system layer running on the hardware layer, and an application layer running on the operating system layer.
  • This hardware layer includes hardware such as central processing unit (dentral processing unit, CPU), memory management unit (memory management unit, MMU), and memory (also called main memory).
  • the operating system may be any one or more computer operating systems that implement business processing through processes, for example, Linux operating system, Unix operating system, Android operating system, iOS operating system, or windows operating system.
  • the application layer includes applications such as browsers, address books, word processing software, and instant messaging software.
  • the device that executes the terminal device (or called terminal) side method may be a terminal device or a device in the terminal device.
  • the device in the terminal device may be a chip system, a circuit, or a module, etc., which is not limited in this application.
  • the sending end in the embodiment of the present application may be a device that executes the method on the terminal device side.
  • the device that executes the base station side method may be a base station or a device in the base station.
  • the device in the base station may be a chip system, a circuit, or a module, etc., which is not limited in this application.
  • the receiving end in the embodiment of the present application may be a device that executes the base station side method.
  • FIG. 3 is a schematic flowchart of the data transmission method provided in Embodiment 1 of this application; as shown in FIG. 3, the method provided in this embodiment of the present application may include the following steps:
  • Step S201 The transmitting end sends a detection signal to M receiving antennas at the receiving end through N transmitting antennas.
  • the detection signal may be used for signal detection between the transmitting end and the receiving end.
  • the detection signal may specifically be a channel evaluation frame (sounding), a sounding reference signal (SRS), or other signals, which are not limited in the embodiment of the present application.
  • Step S202 The receiving end calculates a channel matrix according to the detection signal.
  • the detection signal can be first transformed by fast fourier transformation (FFT). Transform to the frequency domain to obtain multiple subcarriers, then extract the signal on each subcarrier, perform channel estimation on each subcarrier, and obtain the channel matrix H.
  • FFT fast fourier transformation
  • H is a 2x4 matrix.
  • h00, h01, h02, h03, h10, h11, h12, and h13 are the channel responses on each channel of the receiving end and the sending end.
  • Step S203 The receiving end obtains a first matrix according to the channel matrix; where the first matrix includes: the first Nss column of the first unitary matrix, and Nss is the smaller value of M and N; the first unitary matrix is:
  • the channel matrix is an N*N matrix obtained by performing singular value decomposition SVD.
  • the receiving end can perform SVD decomposition on the channel matrix to obtain three matrices U, V and S, where U is a unitary matrix of M*M, V is a unitary matrix of N*N, and S is The diagonal matrix of M*N, the SVD decomposition of the matrix is the prior art, which will not be repeated here, the first unitary matrix in the embodiment of the present application is the V matrix, and the first matrix may be the first Nss column in the V matrix The matrix of composition. In specific applications, after the V matrix is obtained, the first Nss columns can be selected from the V matrix to obtain the first matrix.
  • Step S204 The receiving end performs unitary transformation on the first matrix to obtain a second matrix.
  • unitary transformation refers to an equal metric transformation in a unitary space.
  • the unitary transform may be a normalized discrete Fourier transform (DFT) or a Givens transform.
  • DFT discrete Fourier transform
  • Givens transform Givens transform
  • the receiving end performs unitary transformation on the first matrix, and the second matrix obtained may be:
  • the preset matrix may be a DFT matrix or a Givens matrix.
  • the embodiment of the present application does not specifically limit the preset matrix.
  • the receiving end performs a unitary transformation on the first matrix to obtain the second matrix: when the channel state satisfies the first preset condition, the second preset condition, and the third preset condition In the case of at least one condition of, perform unitary transformation on the first matrix to obtain the second matrix.
  • the first preset condition includes: the received signal strength indication (RSSI) of the M receiving antennas is greater than a first threshold and less than a second threshold;
  • the second preset condition includes: the channel matrix The maximum condition number is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas;
  • the third preset condition includes: The maximum difference of the noise ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the maximum difference of the signal-to-noise ratio between the spatial streams formed after the sending end performs the weight assignment through the first unitary matrix.
  • the unitary transformation of the first matrix is not effective in improving the signal quality. Therefore, in the embodiment of the present application, the channel state meets the first preset condition, the second preset condition, and the third preset In the case of at least one of the conditions, unitary transformation is performed on the first matrix to obtain the second matrix.
  • the first preset condition is a condition related to the signal strength indicator RSSI.
  • the RSSI is greater than the first threshold and less than the second threshold.
  • the value of the first threshold is determined by the minimum signal strength that can be demodulated in a MIMO system composed of M receiving antennas and N transmitting antennas.
  • the value of the first threshold is determined by Ensure that the number of spatial streams sent by the sender is greater than or equal to 2, because if the signal strength is too low, the sender will send a signal with a single spatial stream, and the method of the embodiment of the present application will have a negative benefit in a single spatial stream;
  • the second threshold The selection is determined by the maximum signal strength value of the linear working area of the signal-to-noise ratio of the receiving end.
  • the signal-to-noise ratio of the receiving end increases linearly with the signal strength, and when the signal strength exceeds a certain value
  • the signal-to-noise ratio does not increase with the increase of signal strength
  • the method of the embodiment of the present application is adapted to the linear working area, so the signal-to-noise ratio can be changed without increasing the signal strength.
  • the signal strength corresponding to the increase is determined to be the maximum signal strength value of the linear working area
  • the second threshold may correspond to the maximum signal strength value of the linear working area.
  • the first threshold may be a value between -100 and 10 dBm, such as -70 dBm
  • the second threshold may be a value between -100 and 10 dBm, such as -30 dBm.
  • the second preset condition is a condition related to the maximum condition number of the channel matrix.
  • the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold.
  • the value of the third threshold is related to the error correction capability of the channel decoding at the receiving end, which can be determined by simulation in practical applications. For example, it is about 9dB in WiFi.
  • the condition number is less than this value, the compatibility of single stream is considered. It is not necessary to use the unitary matrix transformation of this application; the value of the fourth threshold is related to the scheduling algorithm of the sending end, which can be given through testing in practical applications.
  • the sending end The probability of sending a single spatial stream is relatively large.
  • the fourth threshold can be selected about 30 dB.
  • the condition number is used to identify the correlation between spatial streams in a MIMO system composed of M receiving antennas and N transmitting antennas.
  • the correlation between spatial streams may be the orthogonality of spatial streams.
  • the condition number CN of the channel matrix is calculated by the following formula: Wherein, S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • the logarithm of the condition number can be defined as The unit is dB.
  • the third preset condition is a condition related to the maximum difference of the signal-to-noise ratio.
  • the maximum difference of the signal-to-noise ratio of each spatial stream is greater than the fifth threshold.
  • the value of the fifth threshold is related to the error correction capability of the channel decoding at the receiving end, which can be determined by simulation in practical applications, such as wireless fidelity (Wireless-Fidelity, WiFi), when the signal-to-noise ratio is the largest When the difference is less than this value, considering the compatibility of the single stream, it is not necessary to adopt the unitary matrix transformation of this application.
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel state can further improve the signal quality.
  • Step S205 The receiving end sends the second matrix to the sending end to instruct the sending end to use the second matrix to perform weight assignment on the N sending antennas.
  • the second matrix is used as the assignment matrix of the sending end.
  • the receiving end may also compress the second matrix into two angle vectors phi and psi, and then send it to the sending end, which is not specifically limited in the embodiment of the present application.
  • step S206 the transmitting end weights the N transmitting antennas according to the second matrix.
  • the transmitting end may weight the transmission signal according to the second matrix, thereby improving the quality of the received signal. It can be understood that if the sending end receives the compressed second matrix, it can decompress and restore the second matrix according to the method defined by the compression protocol of the second matrix, which is not specifically limited in the embodiment of the present application.
  • the receiving end may also determine, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment;
  • the fourth matrix includes : The first Nss row and the first Nss column of the diagonal matrix.
  • the diagonal matrix is: a singular value matrix obtained by performing SVD on the channel matrix; send the output signal-to-noise ratio of each spatial stream to the sending end.
  • the receiving end not only performs unitary transformation on the first matrix to obtain the second matrix, but also determines the output signal of each spatial stream formed by the transmitting end using the second matrix for weight assignment through the fourth matrix.
  • the noise ratio is used to feed back the signal processing capability of each spatial stream through the output signal-to-noise ratio of each spatial stream.
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment, and the output of each spatial stream
  • the signal-to-noise ratio may be consistent or inconsistent.
  • the embodiment of the present application does not limit the specific method for determining the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment.
  • determining, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment includes:
  • the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition, it is determined according to the fourth matrix that the transmitting end uses the second matrix to perform weight assignment.
  • the output signal-to-noise ratio of each spatial stream wherein the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset condition includes: the The maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas; the third preset condition Including: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the maximum difference of the signal-to-noise ratio between the spatial streams formed after the sending end performs weight assignment through the first unitary matrix.
  • the receiving end obtains the second matrix by performing unitary transformation on the first unitary matrix, so that the transmitting end can weight the transmission signal of the transmitting antenna according to the second matrix.
  • the transmission signal of the transmitting antenna is weighted and transmitted through the V matrix in the SVD. Therefore, the embodiment of the present application provides an alternative solution for weighting the transmitting antenna.
  • the inventor of the present application has discovered through a lot of research that, in the prior art technical solution in which the sender uses the V matrix to weight the transmission signal, the packet error rate between the receiver and the sender is often high.
  • the V matrix is the matrix obtained by SVD decomposition of the channel matrix by the receiving end, and the V matrix is the unitary matrix.
  • the corner effect specifically refers to: when the distance between the sending end and the receiving end is constant, Changing the relative position of the transmitting end and the receiving end, such as changing the antenna placement direction, etc., the throughput between the transmitting end and the receiving end will change significantly, and the packet error rate will increase significantly; and the inventor further found that the corner effect occurs
  • the main reason is: after the relative position of the transmitting end and the receiving end are changed, the output signal-to-noise ratio of each spatial stream of MIMO is different, which leads to unbalanced signal processing of each spatial stream, and a spatial stream with a small output signal-to-noise ratio will appear. Cannot be decoded correctly.
  • the output signal-to-noise ratios of the two spatial streams are respectively with Among them, s0 and s1 are the singular values of the channel matrix, and ⁇ 2 is the average value of the noise variance of the M receiving antennas, because the difference between s0 and s1 in the prior art is usually large.
  • s0 is much larger than s1, resulting in s0
  • the output signal-to-noise ratio of s1 can meet the demodulation requirements, s1 is too small, and the output signal-to-noise ratio corresponding to s1 is too small, resulting in the failure of demodulation of the spatial stream corresponding to s1, resulting in packet demodulation failure.
  • the inventor further researched and determined that when the unitary transformation is performed on the first matrix of the first embodiment, when the unitary transformation is DFT transformation or Givens transformation, the corner effect can be effectively improved, and the transmitting end and receiving end can be reduced. Packet error rate between terminals.
  • the second embodiment of the present application provides a data transmission method.
  • the second embodiment of the present application is a specific implementation of step S204 in the foregoing embodiment 1.
  • the unitary transformation is DFT transformation
  • the preset matrix is A unified discrete Fourier transform DFT matrix
  • the receiving end obtains the third matrix by multiplying the first matrix to the right by the DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment according to the fourth matrix in Embodiment 1 of the present application includes:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the number of transmitting antennas is 2, and the number of receiving antennas is also 2, there may be two spatial streams between the receiving antenna and the transmitting antenna.
  • the fourth matrix S can be:
  • the DFT matrix can be:
  • the second matrix Vnew can be:
  • the output signal-to-noise ratio of the spatial stream postSNR 0 and postSNR 1 are both:
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same. Therefore, the MIMO system balances the signal processing of each spatial stream, thereby solving the corner effect to a greater extent and reducing the gap between the sending end and the receiving end.
  • the packet error rate is the same.
  • the third embodiment of the present application provides a data transmission method.
  • the third embodiment of the present application is another specific implementation of step S204 of the above-mentioned embodiment.
  • the unitary transformation is the Givens transformation
  • the preset matrix is Givens matrix
  • the receiving end obtains the third matrix by multiplying the first matrix to the right by the Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi.
  • Np (Nss-1)/2; I n,n represents a unit matrix with n rows and n columns, and Im,m represents a unit matrix with m rows and m columns; 0 m,1 represents m rows 1 Column 0 matrix; S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment according to the fourth matrix in Embodiment 1 of the present application includes:
  • the output signal-to-noise ratio of each spatial stream formed by the sending end using the second matrix for weight assignment is:
  • the number of receiving antennas is 2, the number of transmitting antennas is not less than 2, and Nss is 2, there can be two spatial streams between the receiving antenna and the transmitting antenna.
  • the third matrix P is the first matrix V1 multiplied by G1.
  • the number of receiving antennas is 4, the number of transmitting antennas is not less than 4, and Nss is 4, there can be four spatial streams between the receiving antenna and the transmitting antenna.
  • G2 is:
  • Nss is the smaller value of Nrx and Ntx, and there may be Nss spatial streams between the receiving antenna and the transmitting antenna.
  • Nss is an even number greater than 2
  • Np Nss/2.
  • G1, G2,...,GNp are the extended Givens matrix.
  • I is a unit matrix
  • I m,m represents a unit matrix with m rows and m columns.
  • 0 m,1 represents a 0 matrix with m rows and 1 column.
  • Nss is an odd number greater than 2
  • Np (Nss-1)/2
  • other calculation methods are the same as the case where Nss is an even number greater than 2, which will not be repeated here.
  • the second matrix is obtained by performing the Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is The maximum difference between is lower than the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art, so the signal processing of each spatial stream by the MIMO system is more balanced than the prior art, and thus can be larger To solve the corner effect to a degree, reduce the packet error rate between the sender and the receiver.
  • FIG. 4 shows a schematic diagram of a specific flow of a data transmission method according to Embodiment 5 of the present application.
  • the receiving end can receive the antenna 1 signal sent by antenna 1 and the antenna 2 signal sent by antenna 2, and then perform fast Fourier transform FFT on the antenna 1 signal and antenna 2 signal respectively, and then The channel estimation of each channel is obtained, and the channel matrix H is obtained. After the singular value decomposition SVD of the channel matrix H, the first unitary matrix V can be obtained. According to the channel estimation, the signal strength estimation and the channel matrix that can be used to identify the channel state can also be obtained.
  • the unitary transformation of the embodiment of the application can be performed according to the V matrix to obtain the second matrix, and then the second matrix is compressed and fed back to the sending end through the report frame.
  • the signal The intensity estimation does not meet the first preset condition, and/or the maximum condition number of the channel matrix does not meet the second preset condition, and/or the maximum signal-to-noise ratio difference does not meet the third preset condition
  • the V matrix is not subjected to the unitary transformation of the embodiment of the application, and the V matrix is directly compressed and fed back to the transmitting end through the report frame; and, when the signal strength estimation meets the first preset condition, and/or the maximum condition number of the channel matrix meets The second preset condition, and/or, when the maximum difference of the signal-to-noise ratio satisfies the third preset condition, the channel matrix H may also be sent based on the diagonal matrix obtained by performing singular value decomposition SVD, combined with the noise variance calculation.
  • the new signal-to-noise ratio of each spatial stream formed after the weight assignment based on the second matrix is performed, and the new signal-to-noise ratio of each spatial stream is fed back to the sending end through the report frame.
  • the signal strength estimation does not meet the first preset condition
  • the maximum condition number of the channel matrix does not meet the second preset condition
  • the transmitter can be calculated according to the noise variance
  • the original signal-to-noise ratio of each spatial stream formed by the matrix weight assignment is fed back to the sending end through the report frame.
  • Table 1 shows the signal quality improvement gains of two transmitting antennas and two receiving antennas in the Quadrature Amplitude Modulation (QAM) scenario in the embodiment of the present application, as shown in Table 1:
  • QAM Quadrature Amplitude Modulation
  • the receiving end obtains the second matrix by performing unitary transformation on V, so that the transmitting end can weight the transmission signal of the transmitting antenna according to the second matrix, while the transmitting end in the prior art uses The V matrix in the SVD performs weighted transmission on the transmission signal of the transmission antenna. Therefore, the embodiment of the present application provides an alternative solution for weighting the transmission antenna to improve signal quality.
  • FIG. 5 is a schematic diagram of the functional structure of a data processing device provided by an embodiment of the present invention. As shown in FIG. 5, the device includes:
  • the detection signal receiving module 51 is configured to receive the detection signal through M receiving antennas; wherein, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2.
  • the channel matrix calculation module 52 is configured to calculate the channel matrix according to the detection signal.
  • the matrix obtaining module 53 is configured to obtain a first matrix according to the channel matrix; wherein, the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is : N*N matrix obtained by performing singular value decomposition SVD on the channel matrix.
  • the unitary transformation module 54 is configured to perform unitary transformation on the first matrix to obtain a second matrix
  • the matrix sending module 55 is configured to send the second matrix to the sending end to instruct the sending end to use the second matrix to perform weight assignment on the N transmitting antennas.
  • the detection signal is first received through M receiving antennas; among them, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2; then the channel matrix is calculated according to the detection signal;
  • the singular value decomposition SVD obtains the first matrix; where the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: N obtained by SVD on the channel matrix *N matrix; Unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used by the transmitting end to assign weights to N transmitting antennas; the second matrix is sent to the transmitting end; the transmitting end can use the second matrix Assign values to multiple transmit antennas to improve the quality of the received signal at the receiving end.
  • the unitary transformation module includes:
  • the first unitary transformation sub-module is configured to multiply the first matrix by the preset matrix to obtain a third matrix; replace the first Nss column of the first unitary matrix with the third matrix to obtain the second matrix.
  • the preset matrix includes: a normalized discrete Fourier transform DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the preset matrix includes: Givens transformation Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi, where:
  • Np (Nss-1)/2
  • I n,n represents a unit matrix with n rows and n columns
  • I m,m represents a unit matrix with m rows and m columns
  • 0 m,1 represents m rows and 1 column
  • S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • the unitary transformation module includes: a second unitary transformation sub-module, which is configured to perform a correction when the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition.
  • the first matrix is subjected to unitary transformation to obtain the second matrix; wherein, the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset The conditions include: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas;
  • Three preset conditions include: the maximum difference in signal-to-noise ratio is greater than the fifth threshold; the maximum difference in signal-to-noise ratio is the maximum signal-to-noise ratio between the spatial streams formed by the sending end through the first unitary matrix weight assignment Difference.
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel can further improve the signal quality.
  • the device further includes:
  • the output signal-to-noise ratio determining module is configured to determine, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment; the fourth matrix includes: the first Nss rows of the diagonal matrix In the first Nss column, the diagonal matrix is: the singular value matrix obtained by performing SVD on the channel matrix.
  • the output signal-to-noise ratio sending module is used to send the output signal-to-noise ratio of each spatial stream to the sending end.
  • the output signal-to-noise ratio determination module includes: a first output signal-to-noise ratio determination submodule, configured to satisfy at least one of a first preset condition, a second preset condition, and a third preset condition when the channel state
  • the fourth matrix is used to determine the output signal-to-noise ratio of each spatial stream formed by the transmitting end using the second matrix for weight assignment
  • the first preset condition includes: The received signal strength indicator RSSI is greater than the first threshold and less than the second threshold
  • the second preset condition includes: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, wherein the condition number is used to identify the N
  • the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold
  • the maximum difference of the signal-to-noise ratio is that the transmitting end passes The maximum difference in the signal-to-noise ratio
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment it is determined whether to determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment, which avoids blindly determining that the sending end uses the second matrix for weight assignment.
  • the output signal-to-noise ratio of each spatial stream consumes computing resources.
  • determining, according to the fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment includes:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same. Therefore, the MIMO system balances the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sender and the receiver. Package rate.
  • the output signal-to-noise ratio determination module includes: a second output signal-to-noise ratio determination sub-module, configured to determine, according to the fourth matrix, the output signal of each spatial stream formed after the sending end uses the second matrix to perform weight assignment.
  • the noise ratio is:
  • the second matrix is obtained by performing Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is between
  • the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art is lower than the maximum difference between the output signal-to-noise ratios of any two spatial streams in the prior art. Therefore, the signal processing of each spatial stream by the MIMO system is more balanced compared to the prior art, which can solve the problem to a greater extent
  • the corner effect reduces the packet error rate between the sending end and the receiving end.
  • condition number CN of the channel matrix is calculated by the following formula:
  • S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • the matrix acquisition module includes: a matrix acquisition sub-module configured to perform SVD on the channel matrix to obtain the first unitary matrix; and select the first Nss columns of the first unitary matrix to obtain the first matrix.
  • FIG. 6 is a schematic structural diagram of a communication device provided by an embodiment of the present invention. As shown in FIG. 6, the device includes a processor 61 and a transceiver 63 coupled to the processor.
  • the transceiver is used for receiving detection signals through M receiving antennas; wherein, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2.
  • the processor is configured to calculate the channel matrix according to the detection signal.
  • the processor is configured to obtain a first matrix according to the channel matrix; wherein, the first matrix includes: the first Nss columns of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: The N*N matrix obtained by performing singular value decomposition SVD on the channel matrix.
  • the processor is configured to perform unitary transformation on the first matrix to obtain a second matrix
  • the transceiver is configured to send the second matrix to the sending end to instruct the sending end to use the second matrix to perform weight assignment on the N sending antennas.
  • the detection signal is first received through M receiving antennas; among them, the detection signal is sent by the transmitting end through N transmitting antennas; M and N are both greater than or equal to 2; then the channel matrix is calculated according to the detection signal;
  • the singular value decomposition SVD obtains the first matrix; where the first matrix includes: the first Nss column of the first unitary matrix, where Nss is the smaller value of M and N; the first unitary matrix is: N obtained by SVD on the channel matrix *N matrix; Unitary transformation is performed on the first matrix to obtain the second matrix; the second matrix is used by the transmitting end to assign weights to N transmitting antennas; the second matrix is sent to the transmitting end; the transmitting end can use the second matrix Assign values to multiple transmit antennas to improve the quality of the received signal at the receiving end.
  • the processor is configured to right-multiply the first matrix by a preset matrix to obtain a third matrix; replace the first Nss columns of the first unitary matrix with the third matrix to obtain the second matrix.
  • the preset matrix includes: a normalized discrete Fourier transform DFT matrix.
  • DFT(k,l) represents the element in the kth row and lth column of the DFT matrix; k is an integer from 0 to Nss-1; l is an integer from 0 to Nss-1; pi is the pi.
  • the preset matrix includes: Givens transformation Givens matrix.
  • the Givens matrix includes multiple transformation matrices Gi, where:
  • Np (Nss-1)/2
  • I n,n represents a unit matrix with n rows and n columns
  • I m,m represents a unit matrix with m rows and m columns
  • 0 m,1 represents m rows and 1 column
  • S i to S Nss-1 are the singular values of the channel matrix; wherein, S i+1 is greater than or equal to S i .
  • the processor is configured to perform a unitary transformation on the first matrix when the channel state satisfies at least one of the first preset condition, the second preset condition, and the third preset condition, Obtain the second matrix; wherein, the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second threshold; the second preset condition includes: the maximum value of the channel matrix The condition number is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the correlation between the spatial streams of the N transmitting antennas and the M receiving antennas; the third preset condition includes: signal noise The maximum difference of the ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the maximum difference of the signal-to-noise ratio between the spatial streams formed after the sending end performs the weight assignment through the first unitary matrix.
  • the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than a first threshold and less than a second
  • determining whether to perform unitary transformation on the first matrix according to the specific conditions of the channel can further improve the signal quality.
  • the processor is configured to determine, according to a fourth matrix, the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment;
  • the fourth matrix includes: the first Nss of the diagonal matrix In the Nss column before the row, the diagonal matrix is: the singular value matrix obtained by performing SVD on the channel matrix.
  • the transceiver is used to send the output signal-to-noise ratio of each spatial stream to the sending end.
  • the processor is configured to determine the sending end according to the fourth matrix when the channel state satisfies at least one of a first preset condition, a second preset condition, and a third preset condition
  • the first preset condition includes: the received signal strength indicator RSSI of the M receiving antennas is greater than the first threshold and less than the second threshold
  • the second preset condition includes: the maximum condition number of the channel matrix is greater than the third threshold and less than the fourth threshold, where the condition number is used to identify the spatial flow between the N transmit antennas and the M receive antennas
  • the third preset condition includes: the maximum difference of the signal-to-noise ratio is greater than the fifth threshold; the maximum difference of the signal-to-noise ratio is the value of the spatial stream formed by the sending end through the weight assignment of the first unitary matrix The maximum difference between the signal-to-noise ratio.
  • the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment it is determined whether to determine the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix for weight assignment, which avoids blindly determining that the sending end uses the second matrix for weight assignment.
  • the output signal-to-noise ratio of each spatial stream consumes computing resources.
  • the processor is used to:
  • the output signal-to-noise ratio of each spatial stream is determined as:
  • S is the fourth matrix
  • S -1 represents the inverse of the S
  • DFT Nss ⁇ Nss S -1 is the inverse of S multiplied by the DFT matrix
  • (DFT Nss ⁇ Nss S -1 ) 1 X Nss is the DFT
  • 2 is the calculation norm for the first row of DFT Nss ⁇ Nss S -1
  • ⁇ 2 is the M The average value of the noise variance of the receiving antenna.
  • the output signal-to-noise ratio of any two spatial streams of the MIMO system is the same. Therefore, the MIMO system balances the signal processing of each spatial stream, which can solve the corner effect to a greater extent and reduce the error between the sender and the receiver. Package rate.
  • the processor is configured to determine, according to the fourth matrix, that the output signal-to-noise ratio of each spatial stream formed after the sending end uses the second matrix to perform weight assignment is:
  • the second matrix is obtained by performing Givens transformation on the first matrix, so that when the transmitting end of the MIMO system in the embodiment of the present application performs weight assignment through the second matrix, the output signal-to-noise ratio of any two spatial streams is between
  • the maximum difference between the output signal-to-noise ratio of any two spatial streams in the prior art is lower than the maximum difference between the output signal-to-noise ratios of any two spatial streams in the prior art. Therefore, the signal processing of each spatial stream by the MIMO system is more balanced compared to the prior art, which can solve the problem to a greater extent
  • the corner effect reduces the packet error rate between the sending end and the receiving end.
  • condition number CN of the channel matrix is calculated by the following formula:
  • S a and S b are both singular values of the channel matrix, a and b are both integers not less than 0, and a is less than b.
  • the processor is configured to perform SVD on the channel matrix to obtain the first unitary matrix; select the first Nss columns of the first unitary matrix to obtain the first matrix.
  • the processor may be a general-purpose processor, a digital signal processor, an application specific integrated circuit, a field programmable gate array or other programmable logic device, a discrete gate or transistor logic device, a discrete hardware component, and may implement or Perform the methods, steps, and logic block diagrams disclosed in the embodiments of the present application.
  • the general-purpose processor may be a microprocessor or any conventional processor. The steps of the method disclosed in the embodiments of the present application may be directly embodied as being executed and completed by a hardware processor, or executed and completed by a combination of hardware and software modules in the processor.
  • the memory 62 may store computer programs, etc., and the memory 62 may be a non-volatile memory, such as a hard disk (HDD) or a solid-state drive (SSD), etc. Volatile memory (volatile memory), such as random-access memory (random-access memory, RAM), may also be a circuit or any other device that can implement a storage function.
  • the memory may also be any other medium that can be used to carry or store desired program codes in the form of instructions or data structures and that can be accessed by a computer, but is not limited thereto.
  • An embodiment of the present application further provides a device, which includes a processor and a memory; wherein the memory is used to store program instructions; the processor is used to call and execute the program instructions stored in the memory to realize the above
  • a device which includes a processor and a memory; wherein the memory is used to store program instructions; the processor is used to call and execute the program instructions stored in the memory to realize the above
  • An embodiment of the present application also provides a communication system, including a receiving end and a sending end.
  • the receiving end is configured to execute the method as described in any one of the foregoing data transmission method embodiments of the present application
  • the sending end is configured to use the second The matrix performs weight assignment on the N transmitting antennas.
  • the embodiments of the present application also provide a computer program product containing instructions, which when run on a computer, cause the computer to execute the technical solutions in the above-mentioned data transmission method embodiments of the present application.
  • the implementation principles and technical effects are similar. Repeat it again.
  • the embodiment of the present application also provides a computer-readable storage medium.
  • the computer-readable storage medium stores instructions, which when run on a computer, cause the computer to execute the technical solutions in the above-mentioned data transmission method embodiments of the present application. The principle and technical effect are similar, and will not be repeated here.
  • the disclosed device and method can be implemented in other ways.
  • the device embodiments described above are only illustrative.
  • the division of the unit is only a logical function division. In actual implementation, there may be other division methods.
  • multiple units or components may be combined or may be Integrate into another system, or some features can be ignored or not implemented.
  • the displayed or discussed mutual coupling or direct coupling or communication connection may be indirect coupling or communication connection through some interfaces, devices or units, and may be in electrical, mechanical or other forms.
  • the unit described as a separate component may or may not be physically separated, and the component displayed as a unit may or may not be a physical unit, that is, it may be located in one place, or may be distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the objectives of the solutions of the embodiments.
  • each unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units may be integrated into one unit.
  • the above-mentioned integrated unit may be implemented in the form of hardware, or may be implemented in the form of hardware plus software functional units.
  • the size of the sequence number of each process does not mean the order of execution.
  • the order of execution of each process should be determined by its function and internal logic.
  • the implementation process of the embodiments of this application should constitute any limitation.
  • all or part of it may be implemented by software, hardware, firmware, or any combination thereof.
  • software it can be implemented in the form of a computer program product in whole or in part.
  • the computer program product includes one or more computer instructions.
  • the computer can be a general-purpose computer, a special-purpose computer, a computer network, network equipment, terminal equipment, or other programmable devices.
  • the computer instruction can be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium.
  • the computer instruction can be transmitted from a website, computer, server, or data center through a cable.
  • the computer-readable storage medium may be any available medium that can be accessed by a computer or a data storage device such as a server or data center integrated with one or more available media.
  • the usable medium may be a magnetic medium (for example, a floppy disk, a hard disk, and a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).

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Abstract

本申请实施例提供一种数据传输方法及装置，通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。

Description

数据传输方法及装置 技术领域
本申请涉及通信技术领域，尤其涉及一种数据传输方法及装置。
背景技术
随着网络技术的发展，无线局域网(wireless local area networks，WLAN)中引入了传输波束成形(transmit beamforming，TxBF)技术，在TxBF的应用中，在多输入多输出(multiple-input multiple-output，MIMO)系统的发送端对多个天线进行加权，通过改变各天线的权值，在空间形成方向性波束，以提高接收端的接收信号的质量。
现有技术中，对发送端的多个天线加权时，发送端向接收端发送信道评估帧(sounding)，接收端接收到信道评估帧后，通过快速傅里叶变换(fast fourier transformation，FFT)将信道评估帧变换到频域，提取每个子载波上的信号，对每个子载波进行信道估计，得到信道矩阵H，对H进行奇异值分解(singular value decomposite，SVD)，即H＝USVH，其中，U、V是酉矩阵，S是对角矩阵，接收端将V作为权值反馈矩阵发送给发送端，发送端使用V矩阵对发送信号进行加权发送。
但是现有技术的对发送端的天线加权的方式较为单一，使得对发送端的天线加权不够灵活。
发明内容
本申请实施例提供一种数据传输方法及装置，为提高接收端的接收信号的质量提供了确定发送端赋值矩阵的替代方案。
第一方面，本申请实施例提供一种数据传输方法，包括：
通过M根接收天线接收检测信号；其中，该检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；根据该检测信号计算信道矩阵；根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD得到的N*N的矩阵；对该第一矩阵进行酉变换，得到第二矩阵；向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
该方法中，提供了确定发送端赋值矩阵的替代方案，具体来说，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
可选的，该对该第一矩阵进行酉变换，得到第二矩阵，包括：
将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
可选的，该预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
可选的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000001
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
可选的，该预设矩阵包括：吉文斯变换Givens矩阵。
可选的，该Givens矩阵包括多个变换矩阵Gi，其中，
Figure PCTCN2019090618-appb-000002
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000003
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
可选的，对该第一矩阵进行酉变换，得到第二矩阵包括：在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该方法中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
可选的，该方法还包括：
根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵；向该发送端发送该各空间流的输出信噪比。
可选的，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该方法中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
可选的，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000004
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
该方法中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比，包括：
根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000005
Figure PCTCN2019090618-appb-000006
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
该方法中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000007
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
可选的，根据该信道矩阵获取第一矩阵包括：对该信道矩阵进行SVD得到该第一酉矩阵；选取该第一酉矩阵的前Nss列，得到该第一矩阵。
第二方面，本申请实施例提供一种数据传输装置，包括：
检测信号接收模块，用于通过M根接收天线接收检测信号；其中，该检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2。
信道矩阵计算模块，用于根据该检测信号计算信道矩阵。
矩阵获取模块，用于根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD 得到的N*N的矩阵。
酉变换模块，用于对该第一矩阵进行酉变换，得到第二矩阵；
矩阵发送模块，用于向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
该装置中，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
可选的，该酉变换模块包括：
第一酉变换子模块，用于将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
可选的，该预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
可选的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000008
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
可选的，该预设矩阵包括：吉文斯变换Givens矩阵。
可选的，该Givens矩阵包括多个变换矩阵Gi，其中，
Figure PCTCN2019090618-appb-000009
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000010
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
可选的，酉变换模块包括：第二酉变换子模块，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
可选的，该装置还包括：
输出信噪比确定模块，用于根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后 形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵。
输出信噪比发送模块，用于向该发送端发送该各空间流的输出信噪比。
可选的，输出信噪比确定模块包括：第一输出信噪比确定子模块，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
可选的，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000011
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
该装置中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，输出信噪比确定模块包括：第二输出信噪比确定子模块，用于根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000012
Figure PCTCN2019090618-appb-000013
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
该装置中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000014
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
可选的，矩阵获取模块包括：矩阵获取子模块，用于对该信道矩阵进行SVD得到该第一酉矩阵；选取该第一酉矩阵的前Nss列，得到该第一矩阵。
第三方面，本申请实施例提供一种通信装置，包括：处理器，以及与该处理器相耦合的收发机。
该收发机，用于通过M根接收天线接收检测信号；其中，该检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2。
该处理器，用于根据该检测信号计算信道矩阵。
该处理器，用于根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD得到的N*N的矩阵。
该处理器，用于对该第一矩阵进行酉变换，得到第二矩阵；
该收发机，用于向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
该装置中，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
可选的，该处理器，用于将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
可选的，该预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
可选的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000015
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
可选的，该预设矩阵包括：吉文斯变换Givens矩阵。
可选的，该Givens矩阵包括多个变换矩阵Gi，其中，
Figure PCTCN2019090618-appb-000016
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000017
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
可选的，该处理器，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
可选的，该处理器，用于根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵。
该收发器，用于向该发送端发送该各空间流的输出信噪比。
可选的，该处理器，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
可选的，该处理器，用于：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000018
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
该装置中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该处理器，用于根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000019
Figure PCTCN2019090618-appb-000020
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
该装置中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000021
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
可选的，该处理器，用于对该信道矩阵进行SVD得到该第一酉矩阵；选取该第一酉矩阵的前Nss列，得到该第一矩阵。
第四方面，本申请实施例提供一种装置，包括：处理器和存储器；其中，该存储器，用于存储程序指令；该处理器，用于调用并执行该存储器中存储的程序指令，实现如第一方面任一项该的方法。
第五方面，本申请实施例提供一种通信系统，包括接收端和发送端，该接收端用于执行如第一方面任一项该的方法，该发送端用于利用该第二矩阵对该N根发送天线进行权重赋值。
第六方面，本申请实施例提供一种计算机可读存储介质，该计算机可读存储介质存储有指令，当该指令被执行时，使得计算机执行如本申请第一方面任一项该的方法。
第七方面，本申请实施例提供一种计算机程序产品，该计算机程序产品包括指令，当该指令被执行时，使得计算机执行如本申请第一方面任一项该的方法。
综上该，本申请实施例的数据传输方法及装置，提供了确定发送端赋值矩阵的替代方案，具体来说，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
附图说明
图1为本申请实施例所涉及的MIMO系统的天线阵列的信道的示意图；
图2为本申请实施例所应用的MIMO系统的架构图；
图3为本申请实施例提供的数据传输方法的流程示意图；
图4为本申请实施例提供的数据传输方法的另一流程示意图
图5为本申请实施例提供的装置的功能结构示意图；
图6为本申请实施例提供的装置的结构示意图。
具体实施方式
本申请实施例提供的数据传输方法及装置可以应用于MIMO系统，MIMO系统具体可以指在发射端和接收端分别使用多个发射天线和接收天线，使信号通过发射端与接收端的多个天线传送和接收。
示例的，图1为MIMO系统的天线阵列的信道的示意图，如图1所示，发送端可以有N根发送天线，接收端可以有M根接收天线，N根发送天线和M根接收天线之间可以互相进行数据传输。M和N的取值可能相同，也可能不同，当M和N的取值不同时，M可以大于N，也可以小于N，本申请不对此进行限制。
具体实现中，在N根发送天线和M根接收天线之间进行数据传输时，可以采用正交频分复用技术(orthogonal frequency division multiplexing，OFDM)，OFDM是多载波调制(multi carrier modulation，MCM)的一种，OFDM主要思想是：将信道分成若干正交子信道，将高速数据信号转换成并行的低速子数据流，调制到在每个子信道上进行传输，正交信号可以通过在接收端采用相关技术来分开，从而可以减少子信道之间的相互干扰，且每个子信道上的信号带宽小于信道的相关带宽，因此每个子信道上可以看成平坦性衰落，从而可以消除码间串扰，且由于每个子信道的带宽仅仅是原信道带宽的一小部分，信道均衡变得相对容易。
图2为本申请实施例所应用的MIMO系统的架构图。MIMO系统具体可以包括基站110和终端设备120。基站110与终端设备120之间可以建立上行和/或下行连接，这些连接用于将数据从终端设备120向基站110传送，反之亦然。通过上行/下行连接所传送的数据可包括终端设备120之间传送的数据等。可以理解，实际应用中，可以有多个终端设备120，考虑到每个终端设备120与基站110之间进行通信的过程类似，本申请实施例中以任一终端设备120与基站110之间进行通信的过程为例进行说明。
本申请实施例涉及到的基站还可以称为无线接入网(radio access network，RAN)设备。基站可以是全球移动通讯(global system of mobile communication，GSM)或码分多址(code division multiple access，CDMA)中的基站(base transceiver station，BTS)，也可以是宽带码分多址(wideband code division multiple access，WCDMA)中的基站(nodeB，NB)，还可以是长期演进(long term evolution，LTE)中的演进型基站(evolutional node B，eNB或eNodeB)，或者中继站或接入点，或者未来5G网络中的基站等，在此并不限定。其中，5G网络中的基站还可以称为gNB。
本申请实施例涉及到的终端设备可以是有线终端，也可以是无线终端。其中，无线终端可以是一种具有无线收发功能的设备。本申请实施例涉及到的终端设备可以部署在陆地上，包括室内或室外、手持或车载；也可以部署在水面上(如轮船等)；还可以部署在空中(例如飞机、气球和卫星上等)。本申请实施例涉及到的终端设备可以是用户设备(user equipment，UE)，其中，UE包括具有无线通信功能的手持式设备、车载设备、可穿戴设备或计算设备。示例性地，UE可以是手机(mobile phone)、平板电脑或带无线收发功能的电脑。终端设备还可以是虚拟现实(virtual reality，VR)终端设备、增强现实(augmented reality，AR)终端设备、工业控制中的无线终端、无人驾驶中的无线终端、远程医疗中的无线终端、智能电网中的无线终端、智慧城市(smart city)中的无线终端、智慧家庭(smart home)中的无线终端等等。本申请实施例中，实现终端的功能的装置可以是终端，也可以是支持终端实现该功能的装置。
本申请实施例所涉及的终端设备或基站可以包括硬件层、运行在硬件层之上的操作系统层，以及运行在操作系统层上的应用层。该硬件层包括中央处理器(dentral processing unit，CPU)、内存管理单元(memory management unit，MMU)和内存(也称为主存)等硬件。该操作系统可以是任意一种或多种通过进程(process)实现业务处理的计算机操作系统，例如，Linux操作系统、Unix操作系统、Android操作系统、iOS操作系统或windows操作系统等。该应用层包含浏览器、通讯录、文字处理软件、即时通信软件等应用。
当然，本申请实施例提供的数据传输方法及装置，还可以适用于其它场景，本申请实施例中对此并不作限制。
本申请实施例中，执行终端设备(或者称之为终端)侧方法的装置可以是终端设备，也可以是终端设备中的装置。示例性地，终端设备中的装置可以是芯片系统、电路或者模块等，本申请不作限制。可以理解，本申请实施例中发送端可以是执行终端设备侧方法的装置。
本申请实施例中，执行基站侧方法的装置可以是基站，也可以是基站中的装置。示例性地，基站中的装置可以是芯片系统、电路或者模块等，本申请不作限制。可以理解，本申请实施例中接收端可以是执行基站侧方法的装置。
图3为本申请实施例一提供的数据传输方法的流程示意图；如图3所示，本申请实施例提供的方法可以包括以下步骤：
步骤S201：发送端通过N根发送天线向接收端的M根接收天线发送检测信号。
本申请实施例中，检测信号可以用于发射端与接收端之间的信号检测。检测信号具体可以是信道评估帧(sounding)，探测参考信号(sounding reference signal，SRS)，也可以是其他的信号，本申请实施例对此不作限定。
步骤S202：接收端根据该检测信号计算信道矩阵。
本申请实施例中，发送端通过N根发送天线向接收端的M根接收天线发送检测信号后，接收端接收到检测信号之后，可以先通过快速傅氏变换(fast fourier transformation，FFT)将检测信号变换到频域，得到多个子载波，然后提取每个子载波上的信号，对每个子载波进行信道估计，得到信道矩阵H。
示例的，若接收端2根接收天线，发送端4根发送天线，则H是2x4的矩阵。
Figure PCTCN2019090618-appb-000022
其中，h00、h01、h02、h03、h10、h11、h12、h13为接收端与发送端的各个信道上的信道响应。
步骤S203：接收端根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD得到的N*N的矩阵。
在一种可实现方式中，接收端可以对信道矩阵进行SVD分解，得到三个矩阵U、V和S，其中，U是M*M的酉矩阵，V是N*N的酉矩阵，S是M*N的对角矩阵，对矩阵进行SVD分解为现有技术，在此不再赘述，则本申请实施例的第一酉矩阵为V矩阵，第一矩阵可以为V矩阵中的前Nss列组成的矩阵。具体应用中，可以在得到V矩阵后，在V矩阵中选取前Nss列，得到第一矩阵。
在本申请实施例的另一种可实现方式中，也可以对信道矩阵进行其他运算，直接得到第一矩阵，使得第一矩阵的内容为V矩阵的前Nss列即可，本申请实施例对根据信道矩阵获取第一矩阵的具体方式不做限定。
步骤S204：接收端对该第一矩阵进行酉变换，得到第二矩阵。
本申请实施例中，酉变换(unitary transformation)是指酉空间的等度量变换。具体的，酉变换可以是归一化的离散傅里叶变换(discrete fourier transform，DFT)，也可以是吉文斯Givens变换，本申请实施例对酉变换不做具体限定。
在一种可选实施方式中，接收端对第一矩阵进行酉变换，得到第二矩阵可以为：
将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
本申请实施例中，预设矩阵可以是DFT矩阵，也可以是Givens矩阵，本申请实施例对预设矩阵不做具体限定。将第一矩阵右乘预设矩阵后，可以得到第三矩阵，则第三矩阵是N*Nss的矩阵，将第三矩阵替换第一矩阵的前Nss列，可以得到第二矩阵。
在另一种可选实施方式中，接收端对第一矩阵进行酉变换，得到第二矩阵可以为：在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵。
其中，该第一预设条件包括：该M根接收天线的接收信号强度指示(received signal strength indication，RSSI)大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
考虑到在一些情况下，对第一矩阵进行酉变换对提升信号质量的效果不佳，因此，本申请实施例中在信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对第一矩阵进行酉变换，得到第二矩阵。
具体应用中，第一预设条件是与信号强度指示RSSI相关的条件，在第一预设条件中，RSSI要大于第一门限且小于第二门限。其中，第一门限的取值是由M根接收天线和N根发送天线组成的MIMO系统中的多空间流的最低能够解调的信号强度决定的，具体来说，第一门限的取值要确保发送端发送的空间流数大于等于2，因为信号强度过小的话，发送端会以单空间流发送信号，而本申请实施例的方法在单空间流的时候会有负收益；第二门限选取是由接收端的信噪比的线性工作区的最大信号强度值决定的，具体来说，当信号强度较小的时候，接收端的信噪比随着信号强度线性增加，当信号强度超过一定值时，由于射频器件(如低噪放)的影响，信噪比不随信号强度的增加而增加，而本申请实施例的方法适应于线性工作区，因此可以将信噪比不随信号强度的增加而增加时对应的信号强度确定为是线性工作区的最大信号强度值，第二门限可以对应为该线性工作区的最大信号强度值。示例的，第一门限可以取-100～10dBm之间的值，比如取-70dBm，第二门限可以取-100～10dBm之间的值，比如取-30dBm。
具体应用中，第二预设条件是与信道矩阵的最大条件数相关的条件，在第二预设条件中，信道矩阵的最大条件数要大于第三门限且小于第四门限。其中，第三门限的取值跟接收端的信道译码的纠错能力有关，可以在实际应用中通过仿真确定，比如WiFi里面取9dB左右，当条件数小于这个值时，考虑到单流的兼容性，就没有必要采用本申请的酉矩阵变换；第四门限 的取值发送端的调度算法有关，可以在实际应用中通过测试给出，具体的，考虑到条件数大于一定值的时候，发射端发送单空间流的概率比较大，示例的，第四门限可以选取30dB左右。具体的，条件数用于标识M根接收天线和N根发送天线组成的MIMO系统中的空间流之间的相关性，空间流之间的相关性可以是空间流的正交性等，本申请实施例对此不作具体限定。实际应用中，信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000023
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。适应的，条件数的对数值可以定义为
Figure PCTCN2019090618-appb-000024
单位为dB。
具体应用中，第三预设条件是与信噪比最大差值相关的条件，在第三预设条件中，各空间流的信噪比最大差值要大于第五门限。其中，第五门限的取值跟接收端的信道译码的纠错能力有关，可以在实际应用中通过仿真确定，比如无线保真(Wireless-Fidelity，WiFi)里面取9dB左右，当信噪比最大差值小于这个值时，考虑到单流的兼容性，就没有必要采用本申请的酉矩阵变换。
本申请实施例中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
步骤S205：接收端向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
本申请实施例中，第二矩阵作为发送端的赋值矩阵。具体应用中，接收端还可以将第二矩阵进行压缩为两个角度向量phi和psi之后，发送给发送端，本申请实施例对此不作具体限定。
可选的，在发送端接收到第二矩阵后，可以包括步骤S206：发送端根据该第二矩阵对该N根发送天线进行加权。
本申请实施例中，发送端在后续数据包发送中，可以根据第二矩阵对发送信号进行加权发送，从而提高接收信号的质量。可以理解，若发送端收到压缩的第二矩阵，则可以按照第二矩阵的压缩协议定义的方法解压缩恢复出第二矩阵，本申请实施例对此不作具体限定。
作为本申请实施例的一种可选实现方式，接收端还可以根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵；向该发送端发送该各空间流的输出信噪比。
通常情况下，MIMO系统中各空间流的输出信噪比差异越大，实际应用中对各空间流的信号处理越不均衡，进而会出现输出信噪比较小的空间流不能被正确译码的现象，因此本申请实施例中，接收端不仅对第一矩阵进行酉变换得到第二矩阵，还通过第四矩阵确定发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比，以通过各空间流的输出信噪比，反馈各空间流的信号处理能力。
具体应用中，可以根据对信道矩阵进行SVD得到的对角矩阵中包含的奇异值，确定发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比，各空间流的输出信噪比可以一致，也可以不一致，本申请实施例对发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比的具体确定方式不作限定。
作为本申请实施例的一种可选实现方式，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
本申请实施例中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
具体的，第一预设条件、第二预设条件和第三预设条件的具体说明参照步骤S204中说明部分的详细记载，在此不再赘述。
综上该，本申请实施例中，接收端通过对第一酉矩阵进行酉变换得到第二矩阵，使得发送端可以根据第二矩阵对发送天线的发送信号进行加权发送，而现有技术中发送端是通过SVD中的V矩阵对发送天线的发送信号进行加权发送，因此，本申请实施例提供了对发送天线加权的一种替代方案。
实践中，本申请发明人经过大量的研究发现，现有技术中的发送端使用V矩阵对发送信号进行加权发送的技术方案中，经常出现接收端和发送端之间误包率较高的情况，其中，V矩阵是接收端对信道矩阵进行SVD分解得到的矩阵，V矩阵为酉矩阵。
且发明人进一步发现导致接收端和发送端之间误包率较高的原因是，在实际应用中经常出现转角效应，转角效应具体是指：在发送端和接收端距离不变的情况下，改变发送端和接收端的相对位置，例如改变天线的摆放方向等，发送端和接收端之间的吞吐量会发生明显的变化，误包率明显增加；且发明人进一步发现，发生转角效应的主要原因是：发送端和接收端的相对位置改变之后，MIMO的各空间流的输出信噪比差异较大，导致对各空间流的信号处理不均衡，会出现输出信噪比较小的空间流不能被正确译码。
示例的，在现有技术中，以发送天线数目为2，接收天线数目也为2为例，两个空间流的输出信噪比分别为
Figure PCTCN2019090618-appb-000025
和
Figure PCTCN2019090618-appb-000026
其中，s0和s1为信道矩阵的奇异值，σ 2是该M根接收天线的噪声方差的平均值，因为现有技术的s0和s1通常差异较大，具体的，s0远大于s1，导致s0的输出信噪比虽然能满足解调要求，但是s1过小，s1对应的输出信噪比过小，导致s1对应的空间流无法解调，导致数据包解调失败。
基于该发现，发明人进一步研究确定，在对实施例一的第一矩阵进行酉变换时，在酉变换为DFT变换或吉文斯Givens变换的情况下，可以有效改善转角效应，降低发送端与接收端之间的误包率。
本申请实施例二提供一种数据传输方法，本申请实施例二是上述实施例一中步骤S204的一种具体实现，具体的本申请实施例二中酉变换为DFT变换，预设矩阵为归一化的离散傅里叶变换DFT矩阵，接收端通过将第一矩阵右乘DFT矩阵，得到第三矩阵。
具体的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000027
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
进一步转化DFT(k,l)，可以得到：
Figure PCTCN2019090618-appb-000028
适应的，本申请实施例一中的根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000029
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
示例的，以发送天线数目为2，接收天线数目也为2为例，接收天线与发送天线之间可以有两个空间流。
第四矩阵S可以为：
Figure PCTCN2019090618-appb-000030
DFT矩阵可以为：
Figure PCTCN2019090618-appb-000031
第二矩阵Vnew可以为：
Figure PCTCN2019090618-appb-000032
空间流的输出信噪比postSNR 0与postSNR 1均为:
Figure PCTCN2019090618-appb-000033
本申请实施例二的其他步骤与本申请实施例一的步骤相同，具体参照本申请实施例一，在此不再赘述。
本申请实施例中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
本申请实施例三提供一种数据传输方法，本申请实施例三是上述实施例一种步骤S204的另一种具体实现，具体的本申请实施例三中酉变换为Givens变换，预设矩阵为Givens矩阵，接收端通过将第一矩阵右乘Givens矩阵，得到第三矩阵。
具体的，Givens矩阵包括多个变换矩阵Gi。
Figure PCTCN2019090618-appb-000034
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，定义Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000035
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
第三矩阵为第一矩阵右乘G1至GNp,即P＝V1*G1。
适应的，本申请实施例一中的根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000036
Figure PCTCN2019090618-appb-000037
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
示例的，以接收天线数目为2，发送天线数目不小于2为例，Nss为2，接收天线与发送天线之间可以有两个空间流。
第三矩阵P为第一矩阵V1右乘G1。
Figure PCTCN2019090618-appb-000038
其中，
Figure PCTCN2019090618-appb-000039
Figure PCTCN2019090618-appb-000040
Figure PCTCN2019090618-appb-000041
示例的，以接收天线数目为4，发送天线数目不小于4为例，Nss为4，接收天线与发送天线之间可以有四个空间流。
第三矩阵P为第一矩阵V1右乘G1再右乘G2，即P＝V1*G1*G2。
其中G1为：
Figure PCTCN2019090618-appb-000042
其中，
Figure PCTCN2019090618-appb-000043
G2为：
Figure PCTCN2019090618-appb-000044
其中，
Figure PCTCN2019090618-appb-000045
Figure PCTCN2019090618-appb-000046
Figure PCTCN2019090618-appb-000047
Figure PCTCN2019090618-appb-000048
Figure PCTCN2019090618-appb-000049
示例的，以接收天线数目为Nrx，发送天线数目为Ntx为例，Nss为Nrx与Ntx中较小的值，接收天线与发送天线之间可以有Nss个空间流。在Nss是大于2的偶数情况下，Np＝Nss/2。
第三矩阵P为第一矩阵V1右乘G1至GNp，即P＝V1*G1*G2*…*GNp。G1,G2,..,GNp是扩展的Givens矩阵。
Figure PCTCN2019090618-appb-000050
其中，m＝Np-2,I是单位阵，I m,m表示m行m列的单位阵。0 m,1表示m行1列的0矩阵。
Figure PCTCN2019090618-appb-000051
其中，m＝Np-4。
Figure PCTCN2019090618-appb-000052
其中n＝i-1,m＝Np-2*n。
Figure PCTCN2019090618-appb-000053
Figure PCTCN2019090618-appb-000054
Figure PCTCN2019090618-appb-000055
Figure PCTCN2019090618-appb-000056
Figure PCTCN2019090618-appb-000057
Figure PCTCN2019090618-appb-000058
Figure PCTCN2019090618-appb-000059
Figure PCTCN2019090618-appb-000060
Figure PCTCN2019090618-appb-000061
可以理解，在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2，其他计算方式与Nss是大于2的偶数的情况相同，在此不再赘述。
本申请实施例三的其他步骤与本申请实施例一的步骤相同，具体参照本申请实施例一，在此不再赘述。
本申请实施例中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
图4示出了本申请实施例五的一种数据传输方法的具体流程示意图。如图4所示，实 际应用中，接收端可以接收天线1发送的天线1信号和天线2发送的天线2的信号，然后对天线1信号和天线2信号分别进行快速傅里叶变换FFT，进而得到各信道的信道估计，得到信道矩阵H，对信道矩阵H进行奇异值分解SVD后，可以得到第一酉矩阵V，根据信道估计还可以得到可以用于标识信道状态的信号强度估计、信道矩阵的最大条件数、噪声估计和信噪比最大差值，在信号强度估计满足第一预设条件，和/或，信道矩阵的最大条件数满足第二预设条件，和/或，信噪比最大差值满足第三预设条件的情况下，可以根据V矩阵进行本申请实施例的酉变换，得到第二矩阵，之后将第二矩阵压缩后通过上报帧反馈给发送端，可以理解在信号强度估计不满足第一预设条件，和/或，信道矩阵的最大条件数不满足第二预设条件，和/或，信噪比最大差值不满足第三预设条件的情况下，可以不对V矩阵进行本申请实施例的酉变换，直接将V矩阵压缩后通过上报帧反馈给发送端；且，在信号强度估计满足第一预设条件，和/或，信道矩阵的最大条件数满足第二预设条件，和/或，信噪比最大差值满足第三预设条件的情况下，还可以根据对信道矩阵H进行奇异值分解SVD得到的对角矩阵，结合噪声方差计算得到发送端根据第二矩阵进行权重赋值后形成的各空间流的新信噪比，将各空间流的新信噪比通过上报帧反馈给发送端，可以理解在信号强度估计不满足第一预设条件，和/或，信道矩阵的最大条件数不满足第二预设条件，和/或，信噪比最大差值不满足第三预设条件的情况下，可以根据噪声方差计算得到发送端根据V矩阵进行权重赋值后形成的各空间流的原信噪比，将各空间流的原信噪比通过上报帧反馈给发送端。
示例的，表1示出了本申请实施例中2根发送天线和2根接收天线在正交振幅调制(Quadrature Amplitude Modulation，QAM)场景下的信号质量提升收益，如表1所示：
信道条件数 调制阶数 信道编码率 收益(dB)
20 256QAM 5/6 3
20 256QAM 3/4 2
20 64QAM 5/6 4
20 64QAM 3/4 3
20 64QAM 2/3 3
25 256QAM 5/6 10
25 256QAM 3/4 6
25 64QAM 5/6 8
25 64QAM 3/4 6
25 64QAM 2/3 4
表1
综上该，本申请实施例中，接收端通过对V进行酉变换得到第二矩阵，使得发送端可以根据第二矩阵对发送天线的发送信号进行加权发送，而现有技术中发送端是通过SVD中的V矩阵对发送天线的发送信号进行加权发送，因此，本申请实施例提供了对发送天线加权，以提升信号质量的一种替代方案。
图5为本发明实施例提供的一种数据处理装置的功能结构示意图，如图5所示，该装置包括：
检测信号接收模块51，用于通过M根接收天线接收检测信号；其中，该检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2。
信道矩阵计算模块52，用于根据该检测信号计算信道矩阵。
矩阵获取模块53，用于根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD得到的N*N的矩阵。
酉变换模块54，用于对该第一矩阵进行酉变换，得到第二矩阵；
矩阵发送模块55，用于向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
该装置中，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
可选的，该酉变换模块包括：
第一酉变换子模块，用于将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
可选的，该预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
可选的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000062
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
可选的，该预设矩阵包括：吉文斯变换Givens矩阵。
可选的，该Givens矩阵包括多个变换矩阵Gi，其中，
Figure PCTCN2019090618-appb-000063
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000064
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
可选的，酉变换模块包括：第二酉变换子模块，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
可选的，该装置还包括：
输出信噪比确定模块，用于根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵。
输出信噪比发送模块，用于向该发送端发送该各空间流的输出信噪比。
可选的，输出信噪比确定模块包括：第一输出信噪比确定子模块，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
可选的，根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000065
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
该装置中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，输出信噪比确定模块包括：第二输出信噪比确定子模块，用于根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000066
Figure PCTCN2019090618-appb-000067
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
该装置中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000068
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
可选的，矩阵获取模块包括：矩阵获取子模块，用于对该信道矩阵进行SVD得到该第一酉矩阵；选取该第一酉矩阵的前Nss列，得到该第一矩阵。
图6为本发明实施例提供的一种通信装置的结构示意图，如图6所示，该装置包括：处理器61，以及与该处理器相耦合的收发机63。
该收发机，用于通过M根接收天线接收检测信号；其中，该检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2。
该处理器，用于根据该检测信号计算信道矩阵。
该处理器，用于根据该信道矩阵获取第一矩阵；其中，该第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；该第一酉矩阵为：对该信道矩阵进行奇异值分解SVD得到的N*N的矩阵。
该处理器，用于对该第一矩阵进行酉变换，得到第二矩阵；
该收发机，用于向该发送端发送该第二矩阵，以指示该发送端利用该第二矩阵对该N根发送天线进行权重赋值。
该装置中，先通过M根接收天线接收检测信号；其中，检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；然后根据检测信号计算信道矩阵；对信道矩阵进行奇异值分解SVD得到第一矩阵；其中，第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；第一酉矩阵为：对信道矩阵进行SVD得到的N*N的矩阵；对第一矩阵进行酉变换，得到第二矩阵；第二矩阵用于发送端对N根发送天线进行权重赋值；向发送端发送第二矩阵；则发送端可以利用第二矩阵对多个发送天线进行赋值，以提高接收端的接收信号的质量。
可选的，该处理器，用于将该第一矩阵右乘预设矩阵，得到第三矩阵；将该第三矩阵替换该第一酉矩阵的前Nss列，得到第二矩阵。
可选的，该预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
可选的，该DFT矩阵中：
Figure PCTCN2019090618-appb-000069
其中，DFT(k,l)代表该DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
可选的，该预设矩阵包括：吉文斯变换Givens矩阵。
可选的，该Givens矩阵包括多个变换矩阵Gi，其中，
Figure PCTCN2019090618-appb-000070
其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单 位阵；0 m,1表示m行1列的0矩阵；
Figure PCTCN2019090618-appb-000071
S i至S Nss-1为该信道矩阵的奇异值；其中，S i+1大于或等于S i。
可选的，该处理器，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对该第一矩阵进行酉变换，得到该第二矩阵；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否对第一矩阵进行酉变换，可以进一步提升信号质量。
可选的，该处理器，用于根据第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；该第四矩阵包括：对角矩阵的前Nss行前Nss列，该对角矩阵为：对该信道矩阵进行SVD得到的奇异值矩阵。
该收发器，用于向该发送端发送该各空间流的输出信噪比。
可选的，该处理器，用于在该信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比；其中，该第一预设条件包括：该M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；该第二预设条件包括：该信道矩阵的最大条件数大于第三门限且小于第四门限，其中，该条件数用于标识该N根发送天线和该M根接收天线的空间流之间的相关性；该第三预设条件包括：该信噪比最大差值大于第五门限；该信噪比最大差值为该发送端通过该第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
该装置中，根据信道状态的具体情况确定是否确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比，避免了盲目确定发送端使用第二矩阵进行权重赋值后形成的各空间流的输出信噪比对计算资源的占用。
可选的，该处理器，用于：
根据该第四矩阵将该各空间流的输出信噪比均确定为：
Figure PCTCN2019090618-appb-000072
其中，S为该第四矩阵，S -1表示该S求逆；DFT Nss×NssS -1是S的逆右乘该DFT矩阵；(DFT Nss×NssS -1) 1 X Nss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1 X Nss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是该M根接收天线的噪声方差的平均值。
该装置中，MIMO系统的任意两个空间流的输出信噪比相同，因此MIMO系统对各空间流的信号处理均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该处理器，用于根据该第四矩阵确定该发送端使用该第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
Figure PCTCN2019090618-appb-000073
Figure PCTCN2019090618-appb-000074
其中，postSNR i至postSNR Nss-1为该MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为该第四矩阵中的奇异值；其中，S i+1大于或等于S i。
该装置中，通过对第一矩阵进行吉文斯变换得到第二矩阵，使得本申请实施例的MIMO系统的发送端通过第二矩阵进行权重赋值时，任意两个空间流的输出信噪比之间的最大差低于现有技术的任意两个空间流的输出信噪比之间的最大差，因此MIMO系统对各空间流的信号处理相对于现有技术更为均衡，进而能够较大程度解决转角效应，降低发送端与接收端之间的误包率。
可选的，该信道矩阵的条件数CN通过下述公式计算得到：
Figure PCTCN2019090618-appb-000075
其中，S a和S b均为该信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
可选的，该处理器，用于对该信道矩阵进行SVD得到该第一酉矩阵；选取该第一酉矩阵的前Nss列，得到该第一矩阵。
在本申请实施例中，处理器可以是通用处理器、数字信号处理器、专用集成电路、现场可编程门阵列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申请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任何常规的处理器等。结合本申请实施例所公开的方法的步骤可以直接体现为硬件处理器执行完成，或者用处理器中的硬件及软件模块组合执行完成。
在本申请实施例中，存储器62可以存储计算机程序等，存储器62可以是非易失性存储器，比如硬盘(hard disk drive，HDD)或固态硬盘(solid-state drive，SSD)等，还可以是易失性存储器(volatile memory)，例如随机存取存储器(random-access memory，RAM)，还可以是电路或者其它任意可以实现存储功能的装置。存储器还可以是能够用于携带或存储具有指令或数据结构形式的期望的程序代码并能够由计算机存取的任何其他介质，但不限于此。
本申请实施例还提供一种设备，该设备包括处理器和存储器；其中，该存储器，用于存储程序指令；该处理器，用于调用并执行该存储器中存储的程序指令，实现本申请上述数据传输方法实施例中接收端的功能，其实现原理和技术效果类似，此处不再赘述。
本申请实施例还提供一种通信系统，包括接收端和发送端，该接收端用于执行如本申请上述数据传输方法实施例中任一项该的方法，该发送端用于利用该第二矩阵对该N根发送天线进行权重赋值。
本申请实施例还提供一种包含指令的计算机程序产品，当其在计算机上运行时，使得计算机执行本申请上述数据传输方法实施例中的技术方案，其实现原理和技术效果类似，此处不再赘述。
本申请实施例还提供一种计算机可读存储介质，计算机可读存储介质中存储有指令，当其在计算机上运行时，使得计算机执行本申请上述数据传输方法实施例中的技术方案，其实现原理和技术效果类似，此处不再赘述。
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，该单元的划分，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。
该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。上述集成的单元既可以采用硬件的形式实现，也可以采用硬件加软件功能单元的形式实现。
本领域普通技术人员可以理解，在本申请的各种实施例中，上述各过程的序号的大小并不意味着执行顺序的先后，各过程的执行顺序应以其功能和内在逻辑确定，而不应对本申请实施例的实施过程构成任何限定。
在上述各实施例中，可以全部或部分地通过软件、硬件、固件或者其任意组合来实现。当使用软件实现时，可以全部或部分地以计算机程序产品的形式实现。该计算机程序产品包括一个或多个计算机指令。在计算机上加载和执行该计算机程序指令时，全部或部分地产生按照本申请实施例该的流程或功能。该计算机可以是通用计算机、专用计算机、计算机网络、网络设备、终端设备或者其他可编程装置。该计算机指令可以存储在计算机可读存储介质中，或者从一个计算机可读存储介质向另一个计算机可读存储介质传输，例如，该计算机指令可以从一个网站站点、计算机、服务器或数据中心通过有线(例如同轴电缆、光纤、数字用户线(DSL))或无线(例如红外、无线、微波等)方式向另一个网站站点、计算机、服务器或数据中心进行传输。该计算机可读存储介质可以是计算机能够存取的任何可用介质或者是包含一个或多个可用介质集成的服务器、数据中心等数据存储设备。该可用介质可以是磁性介质，(例如，软盘、硬盘、磁带)、光介质(例如，DVD)、或者半导体介质(例如固态硬盘Solid State Disk(SSD))等。

Claims (20)

  1. 一种数据传输方法，其特征在于，应用于多输入多输出MIMO系统，所述方法包括：
    通过M根接收天线接收检测信号；其中，所述检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；
    根据所述检测信号计算信道矩阵；
    根据所述信道矩阵获取第一矩阵；其中，所述第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；所述第一酉矩阵为：对所述信道矩阵进行奇异值分解SVD得到的N*N的矩阵；
    对所述第一矩阵进行酉变换，得到第二矩阵；
    向所述发送端发送所述第二矩阵，以指示所述发送端利用所述第二矩阵对所述N根发送天线进行权重赋值。
  2. 根据权利要求1所述的方法，其特征在于，所述对所述第一矩阵进行酉变换，得到第二矩阵，包括：
    将所述第一矩阵右乘预设矩阵，得到第三矩阵；
    将所述第三矩阵替换所述第一酉矩阵的前Nss列，得到第二矩阵。
  3. 根据权利要求2所述的方法，其特征在于，所述预设矩阵包括：归一化的离散傅里叶变换DFT矩阵。
  4. 根据权利要求3所述的方法，其特征在于，所述DFT矩阵中：
    Figure PCTCN2019090618-appb-100001
    其中，DFT(k,l)代表所述DFT矩阵第k行、第l列的元素；k为0至Nss-1的整数；l为0至Nss-1的整数；pi为圆周率。
  5. 根据权利要求2所述的方法，其特征在于，所述预设矩阵包括：吉文斯变换Givens矩阵。
  6. 根据权利要求5所述的方法，其特征在于，所述Givens矩阵包括多个变换矩阵Gi，其中，
    Figure PCTCN2019090618-appb-100002
    其中，i为0到Np-1的整数；n＝i；m＝Nss-2*(n+1)；在Nss是大于2的偶数情况下，Np＝Nss/2；在Nss是大于2的奇数的情况下，Np＝(Nss-1)/2；I n,n表示n行n列的单位阵,I m,m表示m行m列的单位阵；0 m,1表示m行1列的0矩阵；
    Figure PCTCN2019090618-appb-100003
    S i至S Nss-1为所述信道矩阵的奇异值；其中，S i+1大于或等于S i。
  7. 根据权利要求1-6任一项所述的方法，其特征在于，对所述第一矩阵进行酉变换，得到第二矩阵包括：
    在所述信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，对所述第一矩阵进行酉变换，得到所述第二矩阵；
    其中，所述第一预设条件包括：所述M根接收天线的接收信号强度指示RSSI大于第一门 限且小于第二门限；
    所述第二预设条件包括：所述信道矩阵的最大条件数大于第三门限且小于第四门限，其中，所述条件数用于标识所述N根发送天线和所述M根接收天线的空间流之间的相关性；
    所述第三预设条件包括：信噪比最大差值大于第五门限；所述信噪比最大差值为所述发送端通过所述第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
  8. 根据权利要求1-7任一项所述的方法，其特征在于，还包括：
    根据第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比；所述第四矩阵包括：对角矩阵的前Nss行前Nss列，所述对角矩阵为：对所述信道矩阵进行SVD得到的奇异值矩阵；
    向所述发送端发送所述各空间流的输出信噪比。
  9. 根据权利要求8所述的方法，其特征在于，根据第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
    在所述信道状态满足第一预设条件、第二预设条件和第三预设条件中的至少一个条件的情况下，根据所述第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比；
    其中，所述第一预设条件包括：所述M根接收天线的接收信号强度指示RSSI大于第一门限且小于第二门限；
    所述第二预设条件包括：所述信道矩阵的最大条件数大于第三门限且小于第四门限，其中，所述条件数用于标识所述N根发送天线和所述M根接收天线的空间流之间的相关性；
    所述第三预设条件包括：所述信噪比最大差值大于第五门限；所述信噪比最大差值为所述发送端通过所述第一酉矩阵进行权重赋值后形成的空间流之间的信噪比的最大差值。
  10. 根据权利要求8所述的方法，其特征在于，根据第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比包括：
    根据所述第四矩阵将所述各空间流的输出信噪比均确定为：
    Figure PCTCN2019090618-appb-100004
    其中，S为所述第四矩阵，S -1表示所述S求逆；DFT Nss×NssS -1是S的逆右乘所述DFT矩阵；(DFT Nss×NssS -1) 1XNss是取DFT Nss×NssS -1的第1行；||(DFT Nss×NssS -1) 1XNss|| 2是对DFT Nss×NssS -1的第1行计算范数，σ 2是所述M根接收天线的噪声方差的平均值。
  11. 根据权利要求8所述的方法，其特征在于，根据第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比，包括：
    根据所述第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比为：
    Figure PCTCN2019090618-appb-100005
    Figure PCTCN2019090618-appb-100006
    其中，postSNR i至postSNR Nss-1为所述MIMO系统中第i空间流至第Nss-1空间流的输出信噪比；Si至SNss-1为所述第四矩阵中的奇异值；其中，S i+1大于或等于S i。
  12. 根据权利要求7或9所述的方法，其特征在于，
    所述信道矩阵的条件数CN通过下述公式计算得到：
    Figure PCTCN2019090618-appb-100007
    其中，S a和S b均为所述信道矩阵的奇异值，a和b均为不小于0的整数，且a小于b。
  13. 根据权利要求1-12任一项所述的方法，其特征在于，根据所述信道矩阵获取第一矩阵包括：
    对所述信道矩阵进行SVD得到所述第一酉矩阵；
    选取所述第一酉矩阵的前Nss列，得到所述第一矩阵。
  14. 一种通信装置，其特征在于，包括：处理器，以及与所述处理器相耦合的收发机；
    所述收发机，用于通过M根接收天线接收检测信号；其中，所述检测信号为发送端通过N根发送天线发送的；M和N均大于或等于2；
    所述处理器，用于根据所述检测信号计算信道矩阵；
    所述处理器，还用于根据所述信道矩阵获取第一矩阵；其中，所述第一矩阵包括：第一酉矩阵的前Nss列，Nss为M和N中的较小值；所述第一酉矩阵为：对所述信道矩阵进行奇异值分解SVD得到的N*N的矩阵；
    所述处理器，还用于对所述第一矩阵进行酉变换，得到第二矩阵；
    所述收发机，还用于向所述发送端发送所述第二矩阵，以指示所述发送端利用所述第二矩阵对所述N根发送天线进行权重赋值。
  15. 根据权利要求14所述的装置，其特征在于，所述处理器还用于：
    将所述第一矩阵右乘预设矩阵，得到第三矩阵；
    将所述第三矩阵替换所述第一酉矩阵的前Nss列，得到第二矩阵。
  16. 根据权利要求15所述的装置，其特征在于，所述预设矩阵包括：归一化的离散傅里叶变换DFT矩阵，或吉文斯变换Givens矩阵。
  17. 根据权利要求14至16任一项所述的装置，其特征在于，
    所述处理器，还用于根据第四矩阵确定所述发送端使用所述第二矩阵进行权重赋值后形成的各空间流的输出信噪比；所述第四矩阵包括：对角矩阵的前Nss行前Nss列，所述对角矩阵为：对所述信道矩阵进行SVD得到的奇异值矩阵；
    所述收发器，还用于向所述发送端发送所述各空间流的输出信噪比。
  18. 一种装置，其特征在于，包括处理器和存储器；
    其中，所述存储器，用于存储程序指令；
    所述处理器，用于调用并执行所述存储器中存储的程序指令，实现如权利要求1至13中任一项所述的方法。
  19. 一种通信系统，其特征在于，包括接收端和发送端，所述接收端用于执行如权利要求1至13中任一项所述的方法，所述发送端用于利用所述第二矩阵对所述N根发送天线进行权重赋值。
  20. 一种计算机可读存储介质，其特征在于，所述计算机可读存储介质存储有指令，当所述指令被执行时，使得计算机执行权利要求1至13任一项所述的方法。
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