Method and device for determining precoding matrix, equipment and storage medium

Abstract

The invention discloses a method, a device and equipment for determining a precoding matrix and a storage medium, relates to the technical field of communication, and aims to give consideration to the reporting overhead and the performance of the precoding matrix. The method comprises the steps that one or more intermediate matrixes are used for generating a precoding matrix, the value of each intermediate matrix is determined according to first information, and the first information comprises a first codebook index, a first merging coefficient and a second merging coefficient; wherein the first codebook index is an index selected from a base vector of a first codebook, and the first codebook is a codebook formed by a plurality of base vectors; the first merging coefficient is used for linearly merging the base vectors indicated by the first codebook index to obtain a first base vector set; the second merging coefficient is used for performing linear merging based on the first base vector set, and a linear merging result is used for obtaining a precoding matrix. According to the embodiment of the invention, the reporting overhead and performance of the precoding matrix can be considered.

Description

Technical Field

[0001] This application relates to the field of communication technology, and in particular to a method, apparatus, device and storage medium for determining a precoding matrix. Background Technology

[0002] The design of the codebook for Channel State Information (CSI) feedback is a crucial issue for maintaining links in multi-antenna (Multi-Input Multi-Output, MIMO) transmissions and improving the performance of single-user or multi-user MIMO transmissions. Existing CSI codebook schemes suffer from performance limitations for those with low reporting overhead, while schemes offering high performance and accuracy have excessively high reporting overhead.

[0003] Therefore, it is necessary to study a method for determining the precoding matrix that takes into account both reporting overhead and performance. Summary of the Invention

[0004] This application provides a method, apparatus, device, and storage medium for determining a precoding matrix, taking into account both the reporting overhead and performance of the precoding matrix.

[0005] In a first aspect, embodiments of this application provide a method for determining a precoding matrix, applied to a terminal, comprising:

[0006] A precoding matrix is ​​generated using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0007] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0008] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0009] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0010] Secondly, embodiments of this application also provide a method for determining a precoding matrix, applied to a network device, comprising:

[0011] Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more of the intermediate matrices form a precoding matrix;

[0012] Receive target information sent by the terminal;

[0013] Determine the target precoding matrix based on the target information;

[0014] The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0015] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0016] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0017] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0018] Thirdly, embodiments of this application provide an apparatus for determining a precoding matrix, applied to a terminal, comprising: a memory, a transceiver, and a processor.

[0019] A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations:

[0020] A precoding matrix is ​​generated using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0021] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0022] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0023] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0024] Fourthly, embodiments of this application provide an apparatus for determining a precoding matrix, applied to a network device, comprising: a memory, a transceiver, and a processor.

[0025] A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations:

[0026] Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more of the intermediate matrices form a precoding matrix;

[0027] Receive target information sent by the terminal;

[0028] Determine the target precoding matrix based on the target information;

[0029] The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0030] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0031] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0032] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0033] Fifthly, embodiments of this application provide an apparatus for determining a precoding matrix, applied to a terminal, comprising:

[0034] The first processing unit is configured to generate a precoding matrix using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, the first information including: a first codebook index, a first merging coefficient, and a second merging coefficient;

[0035] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0036] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0037] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0038] Sixthly, embodiments of this application provide an apparatus for determining a precoding matrix, applied to a network device, comprising:

[0039] The first sending unit is used to send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more intermediate matrices form a precoding matrix;

[0040] The first receiving unit is used to receive target information sent by the terminal;

[0041] The first processing unit is used to determine the target precoding matrix based on the target information;

[0042] The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0043] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0044] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0045] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0046] In a seventh aspect, embodiments of this application also provide a processor-readable storage medium storing a computer program that, when executed by a processor, implements the steps in the method for determining a precoding matrix as described above.

[0047] In this embodiment, the basis vectors indicated by the first codebook index are linearly merged using a first merging coefficient to obtain a first set of basis vectors. This optimizes the basis vectors indicated by the first codebook index, making them more compatible with the characteristics of the cell or terminal. Furthermore, by linearly merging the basis vectors based on the first set of basis vectors and the second codebook basis vectors indicated by the second codebook index using a second merging coefficient, more accurate beam direction and delay path estimation can be obtained, thereby improving codebook accuracy and precoding matrix performance. Simultaneously, since the first set of basis vectors obtained by linearly merging the basis vectors indicated by the first codebook index using the first merging coefficient is more compatible with the characteristics of the cell or terminal, fewer non-zero coefficients are required to obtain the optimal beam direction and delay when merging using the second merging coefficient, thus reducing reporting overhead. Attached Figure Description

[0048] Figure 1 This is one of the flowcharts of the method for determining the precoding matrix provided in the embodiments of this application;

[0049] Figure 2 This is a second flowchart of the method for determining the precoding matrix provided in the embodiments of this application;

[0050] Figure 3This is one of the structural diagrams of the apparatus for determining the precoding matrix provided in the embodiments of this application;

[0051] Figure 4 This is a second structural diagram of the apparatus for determining the precoding matrix provided in the embodiments of this application;

[0052] Figure 5 This is the third structural diagram of the apparatus for determining the precoding matrix provided in the embodiments of this application;

[0053] Figure 6 This is the fourth structural diagram of the apparatus for determining the precoding matrix provided in the embodiments of this application. Detailed Implementation

[0054] In the embodiments of this application, the term "and / or" describes the relationship between associated objects, indicating that three relationships can exist. For example, A and / or B can represent three cases: A alone, A and B simultaneously, and B alone. The character " / " generally indicates that the preceding and following associated objects have an "or" relationship.

[0055] In the embodiments of this application, the term "multiple" refers to two or more, and other quantifiers are similar.

[0056] The technical solutions of the embodiments of this application will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only a part of the embodiments of this application, and not all of the embodiments. Based on the embodiments of this application, all other embodiments obtained by those of ordinary skill in the art without creative effort are within the scope of protection of this application.

[0057] This application provides a method and apparatus for determining a precoding matrix, which balances reporting overhead and performance.

[0058] The method and apparatus are based on the same concept of the application. Since the methods and apparatus solve problems in similar ways, the implementation of the apparatus and methods can refer to each other, and the repeated parts will not be described again.

[0059] See Figure 1 , Figure 1 This is a flowchart of a method for determining a precoding matrix provided in an embodiment of this application, applied to a terminal, such as... Figure 1 As shown, it includes the following steps:

[0060] Step 101: Generate a precoding matrix using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on the first information.

[0061] In one implementation of this application, the first information includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0062] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; the first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; the second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of linear merging is used to obtain the precoding matrix. The result of linear merging used to obtain the precoding matrix may include directly obtaining the precoding matrix from the result of linear merging.

[0063] For example, the first codebook index may include the indexes of the basis vectors in the horizontal dimension of the first codebook and / or the indexes of the basis vectors in the vertical dimension of the first codebook; alternatively, the basis vectors in the first codebook may not distinguish between horizontal and vertical dimensions. In embodiments of this application, the first codebook may be a codebook composed of spatial domain basis vectors, an angle domain basis vector, an angle-range domain basis vector, or a beam domain basis vector. This first codebook may be indicated by the network device or selected by the terminal.

[0064] In this case, the terminal may also report one or more of the first codebook index, the first merging coefficient, the second merging coefficient, and the first codebook to the network device.

[0065] In one implementation of this application, the first information includes: a first codebook index, a second codebook index, a first merging coefficient, and a second merging coefficient.

[0066] Wherein, the first codebook index is an index selected from the basis vectors of a first codebook, and the first codebook is a codebook composed of multiple basis vectors; the first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; the second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of linear merging is used to obtain the precoding matrix. Specifically, in this embodiment, the second merging coefficient is used to perform linear merging based on the first set of basis vectors and the second codebook basis vectors indicated by the second codebook index to obtain the precoding matrix. Therefore, using the result of linear merging to obtain the precoding matrix can include directly obtaining the precoding matrix based on the result of linear merging.

[0067] The second codebook index is an index selected from the basis vectors of the second codebook, including the indexes of the basis vectors in the second codebook, or including the indexes of the basis vectors in the second codebook and the indexes of the intermediate basis vectors. The second codebook is a codebook composed of basis vectors.

[0068] For example, the first codebook index may include the indexes of the basis vectors in the horizontal dimension and / or the indexes of the basis vectors in the vertical dimension of the first codebook, or the basis vectors in the first codebook may not distinguish between horizontal and vertical dimensions. The second codebook and the first codebook correspond to different vector spaces. For example, in this embodiment, the first codebook may be a codebook composed of spatial domain basis vectors, an angle domain basis vector codebook, an angle-range domain basis vector codebook, or a beam domain basis vector codebook. The second codebook may be a codebook composed of frequency domain basis vectors or a codebook composed of time-delay domain basis vectors. The first and second codebooks may be indicated by the network device or selected by the terminal.

[0069] In this case, the terminal may also report one or more of the first codebook index, the first merging coefficient, the second merging coefficient, the second codebook index, and the second codebook to the network device.

[0070] In one implementation of this application, the first information includes: a first codebook index, a second codebook index, a first merging coefficient, a second merging coefficient, and a third merging coefficient.

[0071] Wherein, the first codebook index is an index selected from the basis vectors of a first codebook, and the first codebook is a codebook composed of multiple basis vectors; the first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; the second merging coefficient is used to linearly merge based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix. Specifically, the second merging coefficient is used to linearly merge based on the first set of basis vectors to obtain a second set of basis vectors, and the third merging coefficient is used to linearly merge the basis vectors indicated by the second codebook index and the second set of basis vectors to obtain the precoding matrix. Therefore, the result of the linear merging used to obtain the precoding matrix may include processing the result of the linear merging with other information (such as the third merging coefficient) to obtain the precoding matrix.

[0072] The second codebook index is an index selected from the basis vectors of the second codebook, including the indexes of the basis vectors in the second codebook, or including the indexes of the basis vectors in the second codebook and the indexes of the intermediate basis vectors. The second codebook is a codebook composed of basis vectors.

[0073] For an explanation of the first and second codebooks, please refer to the description of the foregoing embodiments.

[0074] In this case, the terminal may also report one or more of the following to the network device: the first codebook index, the first merging coefficient, the second merging coefficient, the second codebook index, the third merging coefficient, the first codebook, and the second codebook.

[0075] In the above embodiments, one or more of the first codebook and the second codebook are based on wideband or subband feedback in the frequency domain and on a first feedback cycle in the time domain (for example, the reporting cycle may be independently or jointly configured relative to other reported information (such as the first merging coefficient); one or more of the first codebook index and the second codebook index are based on wideband feedback in the frequency domain and on a second feedback cycle in the time domain; the first merging coefficient is based on wideband or subband feedback in the frequency domain and on a third feedback cycle in the time domain; the second merging coefficient is based on subband feedback in the frequency domain and on a fourth feedback cycle in the time domain; the third merging coefficient is based on wideband feedback in the frequency domain and on a fifth feedback cycle in the time domain; wherein, the lengths of any two of the first to fifth feedback cycles are the same or different.

[0076] Specifically, the reporting of the first merging coefficient can be simultaneous with the first codebook index or independent; the reporting of the second merging coefficient can be simultaneous with the first merging coefficient and the first codebook index or independent, and the frequency domain granularity of the reported coefficients can be the same or different; when the value of the precoding matrix is ​​also determined by the second codebook index, the reporting of the second codebook index can be simultaneous with the first codebook index or independent, and the frequency domain granularity of the reported coefficients can be the same or different; when the value of the precoding matrix is ​​also determined by the third merging coefficient, the reporting of the third merging coefficient can be simultaneous with the second codebook index or independent, and the frequency domain granularity of the reported coefficients can be the same or different.

[0077] Here, since the long-time feedback CSI portion has already undergone preliminary beam combining in each polarization direction, the resulting long-time feedback beamgroup can form a better basis vector. This allows subsequent linear combining short-time CSI reporting based on this basis vector to obtain a more accurate precoding vector. Furthermore, the better basis vector results in fewer non-zero coefficients in the linear combining report, reducing reporting overhead. By using different feedback periods for long and short-time feedback, the amount of codebook coefficient feedback can be reduced, lowering the overhead of Channel State Information (CSI) reporting and achieving a better trade-off between performance and reporting overhead. In other words, different levels of codebook feedback can adopt different long and short-time feedback periods. Because the long-time feedback portion changes relatively slowly in the time domain and forms a better basis vector, the overhead of subsequent linear combining short-time CSI reporting based on this basis vector can be significantly reduced, improving the trade-off between codebook performance and overhead.

[0078] Wherein, the first merging coefficient includes K 01 K is a non-zero coefficient. 01 The first merging coefficient is an integer greater than 0; it includes: an indicator of the position of the first non-zero merging coefficient, an indicator of the position of the first strongest merging coefficient, a first amplitude merging coefficient, and a first phase merging coefficient. K 01 The value can be selected and reported by the UE, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0079] The first indicator of the position of the non-zero coefficient is used to indicate the position information of the non-zero coefficients in each column of the matrix corresponding to the first merged coefficient; the indicator of the position of the first strongest coefficient is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the first merged coefficient; the first amplitude merged coefficient is used to indicate the linear merged amplitude scaling coefficient information in each column of the matrix corresponding to the first merged coefficient; and the first phase merged coefficient is used to indicate the coefficient information of the linear merged phase adjustment in each column of the matrix corresponding to the first merged coefficient.

[0080] Wherein, the second merging coefficient includes K 02 K is a non-zero coefficient. 02 The second merging coefficient is an integer greater than 0; it includes: an indicator of the position of the second non-zero merging coefficient, an indicator of the position of the second strongest merging coefficient, a second amplitude merging coefficient, and a second phase merging coefficient. K 02 The value can be selected and reported by the UE, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0081] The second indicator of the non-zero coefficient position is used to indicate the position information of the non-zero coefficients in each column of the matrix corresponding to the second combined coefficient; the second indicator of the strongest coefficient position is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the second combined coefficient; the second amplitude combined coefficient is used to indicate the linear combined amplitude scaling coefficient information in each column of the matrix corresponding to the second combined coefficient; the second phase combined coefficient is used to indicate the coefficient information of the linear combined phase adjustment in each column of the matrix corresponding to the second combined coefficient.

[0082] The third merging coefficient includes K. 03 K is a non-zero coefficient. 03 The third merging coefficient is an integer greater than 0; it includes: an indication of the position of the third non-zero merging coefficient, an indication of the position of the third strongest merging coefficient, a third amplitude merging coefficient, and a third phase merging coefficient. K 03 The value can be selected and reported by the UE, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0083] The third merge non-zero coefficient position indicator is used to indicate the position information of the non-zero coefficients in each column of the matrix corresponding to the third merge coefficient; the third merge strongest coefficient position indicator is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the third merge coefficient; the third amplitude merge coefficient is used to indicate the linear merge amplitude scaling coefficient information in each column of the matrix corresponding to the third merge coefficient; the third phase merge coefficient is used to indicate the linear merge phase adjustment coefficient information in each column of the matrix corresponding to the third merge coefficient.

[0084] Among the above methods, taking spatial or frequency domain basis vectors as examples, the set of spatial (frequency) domain basis vectors forms a complete linear spatial basis, spanning the entire linear space. In other words, any direction in the spatial (frequency) domain can be obtained by linearly combining the set of spatial (frequency) domain basis vectors. Therefore, in this embodiment, whether using the first or third linear combining coefficients, linear combining is performed, resulting in a better fit with the spatial (frequency) domain characteristics of the cell or terminal. Furthermore, the amplitude distribution range of the second linear combining coefficients is smaller, improving quantization accuracy with the same number of quantization bits. Therefore, when generating the final precoding matrix based on the superior spatial (frequency) domain basis using second linear combining, the codebook accuracy is improved, thereby enhancing the performance of the precoding matrix. Meanwhile, since the superior spatial (frequency) domain basis generated after the linear merging is more compatible with the spatial (frequency) domain characteristics of the cell or terminal, the number of basis vectors fed back when using the second linear merging of the spatial (frequency) domain basis to characterize the precoding matrix of the terminal's layer and / or sub-band will decrease. The number of non-zero coefficients required to obtain the optimal spatial beam direction and delay by performing the second linear merging based on the superior spatial (frequency) domain basis vector will be less, thereby reducing the reporting overhead.

[0085] The following describes, in conjunction with different implementation methods, the values ​​of the intermediate matrix and the determination methods of each piece of information in the first information in the embodiments of this application.

[0086] Option A: In this option, the values ​​of the intermediate matrix are determined as follows:

[0087] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction (a total of 2L vectors), where L is an integer greater than 0.

[0088] The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, wherein the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0;

[0089] The first basis vector set is linearly merged using the matrix corresponding to the second merging coefficient to obtain the precoding matrix. The number of columns of the precoding matrix is ​​RI, where RI is the number of layers (rank) of the precoding matrix and is an integer greater than 0.

[0090] That is, in this scheme A, the first codebook obtains L basis vectors in each of the two polarization directions according to the first codebook index, for a total of 2L basis vectors; the first merging coefficient merges the aforementioned 2L basis vectors into R0 basis vectors to obtain the first basis vector set; the second merging coefficient merges the aforementioned R0 basis vectors into RI basis vectors to obtain the precoding matrix, where RI is the number of layers (rank) of the precoding matrix.

[0091] Specifically, the above precoding matrix can be represented by the following codebook structure:

[0092] W = W1·W2·W3.

[0093] The precoding matrix W has dimensions of 2N1N2×RI, which corresponds to the precoding matrix transmitted across a total of RI layers. The precoding matrix of the i-th layer is a vector in the i-th column of matrix W. N1 and N2 are the number of antenna ports in the horizontal and vertical dimensions, respectively.

[0094] Where W1 represents the first codebook index, it is a matrix composed of the basis vectors of the L first codebooks, and the dimension of W1 is 2N1N2×2L. W1 can be in the form of a block diagonal matrix, i.e. In this matrix, the dimension of matrix B on the diagonal blocks is N1N2×L, and each diagonal block corresponds to the polarization direction of an antenna. Each column of B is a basis vector (such as a spatial basis vector) of length N1N2×1. The index of the basis vector in the first codebook can be used to indicate the index of the basis vector (such as a spatial basis vector) of the first dimension. 1,1 The index indicator i of the second-dimensional basis vectors (such as spatial basis vectors) 1,2 The indicator can also be the index indicator i1 of a single basis vector (such as a spatial basis vector). The first dimension can be either horizontal or vertical, and the second dimension can be either vertical or horizontal.

[0095] The first codebook can be a set of orthogonal or non-orthogonal basis vectors composed of Discrete Fourier Transform (DFT) vectors, Discrete Cosine Transform (DCT) vectors, Slepian Transform (ST) vectors, eigenvectors, etc. In the example above, the l-th column of matrix B can be written as... u l,1 Let i be an orthogonal or non-orthogonal basis vector in the first codebook in the horizontal or vertical direction, determined by the index i of the basis vectors in the first dimension (such as spatial basis vectors). 1,1 Instructions, u l,2For an orthogonal or non-orthogonal basis vector in the first codebook in the vertical or horizontal direction, the index i of the basis vector in the second dimension (such as the spatial basis vector) is... 1,2 Indication. The choice of L basis vectors in each of the two polarization directions can be the same or different.

[0096] When the L basis vectors of the two polarization directions are chosen differently, the above The matrices B1 and B2 on the diagonal blocks have dimensions N1N2×L, corresponding to the selection of L basis vectors in the corresponding polarization direction. The value of L can be predefined by the protocol, configured by the network through higher-layer signaling (Radio Resource Control (RRC) signaling), or a combination of both. The first codebook can be predefined by the protocol, configured by the network through higher-layer signaling (RRC signaling), reported by the terminal (feature vector codebook), or a combination of the above forms.

[0097] Where W2 is the matrix of the first merging coefficients, and the dimension of W2 is 2L×R0. R0 is the number of columns in the W2 matrix. Each column vector of W2 merges the L basis vectors (e.g., spatial basis vectors) selected by the terminal in each of the two polarization directions in the W1 matrix into a new basis vector (e.g., spatial basis vector). The effect of W1·W2 is that each column of the R0 column in the W2 matrix merges 2L basis vectors (e.g., spatial basis vectors) into a new basis vector (e.g., spatial basis vector), for a total of R0 new basis vectors (e.g., spatial basis vectors), thus obtaining the first basis vector set. The merging in the two polarization directions can be independent. The value of R0 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0098] by Taking spatial basis vectors as an example, without loss of generality, let the r-th column of the W2 matrix be... That is, 2L spatial basis vectors are merged into 1 new spatial basis vector. Regarding the first merging coefficient c... i , Merging 2L spatial basis vectors into a new spatial vector can be any form of linear merging, including the indicator i of the position of the non-zero coefficient of the first merge. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 .

[0099] Wherein, the first combination is not an indicator of the zero coefficient position i 2,1Provide the position information of the non-zero coefficients in each column. In the example above, the position of the first non-zero coefficient in the r-th column is indicated by i. 2,1,r Can indicate middle The specific position of each non-zero coefficient among 2L elements.

[0100] Specific indication methods may include: (i) indicating using a bitmap, for example... In this bitmap, w corresponds from left to right (or from right to left). r In (ii) Alternatively, it can be indicated by the position index of the first non-zero coefficient in column r and the difference position index offset of the remaining non-zero coefficients. In the example above, the number of the first non-zero coefficients in column r is... The W2 matrix has column R0, therefore the total number of non-zero coefficients contained in the first combined coefficients is... Among them, K 01 The value can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0101] Indicator i of the position of the strongest coefficient in the first merging 2,2 Provide the location information of the strongest coefficient in each column. In the example above, the indicator i of the location of the first merged strongest coefficient... 2,2,r It can indicate the strongest coefficient in column r. The specific position of each non-zero coefficient. A specific indication method could be to use the strongest coefficient in the r-th column... The position index of the non-zero coefficients is used to indicate this. In the example above, the W2 matrix has column R0, so the index of the first combined strongest coefficient is i. 2,2,r The total number is R0. The value of R0 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0102] First amplitude combining coefficient i 2,3 Provide the linear combining amplitude scaling factor information for each column. First amplitude combining factor i 2,3 Specifically, it is further divided into the indication of the broadband amplitude merging amplitude scaling factor i 2,3,1 Indicator i of the amplitude scaling factor for sub-band amplitude merging 2,3,2 This corresponds to the first amplitude combining coefficient indicator when different reporting granularities are selected. When the reporting granularity is wideband, the first amplitude combining coefficient only includes the indicator i of the wideband amplitude combining amplitude scaling factor. 2,3,1 When the reported granularity is sub-band, the first amplitude combining factor includes an indicator i of the broadband amplitude combining amplitude scaling factor. 2,3,1 Indicator i of the amplitude scaling factor for sub-band amplitude merging2,3,2 Or it may only contain an indication of the sub-band amplitude combining amplitude scaling factor. 2,3,2 Specifically, the bandwidth amplitude scaling factor i in column r is... 2,3,1,r It also contains 2 indicators i 2,3,1,r,1 i 2,3,1,r,2 , corresponding to the broadband amplitude combining scaling factor for the two polarization directions in the r-th column, respectively. The indicator i for the sub-band amplitude combining scaling factor. 2,3,2 Contains N subband (N subband This indicates the number of sub-bands (an integer greater than 0). It represents the combined amplitude scaling factor for all sub-band amplitude values ​​in columns R0 of the nth sub-band. SB The sub-band amplitude combining scaling factor in the r-th column of the sub-band is indicated as follows:

[0103] First amplitude combining coefficient i 2,3 This could be: (i) a bitmap of index values ​​for the amplitude scaling factor, where the specific scaling factor is determined based on the index value corresponding to each bit in the bitmap. For example, in the example above, the indicator of the combined amplitude scaling factor for the broadband amplitude in the two polarization directions in column r. nth SB Subband amplitude scaling factor in the r-th column of the subband Index value The value range is {0, 1, 2, 3, 4, 5, 6, 7}, and the amplitude scaling factor corresponding to each index value is... (ii) Specific scaling factor quantization values. For example, in the example above, the indication of the broadband amplitude combining amplitude scaling factor in the two polarization directions of the r-th column. nth SB Subband amplitude scaling factor in the r-th column of the subband It refers to the specific scaling factor quantization value. Quantization can be scalar quantization or vector quantization. The quantization interval can be uniform or non-uniform. The quantization range, number of bits, and quantization interval can be predefined by the protocol, selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of the above.

[0104] First phase combining coefficient i 2,4 Provide the coefficient information for the linear merging phase adjustment of each column. First phase merging coefficient i 2,4 Specifically, it is further divided into the indication of the broadband phase merging phase adjustment coefficient i 2,4,1 Indicator i of sub-band phase merging phase adjustment coefficient 2,4,2This corresponds to the first phase merging coefficient indicator when different reporting granularities are selected. When the reporting granularity is wideband, the first phase merging coefficient only includes the indicator i of the wideband phase merging phase adjustment coefficient. 2,4,1 When the reported granularity is sub-band, the first phase combining coefficient includes an indication i of the broadband phase combining phase adjustment coefficient. 2,4,1 Indicator i of sub-band phase merging phase adjustment coefficient 2,4,2 Or only include an indication of the sub-band phase merging phase adjustment coefficient. 2,4,2 Specifically, the broadband phase merging phase adjustment coefficient i in the r-th column. 2,4,1,r The broadband phase-combining phase adjustment coefficients correspond to the r-th polarization direction. Specifically, the phase adjustment coefficient for the first polarization direction is 1 (no adjustment) by default, and the phase adjustment coefficient for the second polarization direction relative to the first polarization direction is i. 2,4,1,r i 2,4,2 Contains N subband (N subband The indicator represents the subband phase merging phase adjustment coefficients of all R0 columns in the nth subband (indicating the number of subbands reported by the terminal), where the nth subband is the subband phase merging phase adjustment coefficient. SB The subband phase merging phase adjustment coefficient of the r-th column of the subband is indicated as follows:

[0105] First phase combining coefficient i 2,4 This could be: (i) a bitmap of index values ​​for phase adjustment coefficients, where the specific adjustment coefficient is determined based on the index value corresponding to each bit in the bitmap. For example, in the example above, the indicator of the broadband phase-combining phase adjustment coefficients in the two polarization directions of column r. nth SB Subband phase merging phase adjustment coefficient in the r-th column of the subband Index value The value range is {0, 1, ..., 15}, and the phase adjustment coefficient corresponding to each index value is... (ii) Specific adjustment coefficient quantification value.

[0106] For example, in the above example, the indication of the inter-polarization broadband phase merging phase adjustment coefficient of the r-th column. nth SB The sub-band phase merging phase adjustment factor for the r-th column of the sub-band is:

[0107] in, It refers to the specific adjustment coefficient quantization value. Quantization can be scalar quantization, the quantization interval can be uniform, and the quantization range, number of bits, and quantization interval can be predefined by the protocol, selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of the above.

[0108] Here, W3 is the matrix of the second merging coefficients, with dimensions R0×RI, where RI is the number of columns in the W3 matrix, which is also the level (rank) of the precoding matrix. Since the W3 matrix has RI columns, the effect of W1·W2·W3 is that each column of the W3 matrix merges the R0 basis vectors (such as spatial basis vectors) of W1·W2 into one new basis vector (such as spatial basis vector), for a total of RI new basis vectors (such as spatial basis vectors), resulting in the precoding matrix. The merged sum in the i-th column of the W3 matrix corresponds to the precoding matrix of the i-th level.

[0109] by For example, let a column of the W3 matrix be... but That is, R0 basis vectors (such as spatial basis vectors) are merged into one new basis vector (such as spatial basis vector). Regarding the merging coefficient w′, merging R0 basis vectors (such as spatial basis vectors) into one new basis vector (such as spatial basis vector) can be any form of linear merging, including the indicator i indicating the position of the second non-zero coefficient. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific interpretations of these instructions are similar to those related to the first consolidation coefficient.

[0110] Based on the foregoing description, taking the basis vectors included in the first codebook as spatial basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: The precoding codeword of layer i, obtained by vector summation and expansion of the first codebook index, first merging coefficient, and second merging coefficient reported by the terminal, i.e., the precoding matrix of layer i, can be written as:

[0111]

[0112] Among them, b l , The index of the spatial basis vector in the horizontal dimension indicates i 1,1 The index indicator i of the spatial basis vectors in the vertical dimension 1,2 Determine (b1 and (They can be the same vector); The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure.

[0113] Option B: In this option, the values ​​of the intermediate matrix are determined as follows:

[0114] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0.

[0115] Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0;

[0116] The first basis vector set is linearly merged using the matrix corresponding to the second merging coefficient to obtain the precoding matrix. The precoding matrix has RI columns, where RI is the layer number of the precoding matrix and is a positive integer. Specifically, L vectors are obtained for each of the two polarization directions based on the first codebook index, for a total of 2L vectors. The first merging coefficient and the first codebook index are then used to obtain R0 vectors for each of the two polarization directions (a total of 2R0 vectors), which is the first basis vector set. The second merging coefficient merges these 2R0 vectors into RI vectors to obtain the precoding matrix, where RI is the layer number (rank) of the precoding matrix.

[0117] In this scheme, the above codebook design can be represented by the following codebook structure:

[0118]

[0119] The precoding matrix W has a dimension of 2N1N2×RI, which corresponds to the precoding matrix transmitted across a total of RI layers. The precoding matrix of the i-th layer is a vector of the i-th column of matrix W.

[0120] Here, W1 represents the first codebook index, which is a matrix composed of L vectors from the first codebook. The dimension of W1 is N1N2×L, corresponding to the polarization direction of an antenna. Each column of W1 is a spatial basis vector of length N1N2×1, indicated by the index of the vector in the first codebook, and may contain the index indicator i of the basis vector of the first dimension. 1,1 The index indicator i of the second-dimensional basis vectors (such as spatial basis vectors) 1,2 The indicator can also be the index indicator i1 of a single basis vector (such as a spatial basis vector). The first dimension can be a horizontal or vertical dimension, and the second dimension can be a horizontal or vertical dimension. The first codebook can be a set of orthogonal or non-orthogonal basis vectors composed of Discrete Fourier Transform (DFT) vectors, Discrete Cosine Transform (DCT) vectors, Slepian Transform (ST) vectors, eigenvectors, etc.

[0121] In the example above, the l-th column of matrix W1 can be written as u l,1 Let i be an orthogonal or non-orthogonal basis vector in the first codebook in the horizontal or vertical direction, determined by the index i of the basis vectors in the first dimension (such as spatial basis vectors). 1,1 Instructions, u l,2 For an orthogonal or non-orthogonal basis vector in the first codebook in the vertical or horizontal direction, the index i of the basis vector in the second dimension (such as the spatial basis vector) is... 1,2 Instructions. The choice of L basis vectors in the two polarization directions can be the same or different. When the choice of L basis vectors in the two polarization directions is different, the above... Wherein, matrix W 1,1 W 1,2 The dimension is N1N2×L, corresponding to the selection of L basis vectors in the polarization direction. The value of L can be predefined by the protocol, configured by the network through higher-layer signaling (RRC signaling), or a combination of both. The first codebook can be predefined by the protocol, configured by the network through higher-layer signaling (RRC signaling), reported by the terminal (feature vector codebook), or a combination of the above forms.

[0122] In this matrix, W2 is the first merging coefficient matrix, with dimensions L×R0, where R0 is the number of columns. Each column vector of W2 merges the L basis vectors (e.g., spatial basis vectors) selected by the terminal in one polarization direction from the W1 matrix into a new basis vector (e.g., spatial basis vector). The effect of W1·W2 is that each column of the R0 column in the W2 matrix merges the L basis vectors (e.g., spatial basis vectors) into a new basis vector (e.g., spatial basis vector), resulting in a total of R0 new basis vectors (e.g., spatial basis vectors), thus obtaining the first basis vector set. The merging in the two polarization directions can be independent. The value of R0 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0123] With W1 = [b1…b L For example, without loss of generality, let the r-th column of the W2 matrix be w. r =[c1…c L ] T , That is, L basis vectors (such as spatial basis vectors) are merged into one new basis vector (such as spatial basis vector). The first merging coefficient can be the same or different in the two polarization directions. Regarding the first merging coefficient c... i For L basis vectors (such as spatial basis vectors), merging a new basis vector can be performed. This can be an arbitrary linear merging, including the indicator i of the position of the non-zero coefficient of the first merge. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 .

[0124] The first merge coefficient of Scheme B is not the zero coefficient position indicator, but the position indicator of the first strongest merge coefficient. The first amplitude merge coefficient and the first phase merge coefficient are the same as those of Scheme A, the only difference being the change in matrix dimension.

[0125] Here, W3 is the matrix of the second merging coefficients, and its dimension is 2R0×RI, where RI is the number of columns in the W3 matrix, which is also the number of layers (rank) of the precoding matrix. Since the W3 matrix has RI columns... The effect is that each column of the RI column in the W3 matrix will... The 2R0 basis vectors (such as spatial basis vectors) are merged into 1 new basis vector (such as spatial basis vector), for a total of RI new basis vectors (such as spatial basis vectors), to obtain the precoding matrix. In the W3 matrix, the merging and subtraction of the i-th column corresponds to the precoding matrix of the i-th layer.

[0126] by For example, let a column of the W3 matrix be... but That is, 2R0 spatial vectors are merged into one new spatial vector. Regarding the merging coefficient w′, merging 2R0 spatial vectors into one new spatial vector can be any form of linear merging, including the indicator i indicating the position of the second non-zero coefficient. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific interpretations of these instructions are similar to those of the instructions related to the first consolidation coefficient.

[0127] Based on the foregoing description, taking the basis vectors included in the first codebook as spatial basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: W1 = [b1…b L Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: The precoding codeword of layer i, obtained by vector summation and expansion of the first codebook index, first merging coefficient, and second merging coefficient reported by the terminal, i.e., the precoding matrix of layer i, can be written as:

[0128]

[0129] Among them, b l The index of the spatial basis vector in the first dimension indicates i 1,1 The index indicator i of the second-dimensional spatial basis vector 1,2 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure.

[0130] By improving scheme B, scheme B1 can also be obtained, in which:

[0131] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0.

[0132] Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0;

[0133] Using the matrix corresponding to the second merging coefficient, a single basis vector is selected from the first basis vector set and an inter-polarity merging factor is added to obtain the precoding matrix. The number of columns of the precoding matrix is ​​RI, where RI is the number of layers of the precoding matrix and RI is an integer greater than 0.

[0134] In scheme B1, the above codebook design scheme can be represented by the following codebook structure:

[0135]

[0136] The designs of W1 and W2 are the same as those of Scheme B, the difference being the design of W3.

[0137] W3 is the matrix of the second merging coefficients. The dimension of W3 is 2R0×RI, where RI is the number of columns in the W3 matrix, which is also the level (rank) of the precoding matrix. Each column of W3 consists of a column selection vector plus a phase / amplitude merging factor. The k-th column of the W3 matrix is... Where c jk It is a column selection vector of length R0, the j-th column... k One element is 1, and the other elements are 0. The result is that each column of column RI in the W3 matrix will select one column from W1·W2 and add a merging factor to obtain a new spatial vector, for a total of RI new spatial vectors, forming a precoding matrix. The i-th column in the W3 matrix corresponds to the precoding matrix of the i-th layer.

[0138] by For example, let the k-th column of the W3 matrix be... but The indication information of W3 includes the indication of the position of the second non-zero coefficient. 3,1 (Determine the position of each non-zero element in each column), second amplitude merging coefficient i 3,3 Second phase merging coefficient i 3,4 The specific details are similar to those of the first merging coefficient, and will not be repeated here.

[0139] Based on the foregoing description, taking the basis vectors included in the first codebook as spatial basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: W1 = [b1…b L Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: The precoding codeword of layer i, obtained by vector summation and expansion of the first codebook index, first merging coefficient, and second merging coefficient reported by the terminal, i.e., the precoding matrix of layer i, can be written as:

[0140]

[0141] in, The index of the spatial basis vector in the first dimension indicates i 1,1 The index indicator i of the second-dimensional spatial basis vector 1,2 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Confirmed; j i The indication i of the position of the second non-zero coefficient 3,1 Confirmed, d i The second amplitude combining coefficient i 3,3 Determined; θ i By the second phase merging coefficient i 3,4 Sure.

[0142] Option C: In this option, the values ​​of the intermediate matrix are determined as follows:

[0143] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. L basis vectors are selected in each polarization direction, where L is an integer greater than 0.

[0144] The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, where the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0.

[0145] The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is K, and K is an integer greater than 0.

[0146] The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the second set of basis vectors, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

[0147] That is, in scheme C, L basis vectors are obtained in each of the two polarization directions of the first codebook according to the first codebook index, for a total of 2L basis vectors; the first merging coefficient merges the aforementioned 2L basis vectors into R0 basis vectors, obtaining the first vector set; the second merging coefficient further merges the R0 vectors obtained by the first merging coefficient into K vectors, obtaining the second basis vector set; the aforementioned K vectors and the K basis vectors of length N obtained according to the second codebook index... subband The row vectors are merged to obtain N. subband From the vectors, we obtain the precoding matrix.

[0148] Specifically, the above codebook design scheme can be represented by the following codebook structure:

[0149] W = W1·W2·W3·W4.

[0150] In this scheme, W1 and W2 are the same as those described in the previous scheme. It is important to note that the dimension of matrix W differs from that in the previous scheme. In this scheme, the dimension of matrix W is 2N1N2×N. subband All N corresponding to the transmission of one layer subband If there are a total of RI layers of transmission in the subband precoding matrix, and each layer corresponds to a dimension of 2N1N2×N. subband The matrix W can be the same or different for each layer.

[0151] In this matrix, W3 is the matrix of the second merging coefficients. It's important to note that in this case, the dimension of matrix W3 differs from the previous scheme; W3 has a dimension of R0×K. Here, K is the number of columns in matrix W3, the number of rows in matrix W4, the number of frequency domain basis vectors selected after frequency domain compression (if the basis vectors are spatial basis vectors), and the number of effective channel delay paths corresponding to the precoding matrix. Since matrix W3 has K columns, the effect of W1·W2·W3 is that each of the K columns in matrix W3 merges the R0 basis vectors (e.g., spatial basis vectors) of W1·W2 into one new basis vector (e.g., a spatial basis vector), for a total of K new basis vectors.

[0152] by For example, let one column of the W3 matrix be... but That is, R0 basis vectors (such as spatial basis vectors) are merged into one new basis vector (such as spatial basis vector). Regarding the merging coefficient d... i Merging R0 vectors with a new basis vector (such as spatial basis vectors) can be any form of linear merging, including the indicator i of the position of the second non-zero coefficient. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3，4 The specific details are similar to those of the first merging coefficient, and will not be repeated here. The value of R0 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0153] Here, W4 represents the second codebook index, which is a matrix composed of vectors from the K second codebooks, and W4 has a dimension of K×N. subband , where N subband This represents the number of columns in the W4 matrix, and also the number of subbands transmitted. Each row of W4 is a 1×N matrix. subband The basis vectors (such as frequency domain basis vectors) are indicated by the indices of the vectors in the second codebook, including the index indicator i of the basis vectors (such as frequency domain basis vectors). 4，1 And optional, the index indicator i of intermediate basis vectors (such as frequency domain basis vectors) 4，2 The second codebook can be a set of any orthogonal or non-orthogonal basis vectors formed by Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Slepian Transform (ST), frequency domain eigenvectors, etc. The second codebook index indicates i. 4，1 and i 4，2 This forms the W4 matrix. The second codebook can be predefined by the protocol, configured by the network through higher-layer signaling (RRC signaling), reported by the terminal (frequency domain feature vector codebook), or a combination of the above.

[0154] The effect of W3·W4 is that for an original dimension of R0×N subband The basis vector (e.g., frequency domain basis vector) matrix is ​​subjected to frequency domain compression with a rank of K. Let W3 = [q1 … q K ], That is, for dimensions R0×N subband The matrix is ​​estimated and decomposed to have a rank of K. The value of K can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both. subband The value can be predefined by the protocol, configured by the network through higher-level signaling (RRC signaling), or a combination of both.

[0155] Based on the foregoing description, taking the basis vectors of the first codebook as spatial basis vectors and the basis vectors of the second codebook as frequency basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: Let the matrix formed by the vectors in the second codebook be: Based on the first codebook index, first merging coefficient, second merging coefficient, and second codebook index reported by the terminal, all N values ​​of a certain layer are obtained by vector summation and expansion. subband The subband precoding codewords, i.e., the precoding matrix of all subbands in any given layer, can be written as:

[0156]

[0157] Among them, b l , The index of the spatial basis vector in the horizontal dimension indicates i 1,1 The index indicator i of the spatial basis vectors in the vertical dimension 1,2 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure. The index of the frequency domain basis vector indicates i 4,1 And optionally, the index indicator i of the intermediate frequency domain basis vectors 4,2 Sure.

[0158] Option D: In this option, the values ​​of the intermediate matrix are determined as follows:

[0159] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0.

[0160] Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0;

[0161] The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is K, and K is an integer greater than 0.

[0162] The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the second set of basis vectors, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

[0163] That is, based on the first codebook index, L vectors are obtained for each of the two polarization directions, for a total of 2L vectors; after the first merging coefficient and the first codebook index are processed, R0 vectors are obtained for each of the two polarization directions (a total of 2R0 vectors), thus obtaining the first basis vector set; the second merging coefficient further merges the aforementioned 2R0 vectors into K vectors, thus obtaining the second basis vector set; the aforementioned K vectors, based on the second codebook index, yield K basis vectors of length N. subband The row vectors are merged to obtain N. subband The precoding matrix is ​​obtained by using vectors.

[0164] Specifically, the above precoding matrix can be represented by the following codebook structure:

[0165]

[0166] In this case, W1 and W2 are the same as in scheme B. It should be noted that the dimension of matrix W is 2N1N2×N. subband All N corresponding to the transmission of one layer subband Subband precoding matrix. If there are a total of RI layers for transmission, each layer corresponds to a dimension of 2N1N2×N. subband The matrix W can be the same or different for each layer.

[0167] W3 is the matrix of the second combining coefficients, with dimensions 2R0×K. The design and usage of W3 are the same as in scheme B, except that it has K columns. K is also the number of rows in matrix W4, the number of frequency domain basis vectors selected after frequency domain compression, and the number of effective channel delay paths corresponding to the precoding matrix. The second combining coefficients for combining 2R0 basis vectors (such as spatial basis vectors) can be any form of linear combining, including the indicator i of the non-zero coefficient position of the second combining coefficient. 3，1 The indicator i of the position of the second strongest combined coefficient 3，2 The second amplitude combining coefficient i 3，3 Second phase merging coefficient i 3，4 For details, please refer to the description of the aforementioned Scheme B.

[0168] W4 represents the second codebook index, and its design and use are the same as in scheme C.

[0169] Based on the foregoing description, taking the basis vectors of the first codebook as spatial basis vectors and the basis vectors of the second codebook as frequency basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: W1=[b1…b L Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: Let the matrix formed by the vectors in the second codebook be: Based on the first codebook index, first merging coefficient, second merging coefficient, and second codebook index reported by the terminal, all N values ​​of a certain layer are obtained by vector summation and expansion. subband The subband precoding codewords, i.e., the precoding matrix of all subbands in any given layer, can be written as:

[0170] Among them, b l It is indicated by the index i of the spatial basis vectors in the first dimension. 1，1 The index indicator i of the second-dimensional spatial basis vector 1,2 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure. The index of the frequency domain basis vector indicates i 4,1 And optionally, the index indicator i of the intermediate frequency domain basis vectors 4,2 Sure.

[0171] Option E: In this option, the values ​​of the intermediate matrix are determined as follows:

[0172] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0.

[0173] The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, wherein the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0;

[0174] The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is R1, and R1 is an integer greater than 0.

[0175] The second basis vector set is merged using the third merging coefficient to obtain a third basis vector set, wherein the number of columns in the third basis vector set is K, and K is an integer greater than 0;

[0176] The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the third basis vector set, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

[0177] That is, based on the first codebook index, L vectors are obtained in each of the two polarization directions of the first codebook, for a total of 2L vectors; the first merging coefficient merges the aforementioned 2L vectors into R0 vectors, thus obtaining the first basis vector set; the second merging coefficient further merges the R0 vectors obtained by the first merging coefficient into R1 vectors, thus obtaining the second basis vector set; the third merging coefficient further merges the aforementioned R1 vectors into K vectors, thus obtaining the third basis vector set; the aforementioned K vectors, obtained from the second codebook index, are K vectors of length N. subband The row vectors are merged to obtain N. subbandFrom the vectors, we obtain the precoding matrix.

[0178] Specifically, the above precoding matrix can be represented by the following codebook structure:

[0179] W = W1·W2·W3·W4′·W4.

[0180] W1 and W2 are the same as in the previous scheme, and will not be repeated here. It should be noted that in this case, the dimension of matrix W is 2N1N2×N. subband All N corresponding to the transmission of one layer subband Subband precoding matrix. If there are a total of RI layers for transmission, each layer corresponds to a dimension of 2N1N2×N. subband The matrix W can be the same or different for each layer.

[0181] Here, W3 is the matrix of the second merging coefficients. It's important to note that in this case, the dimension of matrix W3 differs from the previous scheme; W3 has a dimension of R0 × R1. R1 is the number of columns in matrix W3. Since matrix W3 has R1 columns, the effect of W1·W2·W3 is that each column of matrix W3 merges the R0 basis vectors obtained from merging W1·W2 into one basis vector, resulting in a total of R1 new basis vectors. For example, let one column of the W3 matrix be... but That is, R0 spatial vectors are merged into one new vector. Regarding the merging coefficient d... i For R0 basis vectors, a new basis vector can be merged, which can be any form of linear merging, including the indicator i of the position of the second non-zero coefficient. 3，1 The indicator i of the position of the second strongest combined coefficient 3，2 The second amplitude combining coefficient i 3，3 Second phase merging coefficient i 3，4 The specific content is similar to the relevant indication of the first merging coefficient. The value of R0 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both. Taking the basis vector of the first codebook as the spatial basis vector and the basis vector of the second codebook as the frequency basis vector as an example, the matrix operation W1·W2·W3 will yield a new basis vector in column R1, which corresponds to the spatial beam direction in the direction of the R1 frequency basis vectors.

[0182] Here, W4′ is the matrix of the third combining coefficients. It's important to note that the definition and dimensions of matrix W4′ differ from the previous schemes; the dimension of matrix W4′ is R1×K. R1 is the number of columns in matrix W3, and also the number of rows in matrix W4′. K is the number of columns in matrix W4′, the number of rows in matrix W4 (see subsequent description), the number of frequency domain basis vectors selected after frequency domain compression, and the number of effective channel delay paths corresponding to the precoding matrix. W4′ combines the R1 column vectors of W1·W2·W3 to obtain a new vector of K columns. This combination can be any form of linear combination, including the indicator i of the non-zero coefficient position of the third combining coefficient. 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude merging coefficient i 4′,3 Third phase merging coefficient i 4′，4 The specific details are similar to those of the first merging coefficient, and will not be repeated here. The value of R1 can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both.

[0183] Here, W4 represents the second codebook index, and W4 is a matrix composed of K vectors from the second codebook, with dimensions K×N. subband , where N subband This represents the number of columns in the W4 matrix, and also the number of subbands transmitted. Each row of W4 is a 1×N matrix. subband The frequency domain basis vectors are indicated by the indices of the vectors in the second codebook, including the index indicator i of the frequency domain basis vectors. 4，1 And optionally, the index indicator i of the intermediate frequency domain basis vectors 4，2 The second codebook can be a set of any orthogonal or non-orthogonal basis vectors formed by Discrete Fourier Transform (DFT), Discrete Cosine Transform (DCT), Slepian Transform, frequency domain eigenvectors, etc. The second codebook index indicates i. 4，1 and i 4，2 This forms the W4 matrix. The second codebook can be predefined by the protocol, configured by the network through higher-layer signaling (RRC signaling), reported by the terminal (frequency domain feature vector codebook), or a combination of the above. The effect of W4′·W4 is that for an original dimension of R1×N... subband The frequency domain basis vector matrix is ​​compressed in the frequency domain with a rank of K.

[0184] With W4′=[q1…q K ], That is, for dimensions R1×N subbandThe matrix is ​​estimated and decomposed to have a rank of K. The value of K can be selected and reported by the terminal, configured by the network through higher-layer signaling (RRC signaling), or a combination of both. subband The value can be predefined by the protocol, configured by the network through higher-level signaling (RRC signaling), or a combination of both.

[0185] Based on the foregoing description, taking the basis vectors of the first codebook as spatial basis vectors and the basis vectors of the second codebook as frequency basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: Let the W4′ matrix be formed by the third merging coefficients: Let the matrix formed by the vectors in the second codebook be: Based on the first codebook index, first merging coefficient, second merging coefficient, third merging coefficient, and second codebook index reported by the terminal, all N values ​​of a certain layer are obtained through vector summation expansion. subband The subband precoding codewords, i.e., the precoding matrix of all subbands in any given layer, can be written as:

[0186]

[0187] Among them, b l , The index of the spatial basis vector in the horizontal dimension indicates i 1,1 The index indicator i of the spatial basis vectors in the vertical dimension 1,2 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indication i of the position of the first non-zero coefficient 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure. The index of the frequency domain basis vector indicates i 4,1 And optionally, the index indicator i of the intermediate frequency domain basis vectors 4,2 Sure; The indication i of the position of the third non-zero coefficient 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude merging coefficient i 4′,3 Sure; The indication i of the position of the third non-zero coefficient 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 Third phase merging coefficient i 4′,4 Sure.

[0188] Option F: In this option, the values ​​of the intermediate matrix are determined as follows:

[0189] The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0.

[0190] Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0;

[0191] The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is R1, and R1 is an integer greater than 0.

[0192] The second basis vector set is merged using the third merging coefficient to obtain a third basis vector set, wherein the number of columns in the third basis vector set is K, and K is an integer greater than 0;

[0193] The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the third basis vector set, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

[0194] That is, based on the first codebook index, L vectors are obtained for each of the two polarization directions, for a total of 2L vectors; after the first merging coefficient and the first codebook index are processed, R0 vectors are obtained for each of the two polarization directions (a total of 2R0 vectors), which is the first basis vector set; the second merging coefficient further merges the aforementioned 2R0 vectors into R1 vectors, obtaining the second basis vector set; the third merging coefficient further merges the aforementioned R1 vectors into K vectors, obtaining the third basis vector set; the aforementioned K vectors, based on the second codebook index, yield K vectors of length N. subband The row vectors are merged to obtain N. subband The precoding matrix is ​​obtained by using vectors.

[0195] Specifically, the above precoding matrix can be represented by the following codebook structure:

[0196]

[0197] Among them, W1 and W2 are the same as those in the aforementioned scheme D.

[0198] Here, W3 is the matrix of the second merging coefficients. It's important to note that in this case, the dimension of matrix W3 differs from the previous scheme; the dimension of W3 is 2R0×R1. The design and use of W3 are the same as in scheme B, the difference being that the number of columns is R1. Here, R1 is the number of columns in matrix W3. For merging 2R0 spatial vectors, the second merging coefficients can be any form of linear merging, including the indicator i of the non-zero coefficient position of the second merging coefficient. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific details are similar to those of Plan D, and will not be repeated here.

[0199] Among them, W4′ is the matrix of the third merging coefficients, which is the same as that of scheme E.

[0200] Here, W4 is a matrix composed of K vectors from the second codebook, which is the same as scheme E.

[0201] Based on the foregoing description, taking the basis vectors of the first codebook as spatial basis vectors and the basis vectors of the second codebook as frequency basis vectors as an example, let the W1 matrix formed by the indices of the first codebook be: W1=[b1…b L Let the W2 matrix be formed by the first merging coefficients: Let the W3 matrix be formed by the second merging coefficients: Let the W4′ matrix be formed by the third merging coefficients: Let the matrix formed by the vectors in the second codebook be: Based on the first codebook index, first merging coefficient, second merging coefficient, third merging coefficient, and second codebook index reported by the terminal, all N values ​​of a certain layer are obtained through vector summation expansion. subband The subband precoding codewords, i.e., the precoding matrix of all subbands in any given layer, can be written as:

[0202]

[0203] Among them, b l It is indicated by the index i of the spatial basis vectors in the first dimension. 1,1 The index indicator i of the second-dimensional spatial basis vector 1,2 Sure; The indicator i is the position of the first non-zero coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 Sure; The indicator i is the position of the first non-zero coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 First phase merging coefficient i 2,4 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Sure; The indication i of the position of the second non-zero coefficient 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 Second phase merging coefficient i 3,4 Sure. The index of the frequency domain basis vector indicates i 4,1 And optionally, the index indicator i of the intermediate frequency domain basis vectors 4,2 Sure; The indication i of the position of the third non-zero coefficient 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude merging coefficient i 4′,3 Sure; The indication i of the position of the third non-zero coefficient 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 Third phase merging coefficient i 4′,4 Sure.

[0204] In this embodiment, the basis vectors indicated by the first codebook index are linearly merged using a first merging coefficient to obtain a first set of basis vectors. This optimizes the basis vectors indicated by the first codebook index, making them more compatible with the characteristics of the cell or terminal. Furthermore, by linearly merging the basis vectors based on the first set of basis vectors and the second codebook basis vectors indicated by the second codebook index using a second merging coefficient, more accurate beam direction and delay path estimation can be obtained, thereby improving codebook accuracy and precoding matrix performance. Simultaneously, since the first set of basis vectors obtained by linearly merging the basis vectors indicated by the first codebook index using the first merging coefficient is more compatible with the characteristics of the cell or terminal, fewer non-zero coefficients are required to obtain the optimal beam direction and delay when merging using the second merging coefficient, thus reducing reporting overhead.

[0205] In one embodiment of this application, the main operations of the terminal may further include:

[0206] Step 201: The terminal receives the channel state information reporting parameters configured by the network, wherein the channel state information reporting parameters are used to measure and report channel state information.

[0207] The channel state information (CSI) reporting parameters include CSI reporting bandwidth, subband size, and reference signal configuration. The CSI reporting bandwidth consists of continuous or discontinuous CSI subbands within the system. Each CSI subband includes several consecutive Physical Resource Blocks (PRBs). The number of PRBs in each CSI subband can be configured by the network to the terminal via parameters, or it can be a pre-agreed number.

[0208] Step 202: Receive the reference signal sent by the network device.

[0209] The terminal receives reference signals from the base station, which may be Channel State Information Reference Signals (CSI-RS).

[0210] Step 203: The terminal performs channel estimation based on the reference signal to obtain a downlink channel matrix on one or more subcarrier sets.

[0211] Step 204: The terminal calculates the first broadband correlation matrix (such as the spatial broadband correlation matrix) based on the downlink channel matrix.

[0212] The terminal calculates the first wideband correlation matrix based on the downlink channel matrix within the CSI reporting bandwidth. Let H be the channel matrix of subcarrier i within the CSI reporting bandwidth. i Dimension N r×(2N1N2), where N r Where 2N1N2 is the number of receiving antennas at the terminal, and 2N1N2 is the number of antenna ports for CSI-RS transmission from the base station, the calculation of the empty first broadband correlation matrix is ​​as follows:

[0213]

[0214] Where Sc is the set of subcarriers within the CSI reporting bandwidth.

[0215] Step 205: The terminal obtains a first matrix based on the first broadband correlation matrix. The first matrix is ​​a matrix composed of the largest R0 principal eigenvectors of the first broadband correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R0 principal eigenvectors of the first broadband correlation matrix, where R0 is an integer greater than 0.

[0216] For example, the terminal performs eigenvalue decomposition on the first broadband correlation matrix and selects the R0 largest principal eigenvectors. remember Other algorithms can also be used to calculate the E matrix. For example, the E matrix is ​​the largest R0 principal eigenvectors of the first broadband correlation matrix. The E matrix is ​​obtained through linear transformation or linear combination, or it is obtained by linear transformation of the principal eigenvector e1 of the first broadband correlation matrix. in, These are linear transformation matrices.

[0217] The E matrix can also be determined using methods such as Newton's iteration method, Jacob's method, or orthogonal triangular decomposition (QR).

[0218] Step 206: Based on the first matrix, determine the first merging coefficient and / or the second merging coefficient.

[0219] (1) Among them, determining the first merging coefficient includes:

[0220] Step 207: The terminal determines the first codebook index based on the first broadband correlation matrix and the first codebook.

[0221] The terminal selects a basis vector from the first codebook and constructs the first codebook index W1 using the indices of the selected basis vectors. One implementation is to select the basis vectors in an energy-maximizing manner, that is, for any vector v in the first codebook... i ,calculate Select the L largest Revi vectors, denoted as b1…b L .

[0222] For the aforementioned schemes A, C, and E... For the aforementioned scheme B, B1, D, F, W1 = [b1…b L The terminal uses the index values ​​of the L vectors in the first codebook as the index of the first codebook.

[0223] Step 208: The terminal obtains the first merging coefficient based on the first codebook index and the first matrix.

[0224] The terminal calculates the matrix W2 = Quant((W1)) corresponding to the first merging coefficient. H E). Here, Quant(A) is a function that quantizes each element of matrix A, which can be scalar quantization or vector quantization. The quantization function Quant(A) can quantize some elements in matrix A to 0 values, for example, quantizing values ​​below a set threshold to 0.

[0225] The terminal obtains the indication i of the position of the first non-zero coefficient based on W2. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 .

[0226] (2) Among them, determining the second merging coefficient includes:

[0227] I. For schemes A and B, based on the channel state information of any sub-band within the CSI reported bandwidth, the first codebook index, and the first combining coefficient, determine the second combining coefficient associated with the sub-band, specifically including the following:

[0228] S1. For any sub-band within the CSI reporting bandwidth:

[0229] There are at least two ways to do this:

[0230] Method 1

[0231] (1) The terminal performs eigenvalue decomposition on the correlation matrix of the subband and takes the largest RI principal eigenvectors s1, s2, ..., s RI Let S = [s1, s2, ..., s RI The calculation method for the subband correlation matrix is ​​the same as that for the broadband correlation matrix; it is calculated using the channel matrix on the subcarriers within that subband.

[0232] (2) The terminal calculates the matrix corresponding to the second merging coefficient:

[0233] For scheme A: W3 = Quant((W1W2) H S);

[0234] For option B:

[0235] Method 2

[0236] (1) Calculate the subband correlation matrix R at the terminal. s Terminal pair matrix (W1W2) H R s W1W2 or Perform eigenvalue decomposition and select the RI largest principal eigenvectors u1, u2, ..., u RI .

[0237] (2) The terminal calculates the second merging coefficient matrix W3 = Quant([u1,u2,...,u...). RI ]).

[0238] Subsequently, the terminal calculates the indication i of the position of the second non-zero coefficient based on W3. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific calculation is similar to the relevant indications of the first merging coefficient, and will not be repeated here.

[0239] S2, the terminal will obtain the first codebook index, and the indicator i of the position of the first non-zero coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 The second combination is not an indicator of the zero coefficient position. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3，3 Second phase merging coefficient i 3,4 Send it to the network device.

[0240] II. Regarding Scheme B1, the terminal, based on the channel state information of any sub-band within the CSI-reported bandwidth, the first codebook index, and the first combining coefficient, traverses possible column selection vectors and combining factors to determine the second combining coefficient associated with the sub-band. The column selection vector is a basis vector from a set of first basis vectors determined based on the first codebook index and the first combining coefficient. Specifically, this may include:

[0241] S1. For any sub-band within the CSI reporting bandwidth:

[0242] (1) The terminal performs eigenvalue decomposition on the correlation matrix of the subband and takes the largest R1 principal eigenvectors s1, s2, ..., S. RI Let S = [s1, s2, ..., S2]RI The calculation method for the subband correlation matrix is ​​the same as that for the broadband correlation matrix; it is calculated using the channel matrix on the subcarriers within that subband.

[0243] (2) The terminal calculates the second merging coefficient matrix W3. One approach is for the terminal to traverse possible column selection vectors and merging factors, select the optimal combination of column selection vectors and merging factors, and determine the second merging coefficient associated with the subband.

[0244] (3) The terminal obtains the indication i of the position of the second non-zero coefficient based on W3. 3，1 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 .

[0245] S2, the terminal will obtain the first codebook index, and the indicator i of the position of the first non-zero coefficient. 2，1 The indicator i of the position of the first combined strongest coefficient 2，2 The first amplitude merging coefficient i 2，3 First phase merging coefficient i 2,4 The second combination is not an indicator of the zero coefficient position. 3,1 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3，4 Send it to the network device.

[0246] III. For schemes C and D, there are at least a few ways to determine the second merging coefficient:

[0247] Method 1

[0248] S1. Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reported bandwidth.

[0249] Specifically, the terminal calculates the frequency broadband correlation matrix, i.e., the second broadband correlation matrix. The terminal calculates the frequency broadband correlation matrix based on the downlink channel matrix within the CSI reporting bandwidth. Let H be the channel matrix of subcarrier i within the CSI reporting bandwidth. i Dimension N r ×(2N1N2), where N r 2N1N2 represents the number of receiving antennas at the terminal, and 2N1N2 represents the number of CSI-RS antenna ports transmitted by the base station. Let matrix G... mn = [H1(m,n) H2(m,n) … H F [m, n], where F is the number of subcarriers, H1(m, n) is the element in the m-th row and n-th column of matrix H1, and so on. Then the frequency domain broadband channel correlation matrix is ​​calculated as follows:

[0250]

[0251] S2. Determine the second codebook index W4 based on the second wideband correlation matrix and the second codebook.

[0252] One implementation is to choose based on energy maximization, that is, for any vector f in the second codebook... i ,calculate Select the R1 largest Revi vectors, denoted as s1…s1. K .

[0253]

[0254] The terminal uses the index values ​​of the K vectors in the second codebook as the index of the second codebook.

[0255] S3. Obtain a third matrix based on the channel state information of any sub-band within the CSI reporting bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band.

[0256] For any layer of the precoding matrix:

[0257] For any subband n within the CSI reporting bandwidth SB The terminal performs eigenvalue decomposition on the correlation matrix of the sub-band, takes the largest principal eigenvector s1, and obtains the third matrix, denoted as S(n). SB )=[s1]. The calculation method for the subband correlation matrix is ​​the same as that for the broadband correlation matrix, which is calculated using the channel matrix on the subcarriers within the subband.

[0258] S4. Based on the first codebook index, the first merging coefficient, the third matrix, and the second codebook index, the second merging coefficient W3 is obtained, expressed as:

[0259] W3 = Quant((W1W2) H [[S(1)S(2)…S(N subband )](W4) H );or

[0260]

[0261] Method 2

[0262] S1. Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reported bandwidth.

[0263] S2. Determine the second codebook index W4 based on the second wideband correlation matrix and the second codebook.

[0264] S3. Obtain a third matrix based on the channel state information of any sub-band within the CSI reporting bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band.

[0265] In this case, S1-S3 of method two can be described with reference to S1-S3 of method one.

[0266] S4. Determine the fourth merging coefficient based on the third matrix, the first codebook index, and the first merging coefficient.

[0267] For scheme C, the terminal calculates the fourth merging coefficient W6: W6(n) SB )=(W1W2) H S(n SB ).

[0268] For scheme D, the terminal calculates the fourth merging coefficient W6:

[0269] S5. Based on the fourth merging coefficient and the second codebook index, the second merging coefficient is obtained.

[0270] Specifically, the terminal calculates W3 as follows:

[0271] W3 = Quant([W6(1)W6(2)…W6(N)) subband )](W4) H ).

[0272] Method 3: The terminal determines the second combining coefficient associated with the sub-band based on the channel state information of any sub-band within the bandwidth reported by CSI, the first codebook index, the first combining coefficient, and the second codebook index.

[0273] For any subband n within the CSI reporting bandwidth SB The terminal calculates the subband correlation matrix R. s Terminal pair matrix (W1W2) H R s W1W2 or Perform eigenvalue decomposition and select the RI largest principal eigenvectors u. 1,nSB ,u 2,nSB ,...,u RI,nSB .

[0274] For the i-th layer, the terminal calculates the second merging coefficient W3.

[0275]

[0276] Based on the above three methods, the terminal calculates the indication i of the second non-zero coefficient position according to W3. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific calculation is similar to the relevant indications of the first merging coefficient, and will not be repeated here.

[0277] Subsequently, the terminal will obtain the first codebook index, the second codebook index, and the indicator i of the position of the first non-zero coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 The second combination is not an indicator of the zero coefficient position. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 Send it to the network device.

[0278] IV. For codebook schemes E and F, the third merging coefficient can be determined as follows:

[0279] s1. Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reporting bandwidth.

[0280] Specifically, the terminal calculates the frequency broadband correlation matrix, i.e., the second broadband correlation matrix. The terminal calculates the frequency broadband correlation matrix based on the downlink channel matrix within the CSI reporting bandwidth. Let H be the channel matrix of subcarrier i within the CSI reporting bandwidth. i Dimension N r ×(2N1N2), where N r 2N1N2 represents the number of receiving antennas at the terminal, and 2N1N2 represents the number of CSI-RS antenna ports transmitted by the base station. Let matrix G... mn = [H1(m,n) H2(m,n) … H F [m, n], where F is the number of subcarriers, H1(m, n) is the element in the m-th row and n-th column of matrix H1, and so on. Then the frequency domain broadband channel correlation matrix is ​​calculated as follows:

[0281]

[0282] S2. Determine the second codebook index based on the second wideband correlation matrix and the second codebook.

[0283] The terminal selects a vector from the second codebook to form the second codebook index W4. One implementation is to select the vector in an energy-maximizing manner, that is, for any vector fi in the second codebook, calculate... Select the K largest Revi vectors, denoted as s1 … s K .So:

[0284]

[0285] The terminal uses the index values ​​of the K vectors in the second codebook as the index of the second codebook.

[0286] S3. Based on the second bandwidth correlation matrix, a fourth matrix is ​​obtained. The fourth matrix is ​​a matrix composed of the largest R1 principal eigenvectors of the second bandwidth correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R1 principal eigenvectors of the second bandwidth correlation matrix, where R1 is an integer greater than 0.

[0287] For example, the terminal performs eigenvalue decomposition on the second bandwidth correlation matrix and selects the R1 largest principal eigenvectors. We obtain the fourth matrix, denoted as...

[0288] S4. The terminal obtains the third merging coefficient based on the fourth matrix and the second codebook index.

[0289] The terminal calculates the third combined coefficient matrix W4′=Quant(Q(W4)). H The terminal obtains the indication i of the position of the third non-zero coefficient based on W4′. 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude merging coefficient i 4′,3 Third phase merging coefficient i 4′,4 .

[0290] For schemes E and F, the second merging coefficient can be calculated as follows:

[0291] Method 1

[0292] S1. Obtain a third matrix based on the channel state information of any sub-band within the CSI reporting bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band.

[0293] For any subband n within the CSI reporting bandwidth SB The terminal performs eigenvalue decomposition on the correlation matrix of the subband, takes the largest principal eigenvector s1, and obtains the third matrix, denoted as S(n).SB )=[s1]. The calculation method for the subband correlation matrix is ​​the same as that for the broadband correlation matrix, which is calculated using the channel matrix on the subcarriers within the subband.

[0294] S2. Determine the fourth merging coefficient based on the third matrix, the first codebook index, and the first merging coefficient. For one layer of the precoding matrix:

[0295] For scheme E, the terminal calculates the fourth merging coefficient W6: W6(n SB )=(W1W2) H S(n SB );

[0296] For scheme F, the terminal calculates the fourth merging coefficient W6:

[0297] S3. The second merging coefficient is obtained based on the second codebook index, the third merging coefficient, and the fourth merging coefficient.

[0298] The second merging coefficient can be expressed as:

[0299] W3=Quant([W6(1) W6(2) … W6(N subband )](W4′W4) H ).

[0300] Method 2

[0301] S1. Obtain a third matrix based on the channel state information of any sub-band within the CSI reporting bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band.

[0302] For any subband n within the CSI reporting bandwidth SB The terminal performs eigenvalue decomposition on the correlation matrix of the subband, takes the largest principal eigenvector s1, and obtains the third matrix, denoted as S(n). SB )=[s1]. The calculation method for the subband correlation matrix is ​​the same as that for the broadband correlation matrix, which is calculated using the channel matrix on the subcarriers within the subband.

[0303] S2. The terminal obtains the second merging coefficient based on the first codebook index, the first merging coefficient, the third matrix, the second codebook index, and the third merging coefficient.

[0304] The second merging coefficient can be expressed as:

[0305] W3 = Quant((W1W2) H[[S(1)S(2)…S(N subband )](W4′W4) H );or

[0306]

[0307] The terminal calculates the indication i of the position of the second non-zero coefficient based on W3. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The specific calculation is similar to the relevant indications of the first merging coefficient, and will not be repeated here.

[0308] Subsequently, the terminal will obtain the first codebook index, the second codebook index, and the indicator i of the position of the first non-zero coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 The second combination is not an indicator of the zero coefficient position. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 The third combination is not an indicator of the zero coefficient position. 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude merging coefficient i 4′,3 Third phase merging coefficient i 4′,4 Send it to the network device.

[0309] Optionally, in this embodiment, the terminal may also receive codebook parameters sent by the network device, wherein the codebook parameters are used to determine the values ​​of the intermediate matrix, including one or more of the following:

[0310] Antenna port (N1, N2) parameter configuration in the horizontal and / or vertical directions;

[0311] Configuration of oversampling factors (O1, O2) in the horizontal and / or vertical directions;

[0312] Codebook subset constraints and / or rank constraints (levels) information are configured by RRC;

[0313] Port selection configurations, such as port codebook size and port rank (layer) limit;

[0314] The configuration information for the sub-band precoding matrix indicator (PMI) is calculated based on the sub-band channel quality indicator (CQI).

[0315] Codebook configuration parameter combinations;

[0316] The value of L in the first codebook index;

[0317] The value of R0 in the first merging coefficient; the number of non-zero coefficients K contained in the first merging coefficient. 01 Optional: the first merging coefficient amplitude quantization form (e.g., SQ, VQ) and bit width, the first merging coefficient phase adjustment quantization form (e.g., BPSK, QPSK, 8PSK), and whether to report the first merging coefficient amplitude adjustment in the sub-band.

[0318] The number K of non-zero coefficients included in the first merging coefficient. 01 Optional: the first merging coefficient amplitude quantization form (e.g., SQ, VQ) and bit width, the first merging coefficient phase adjustment quantization form (e.g., BPSK, QPSK, 8PSK), and whether to report the first merging coefficient amplitude adjustment in the sub-band.

[0319] The number K of non-zero coefficients included in the second merging coefficient 02 ;Optional, the value of R1 (when the terminal reports the second codebook index and the terminal reports the third merging coefficient);Optional, the amplitude quantization form (e.g., SQ, VQ) and bit width of the second merging coefficient, the phase adjustment quantization form of the second merging coefficient (e.g., BPSK, QPSK, 8PSK), and whether the sub-band reports the amplitude adjustment of the second merging coefficient.

[0320] The third combining coefficient includes the number of non-zero coefficients, K. 03 Optional: the third merging coefficient amplitude quantization form (e.g., SQ, VQ) and bit width, the second merging coefficient phase adjustment quantization form (e.g., BPSK, QPSK, 8PSK), and whether to report the third merging coefficient amplitude adjustment in the sub-band.

[0321] The codebook parameters may include one or more of the following:

[0322] The amplitude quantization form and bit width of the first merging coefficient;

[0323] The phase adjustment quantization form of the first merging coefficient;

[0324] Whether the first merging coefficient amplitude should be adjusted in the sub-band report;

[0325] The value of the number R1 of the second spatial basis vectors;

[0326] The second quantization form of the combined coefficient amplitude;

[0327] The second merging coefficient phase adjustment quantization form;

[0328] Whether the second merging coefficient amplitude should be adjusted in the sub-band report;

[0329] The third merging coefficient amplitude quantization form;

[0330] The third merging coefficient phase adjustment quantization form;

[0331] Whether the third merging coefficient amplitude should be adjusted in the sub-band report;

[0332] The value of K in the second codebook index;

[0333] Information related to sub-band reporting;

[0334] Indicators of the types of spatial basis vectors in the first codebook (e.g., DFT, DCT, ST eigenvectors);

[0335] Indicators of the types of frequency domain basis vectors in the second codebook (e.g., DFT, DCT, ST eigenvectors);

[0336] Reported volume;

[0337] The type of codebook reported, such as CSI reporting based on the codebook in the embodiments of this application, and the reporting quantity is PMI-RI-CQI, etc.

[0338] See Figure 2 , Figure 2 This application describes a method for determining a precoding matrix, applied to a network device, comprising:

[0339] Step 301: Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more intermediate matrices form a precoding matrix.

[0340] The meaning of the codebook parameters can be found in the description of the foregoing method embodiments. The method for determining the values ​​of the intermediate matrix and related content can also be found in the description of the foregoing method embodiments.

[0341] Step 302: Receive target information sent by the terminal. The target information includes, but is not limited to, first information reported by the terminal; the explanation of the first information can be found in the description of the foregoing method embodiments.

[0342] Step 303: Determine the target precoding matrix based on the target information.

[0343] After determining the target precoding matrix, the base station determines the precoding matrix to be used for the final Physical downlink shared channel (PDSCH) / Demodulation Reference Signal (DMRS) channel transmission based on the obtained channel state information and scheduling decisions, and then performs transmission accordingly.

[0344] Based on the above embodiments, the network device may also send channel state information reporting parameters to the terminal, wherein the channel state information reporting parameters are used to measure and report channel state information; and send a reference signal to the terminal, wherein the reference signal is used for channel estimation.

[0345] In this embodiment, the basis vectors indicated by the first codebook index are linearly merged using a first merging coefficient to obtain a first set of basis vectors. This optimizes the basis vectors indicated by the first codebook index, making them more compatible with the characteristics of the cell or terminal. Furthermore, by linearly merging the basis vectors based on the first set of basis vectors and the second codebook basis vectors indicated by the second codebook index using a second merging coefficient, more accurate beam direction and delay path estimation can be obtained, thereby improving codebook accuracy and precoding matrix performance. Simultaneously, since the first set of basis vectors obtained by linearly merging the basis vectors indicated by the first codebook index using the first merging coefficient is more compatible with the characteristics of the cell or terminal, fewer non-zero coefficients are required to obtain the optimal beam direction and delay when merging using the second merging coefficient, thus reducing reporting overhead.

[0346] Taking network equipment as a base station as an example, the following processing content may be included:

[0347] Step 401: The base station configures the codebook parameters via RRC signaling. The configurable codebook parameters are as described in the previous embodiments.

[0348] Step 402: Configure the channel status information reporting parameters for the base station, including CSI reporting bandwidth, sub-band size, reference signal resource configuration, and channel status information reporting configuration.

[0349] Step 403: The base station transmits reference signals, which may be Channel State Information Reference Signals (CSI-RS).

[0350] Step 404: The base station receives the channel state information report based on the precoding matrix of this application embodiment reported by the terminal.

[0351] Channel state information reporting includes: an optional first codebook; an optional second codebook; a first codebook index; an optional second codebook index; and first combining coefficient information, including an indication of the position of the first non-zero combining coefficient. 2,1 The indicator i of the position of the first combined strongest coefficient 2,2 The first amplitude merging coefficient i 2,3 First phase merging coefficient i 2,4 The second merged coefficient information includes an indication of the position of the second merged non-zero coefficient. 3,1 The indicator i of the position of the second strongest combined coefficient 3,2 The second amplitude combining coefficient i 3,3 Second phase merging coefficient i 3,4 ; Optional third merge coefficient information, including an indication of the position of the third merge non-zero coefficient i 4′,1 The indicator i of the position of the third strongest coefficient in the merging 4′,2 The third amplitude combining coefficient i′ 4,3 Third phase merging coefficient i 4′,4 The base station obtains the precoding matrices for each layer and / or sub-band, along with the associated channel state information, reported by the terminal based on the terminal's channel state information.

[0352] Step 405: The base station makes terminal scheduling decisions based on the precoding matrices of each layer and / or each sub-band and the associated channel state information.

[0353] Step 406: Based on the channel state information and scheduling decisions described above, the base station determines the precoding matrix to be used for the final PDSCH / DMRS channel transmission and transmits accordingly.

[0354] As can be seen from the above description, the embodiments of this application realize the fusion design and rapid switching of conventional precision codebook and high precision codebook, reducing the complexity of base station codebook, measurement reference signal, and CSI reporting configuration.

[0355] The technical solutions provided in this application can be applied to a variety of systems. For example, applicable systems may include Long Term Evolution (LTE) systems, LTE Frequency Division Duplex (FDD) systems, LTE Time Division Duplex (TDD) systems, Long Term Evolution Advanced (LTE-A) systems, Universal Mobile Telecommunications System (UMTS), Worldwide Interoperability for Microwave Access (WiMAX) systems, 5G New Radio (NR) systems and their evolved communication systems, and 6G (sixth generation mobile communication technology) systems. These systems may include terminal equipment and network equipment. The systems may also include a core network component, such as the Evolved Packet Core (EPC) and the 5G Core Network (5GC).

[0356] The terminal devices involved in the embodiments of this application can be devices that provide voice and / or data connectivity to users, handheld devices with wireless connectivity, or other processing devices connected to a wireless modem. The names of the terminal devices may differ in different systems; for example, in 5G or 6G systems, the terminal device may be called User Equipment (UE). Wireless terminal devices can be USB storage devices, other personal computer memory devices, and dongles. They can also communicate with one or more core networks (CNs) via a Radio Access Network (RAN). Wireless terminal devices can be mobile terminal devices, such as mobile phones (or "cellular" phones) and computers with mobile terminal devices. For example, they can be portable, pocket-sized, handheld, computer-embedded, or vehicle-mounted mobile devices that exchange voice and / or data with the radio access network. Examples of such devices include Personal Communication Service (PCS) phones, cordless phones, Session Initiated Protocol (SIP) phones, Wireless Local Loop (WLL) stations, Personal Digital Assistants (PDAs), personal computers, tablets, and Machine-type Communication (MTC) terminal devices. Wireless terminal devices can also be referred to as systems, subscriber units, subscriber stations, mobile stations, mobile devices, remote stations, access points, remote terminals, access terminals, user terminals, user agents, user devices, and wireless access devices and routers / modems that meet the limitations of this definition; however, this application does not limit the scope of the embodiments.

[0357] The network device involved in this application embodiment can be a base station, which may include multiple cells providing services to terminals. Depending on the specific application, the base station may also be called an access point, or a device in the access network that communicates with wireless terminal devices through one or more sectors on the air interface, or other names. The network device can be used to exchange received air frames with Internet Protocol (IP) packets, acting as a router between the wireless terminal device and the rest of the access network, where the rest of the access network may include an Internet Protocol (IP) communication network. The network device can also coordinate the attribute management of the air interface. For example, the network device involved in this application embodiment can be an evolved Node B (eNB or e-NodeB) in a long term evolution (LTE) system, a 5G base station (gNB) in a next generation system, or a Home evolved Node B (HeNB), relay node, femto, pico, network testing equipment, etc., and is not limited in this application embodiment. In some network architectures, network devices may include centralized unit (CU) nodes and distributed unit (DU) nodes, which may also be geographically separated.

[0358] Network devices and terminal devices can each use one or more antennas for multiple-input multiple-output (MIMO) transmission. MIMO transmission can be single-user MIMO (SU-MIMO) or multiple-user MIMO (MU-MIMO). Depending on the configuration and number of antenna combinations, MIMO transmission can be 2D-MIMO, 3D-MIMO, FD-MIMO, or massive-MIMO, and can also be diversity transmission, precoding transmission, or beamforming transmission, etc.

[0359] like Figure 3 As shown in the embodiment of this application, the apparatus for determining the precoding matrix is ​​applied to a network device and includes: a processor 500, configured to read a program from a memory 520 and execute the following processes:

[0360] Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more of the intermediate matrices form a precoding matrix;

[0361] Receive target information sent by the terminal;

[0362] Determine the target precoding matrix based on the target information;

[0363] The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0364] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0365] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0366] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0367] Transceiver 510 is used to receive and send data under the control of processor 500.

[0368] Among them, Figure 3 In this context, the bus architecture may include any number of interconnected buses and bridges, specifically linking various circuits together, represented by one or more processors (processor 500) and memory (memory 520). The bus architecture may also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 510 may be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. The processor 500 is responsible for managing the bus architecture and general processing, and the memory 520 may store data used by the processor 500 during operation.

[0369] The processor 500 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0370] The processor 500 is responsible for managing the bus architecture and general processing, while the memory 520 can store the data used by the processor 500 when performing operations.

[0371] Processor 500 is also used to read the program and perform the following steps:

[0372] Send channel state information reporting parameters to the terminal, wherein the channel state information reporting parameters are used to report channel state information;

[0373] A reference signal is sent to the terminal, the reference signal being used for channel estimation.

[0374] The target information includes, but is not limited to, first information. The value of the intermediate matrix and the explanation of the first information can be found in the description of the foregoing method embodiments.

[0375] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0376] like Figure 4 As shown in the embodiment of this application, the apparatus for determining the precoding matrix is ​​applied to a terminal and includes: a processor 600, configured to read a program from a memory 620 and execute the following processes:

[0377] A precoding matrix is ​​generated using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0378] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0379] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0380] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0381] Transceiver 610 is used to receive and send data under the control of processor 600.

[0382] Among them, Figure 4In this context, the bus architecture can include any number of interconnected buses and bridges, specifically linking various circuits of one or more processors represented by processor 600 and memory represented by memory 620 together. The bus architecture can also link various other circuits such as peripheral devices, voltage regulators, and power management circuits, which are well known in the art and therefore will not be described further herein. The bus interface provides an interface. The transceiver 610 can be multiple elements, including transmitters and receivers, providing a unit for communicating with various other devices over a transmission medium. For different user equipment, the user interface 630 can also be an interface capable of connecting external or internal devices, including but not limited to keypads, displays, speakers, microphones, joysticks, etc.

[0383] The processor 600 is responsible for managing the bus architecture and general processing, while the memory 620 can store the data used by the processor 600 when performing operations.

[0384] The processor 600 can be a central processing unit (CPU), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or a complex programmable logic device (CPLD). The processor can also adopt a multi-core architecture.

[0385] The processor executes any of the methods described in the embodiments of this application according to the obtained executable instructions by calling a computer program stored in memory. The processor and memory may also be physically separated.

[0386] The explanation of the values ​​of the intermediate matrix can be found in the description of the aforementioned method embodiments.

[0387] The processor 600 is also used to read the program and perform the following steps:

[0388] Report the first information to the network device.

[0389] For an explanation of the first information, please refer to the description of the foregoing method embodiments.

[0390] The processor 600 is also used to read the program and perform the following steps:

[0391] Receive channel state information reporting parameters sent by network devices, wherein the channel state information reporting parameters are used to measure and report channel state information;

[0392] Receive reference signals sent by the network device;

[0393] Channel estimation is performed based on the reference signal to obtain a downlink channel matrix on one or more subcarrier sets;

[0394] Calculate the first broadband correlation matrix based on the downlink channel matrix;

[0395] A first matrix is ​​obtained based on the first broadband correlation matrix. The first matrix is ​​a matrix composed of the largest R0 principal eigenvectors of the first broadband correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R0 principal eigenvectors of the first broadband correlation matrix, where R0 is an integer greater than 0.

[0396] Based on the first matrix, determine the first merging coefficient and / or the second merging coefficient.

[0397] The method for determining the first merging coefficient and the second merging coefficient can be referred to the description of the aforementioned method embodiments.

[0398] The processor 600 is also configured to read the program and perform the following steps: obtaining the third merging coefficient. The method for determining the third merging coefficient can be referred to the description of the foregoing method embodiments. In this case, the method for determining the second merging coefficient can be referred to the description of the foregoing method embodiments.

[0399] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0400] like Figure 5 As shown, the apparatus for determining the precoding matrix according to an embodiment of this application, applied to a terminal, includes:

[0401] The first processing unit 701 is configured to generate a precoding matrix using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, the first information including: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0402] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0403] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0404] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0405] The explanation and determination methods for the first information and the values ​​of the intermediate matrix can be found in the description of the aforementioned method embodiments.

[0406] The device may further include:

[0407] The first sending unit is configured to report the first information to the network device. An explanation of the first information can be found in the description of the foregoing method embodiments.

[0408] The device may further include:

[0409] The first receiving unit is used to receive channel state information reporting parameters sent by the network device, wherein the channel state information reporting parameters are used to measure and report channel state information;

[0410] The second receiving unit is used to receive the reference signal sent by the network device;

[0411] The second processing unit is used to perform channel estimation based on the reference signal to obtain a downlink channel matrix on one or more subcarrier sets;

[0412] The third processing unit is used to calculate the first broadband correlation matrix based on the downlink channel matrix;

[0413] The fourth processing unit is used to obtain a first matrix based on the first broadband correlation matrix. The first matrix is ​​a matrix composed of the largest R0 principal eigenvectors of the first broadband correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R0 principal eigenvectors of the first broadband correlation matrix, where R0 is an integer greater than 0.

[0414] Based on the first matrix, determine the first merging coefficient and / or the second merging coefficient.

[0415] The method for determining the first merging coefficient and the second merging coefficient can be referred to the description of the aforementioned method embodiments.

[0416] The device may further include:

[0417] The fifth processing unit is used to obtain the third merging coefficient. The method for determining the third merging coefficient can be referred to the description of the foregoing method embodiments. In this case, the method for determining the second merging coefficient can be referred to the description of the foregoing method embodiments.

[0418] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0419] like Figure 6 As shown in the embodiment of this application, the apparatus for determining the precoding matrix is ​​applied to a network device and includes:

[0420] The first sending unit 801 is used to send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more intermediate matrices form a precoding matrix; the first receiving unit 802 is used to receive target information sent by the terminal; and the first processing unit 803 is used to determine a target precoding matrix based on the target information.

[0421] The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient.

[0422] Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors;

[0423] The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors;

[0424] The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

[0425] The device may further include:

[0426] The second sending unit is used to send channel state information reporting parameters to the terminal, wherein the channel state information reporting parameters are used to report channel state information;

[0427] The third transmitting unit is used to transmit a reference signal to the terminal, the reference signal being used for channel estimation.

[0428] The target information includes, but is not limited to, first information. The explanation and determination method of the first information and the value of the intermediate matrix can be referred to the description of the foregoing method embodiments.

[0429] It should be noted that the apparatus provided in this application embodiment can implement all the method steps implemented in the above method embodiment and can achieve the same technical effect. Here, the parts that are the same as those in the method embodiment and the beneficial effects will not be described in detail.

[0430] It should be noted that the division of units in the embodiments of this application is illustrative and only represents one logical functional division. In actual implementation, other division methods may be used. Furthermore, the functional units in the various embodiments of this application can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit. The integrated units described above can be implemented in hardware or as software functional units.

[0431] If the integrated unit is implemented as a software functional unit and sold or used as an independent product, it can be stored in a processor-readable storage medium. Based on this understanding, the technical solution of this application, in essence, or the part that contributes to the prior art, or all or part of the technical solution, can be embodied in the form of a computer software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) or processor to execute all or part of the steps of the methods described in the various embodiments of this application. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, read-only memory (ROM), random access memory (RAM), magnetic disks, or optical disks.

[0432] This application also provides a communication device, including: a memory, a processor, and a program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps in the method for determining a precoding matrix as described above.

[0433] This application also provides a computer program product, including computer instructions. When executed by a processor, these computer instructions implement the various processes of the above-described method embodiment for determining the precoding matrix and achieve the same technical effect. To avoid repetition, they will not be described again here.

[0434] This application also provides a processor-readable storage medium storing a program. When executed by a processor, this program implements the various processes of the above-described method embodiments for determining the precoding matrix and achieves the same technical effect. To avoid repetition, it will not be described again here. The readable storage medium can be any available medium or data storage device accessible to the processor, including but not limited to magnetic storage (e.g., floppy disks, hard disks, magnetic tapes, magneto-optical disks (MO), etc.), optical storage (e.g., CDs, DVDs, BDs, HVDs, etc.), and semiconductor storage (e.g., ROMs, EPROMs, EEPROMs, non-volatile memory (NAND flash), solid-state drives (SSDs)).

[0435] It should be noted that, in this document, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Unless otherwise specified, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes that element.

[0436] Those skilled in the art will understand that embodiments of this application can be provided as methods, systems, or computer program products. Therefore, this application can take the form of a completely hardware embodiment, a completely software embodiment, or an embodiment combining software and hardware aspects. Furthermore, this application can take the form of a computer program product implemented on one or more computer-usable storage media (including, but not limited to, disk storage and optical storage) containing computer-usable program code.

[0437] This application describes embodiments of methods, apparatus (systems), and computer program products according to embodiments of this application with reference to flowchart illustrations and / or block diagrams. It will be understood that each block of the flowchart illustrations and / or block diagrams, and combinations of blocks in the flowchart illustrations and / or block diagrams, can be implemented by computer-executable instructions. These computer-executable instructions can be provided to a processor of a general-purpose computer, special-purpose computer, embedded processor, or other programmable data processing apparatus to produce a machine, such that the instructions, which execute via the processor of the computer or other programmable data processing apparatus, generate instructions for implementing the flowchart illustrations. Figure 1 One or more processes and / or boxes Figure 1 A device that provides the functions specified in one or more boxes.

[0438] These processor-executable instructions may also be stored in a processor-readable memory that can direct a computer or other programmable data processing device to operate in a particular manner, such that the instructions stored in the processor-readable memory produce an article of manufacture including instruction means, which are implemented in a process Figure 1 One or more processes and / or boxes Figure 1 The function specified in one or more boxes.

[0439] Obviously, those skilled in the art can make various modifications and variations to the embodiments of this application without departing from the spirit and scope of the embodiments of this application. Therefore, if these modifications and variations to the embodiments of this application fall within the scope of the claims of the embodiments of this application and their equivalents, then the embodiments of this application are also intended to include these modifications and variations.

Claims

1. A method for determining a precoding matrix, characterized in that, Applied to terminals, including: A precoding matrix is ​​generated using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient. Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

2. The method according to claim 1, characterized in that, The first information also includes: a second codebook index; Wherein, the second codebook index is an index of the basis vectors selected from the second codebook, including the index of the basis vectors in the second codebook, or including the index of the basis vectors in the second codebook and the index of the intermediate basis vectors. The second codebook is a codebook composed of multiple basis vectors. The second codebook and the first codebook correspond to different vector spaces. The second merging coefficient is specifically used to perform linear merging based on the first set of basis vectors and the second codebook basis vector indicated by the second codebook index to obtain the precoding matrix.

3. The method according to claim 1, characterized in that, The first information also includes: a second codebook index and a third merging coefficient; Wherein, the second codebook index is an index of the basis vectors selected from the second codebook, including the index of the basis vectors in the second codebook, or including the index of the basis vectors in the second codebook and the index of the intermediate basis vectors. The second codebook is a codebook composed of multiple basis vectors. The second codebook and the first codebook correspond to different vector spaces. The second merging coefficient is specifically used to perform linear merging based on the first basis vector set to obtain the second basis vector set; The third merging coefficient is used to linearly merge the basis vector indicated by the second codebook index and the second set of basis vectors to obtain the precoding matrix.

4. The method according to claim 1, characterized in that, The values ​​of the intermediate matrix are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0. The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, wherein the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0; The first basis vector set is linearly merged using the matrix corresponding to the second merging coefficient to obtain the precoding matrix. The number of columns in the precoding matrix is ​​RI, where RI is the number of layers in the precoding matrix and is an integer greater than 0.

5. The method according to claim 1, characterized in that, The intermediate values ​​are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0. Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0; The first basis vector set is linearly merged using the matrix corresponding to the second merging coefficient to obtain the precoding matrix. The number of columns in the precoding matrix is ​​RI, where RI is the number of layers in the precoding matrix and is an integer greater than 0.

6. The method according to claim 5, characterized in that, The step of linearly merging the first basis vector set using the matrix corresponding to the second merging coefficient to obtain the precoding matrix includes: The precoding matrix is ​​obtained by selecting individual basis vectors from the first basis vector set using the matrix corresponding to the second merging coefficient and adding inter-polarity merging factors.

7. The method according to claim 2, characterized in that, The values ​​of the intermediate matrix are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. L basis vectors are selected in each polarization direction, where L is an integer greater than 0. The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, where the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0. The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is K, and K is an integer greater than 0. The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the second set of basis vectors, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

8. The method according to claim 2, characterized in that, The values ​​of the intermediate matrix are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0. Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0; The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is K, and K is an integer greater than 0. The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the second set of basis vectors, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

9. The method according to claim 3, characterized in that, The values ​​of the intermediate matrix are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0. The basis vectors of the two polarization directions are linearly merged using the first merging coefficient to obtain the first basis vector set, wherein the number of basis vectors in the first basis vector set is R0, and R0 is an integer greater than 0; The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is R1, and R1 is an integer greater than 0. The second basis vector set is merged using the third merging coefficient to obtain a third basis vector set, wherein the number of columns in the third basis vector set is K, and K is an integer greater than 0; The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the third basis vector set, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

10. The method according to claim 3, characterized in that, The values ​​of the intermediate matrix are determined as follows: The first codebook index is used to obtain the basis vectors of the first codebook in two polarization directions. There are L basis vectors in each polarization direction, where L is an integer greater than 0. Using the first merging coefficient and the basis vector indicated by the first codebook index in each polarization direction, the first basis vector set is obtained, wherein the number of basis vectors in the first basis vector set is 2R0, and there are R0 basis vectors in each polarization direction, where R0 is an integer greater than 0; The first basis vector set is linearly merged using the second merging coefficient to obtain a second basis vector set, where the number of columns in the second basis vector set is R1, and R1 is an integer greater than 0. The second basis vector set is merged using the third merging coefficient to obtain a third basis vector set, wherein the number of columns in the third basis vector set is K, and K is an integer greater than 0; The precoding matrix is ​​obtained by linearly merging the basis vectors indicated by the second codebook index using the third basis vector set, wherein the basis vectors indicated by the second codebook index are K basis vectors of length N. subband The row vectors of the precoding matrix have N columns. subband N subband This represents the number of subbands reported by the terminal, and is a positive integer.

11. The method according to any one of claims 1-3, characterized in that, The method further includes: Report the first information to the network device.

12. The method according to claim 11, characterized in that, One or more of the first codebook and the second codebook are based on broadband or subband feedback in the frequency domain and on the first feedback cycle feedback in the time domain. One or more of the first codebook index and the second codebook index are based on wideband feedback in the frequency domain and on second feedback period feedback in the time domain; The first merging coefficient is based on broadband or subband feedback in the frequency domain and on third feedback cycle feedback in the time domain; The second combining coefficient is based on sub-band feedback in the frequency domain and on fourth feedback cycle feedback in the time domain; The third merging coefficient is based on broadband feedback in the frequency domain and on the fifth feedback cycle in the time domain; Among them, the lengths of any two feedback cycles in the first to fifth feedback cycles are the same or different.

13. The method according to any one of claims 1-3, characterized in that, The first merging coefficient includes K 01 K is a non-zero coefficient. 01 It is an integer greater than 0; Wherein, the first merging coefficient includes one or more of the following: an indication of the position of the first non-zero merging coefficient, an indication of the position of the first strongest merging coefficient, a first amplitude merging coefficient, and a first phase merging coefficient; Wherein, the first merged coefficient is an indicator of the position of the non-zero coefficient, used to indicate the position information of the non-zero coefficients in each column of the matrix corresponding to the first merged coefficient; The indicator of the position of the first merged strongest coefficient is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the first merged coefficient; The first amplitude combining coefficient is used to indicate the linear combining amplitude scaling coefficient information of each column in the matrix corresponding to the first combining coefficient; The first phase merging coefficient is used to indicate the coefficient information of the linear merging phase adjustment of each column in the matrix corresponding to the first merging coefficient.

14. The method according to claim 2, characterized in that, The second merging coefficient includes K 02 K is a non-zero coefficient. 02 It is an integer greater than 0; Wherein, the second merging coefficient includes one or more of the following: an indication of the position of the second non-zero merging coefficient, an indication of the position of the second strongest merging coefficient, a second amplitude merging coefficient, and a second phase merging coefficient; Wherein, the second merged non-zero coefficient position indicator is used to indicate the position information of the non-zero coefficients in each column of the matrix corresponding to the second merged coefficient; The indicator of the position of the second strongest coefficient is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the second combined coefficient; The second amplitude combining coefficient is used to indicate the linear combining amplitude scaling factor information of each column in the matrix corresponding to the second combining coefficient; The second phase merging coefficient is used to indicate the coefficient information of the linear merging phase adjustment of each column in the matrix corresponding to the second merging coefficient.

15. The method according to claim 3, characterized in that, The third merging coefficient includes K. 03 K is a non-zero coefficient. 03 It is an integer greater than 0; The third merging coefficient includes one or more of the following: an indication of the position of the third merging non-zero coefficient, an indication of the position of the third merging strongest coefficient, a third amplitude merging coefficient, and a third phase merging coefficient; The third merged coefficient is an indicator of the position of non-zero coefficients, used to indicate the position information of non-zero coefficients in each column of the matrix corresponding to the third merged coefficient. The indicator of the position of the third combined strongest coefficient is used to indicate the position information of the strongest coefficient in each column of the matrix corresponding to the third combined coefficient. The third amplitude combining coefficient is used to indicate the linear combining amplitude scaling coefficient information of each column in the matrix corresponding to the third combining coefficient; The third phase merging coefficient is used to indicate the coefficient information of the linear merging phase adjustment of each column in the matrix corresponding to the third merging coefficient.

16. The method according to claim 1, characterized in that, The method further includes: Receive channel state information reporting parameters sent by network devices, wherein the channel state information reporting parameters are used to measure and report channel state information; Receive reference signals sent by the network device; Channel estimation is performed based on the reference signal to obtain a downlink channel matrix on one or more subcarrier sets; Calculate the first broadband correlation matrix based on the downlink channel matrix; A first matrix is ​​obtained based on the first broadband correlation matrix. The first matrix is ​​a matrix composed of the largest R0 principal eigenvectors of the first broadband correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R0 principal eigenvectors of the first broadband correlation matrix, where R0 is an integer greater than 0. Based on the first matrix, determine the first merging coefficient and / or the second merging coefficient.

17. The method according to claim 16, characterized in that, Determining the first merging coefficient includes: The first codebook index is determined based on the first broadband correlation matrix and the first codebook; The first merging coefficient is obtained based on the first codebook index and the first matrix.

18. The method according to claim 17, characterized in that, Determining the second merging coefficient includes: Based on the channel state information of any sub-band within the bandwidth reported by the Channel State Information (CSI), the first codebook index, and the first combining coefficient, the second combining coefficient associated with the sub-band is determined.

19. The method according to claim 17, characterized in that, Determining the second merging coefficient includes: Based on the channel state information of any subband within the CSI reported bandwidth, the first codebook index, and the first merging coefficient, the possible column selection vectors and merging factors are traversed to determine the second merging coefficient associated with the subband, wherein the column selection vector is a basis vector in a set of first basis vectors determined based on the first codebook index and the first merging coefficient.

20. The method according to claim 17, characterized in that, Determining the second merging coefficient includes: Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reported bandwidth; The second codebook index is determined based on the second broadband correlation matrix and the second codebook; The third matrix is ​​obtained based on the channel state information of any sub-band within the CSI reported bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band. The second merging coefficient is obtained based on the first codebook index, the first merging coefficient, the third matrix, and the second codebook index.

21. The method according to claim 17, characterized in that, Determining the second merging coefficient includes: Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reported bandwidth; The second codebook index is determined based on the second broadband correlation matrix and the second codebook; The third matrix is ​​obtained based on the channel state information of any sub-band within the CSI reported bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band. The fourth merging coefficient is determined based on the third matrix, the first codebook index, and the first merging coefficient. The second merging coefficient is obtained based on the fourth merging coefficient and the second codebook index.

22. The method according to claim 17, characterized in that, Determining the second merging coefficient includes: Based on the channel state information of any sub-band within the CSI reported bandwidth, the first codebook index, the first merging coefficient, and the second codebook index, the second merging coefficient associated with the sub-band is determined.

23. The method according to claim 17, characterized in that, The method further includes: Calculate the second broadband correlation matrix based on the downlink channel matrix within the CSI reported bandwidth; The second codebook index is determined based on the second broadband correlation matrix and the second codebook; Based on the second bandwidth correlation matrix, a fourth matrix is ​​obtained. The fourth matrix is ​​a matrix composed of the largest R1 principal eigenvectors of the second bandwidth correlation matrix, or it is a matrix obtained by linear transformation or linear combination of the largest R1 principal eigenvectors of the second bandwidth correlation matrix, where R1 is an integer greater than 0. The third merging coefficient is obtained based on the fourth matrix and the second codebook index.

24. The method according to claim 23, characterized in that, Determining the second merging coefficient includes: The third matrix is ​​obtained based on the channel state information of any sub-band within the CSI reported bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band. The fourth merging coefficient is determined based on the third matrix, the first codebook index, and the first merging coefficient. The second merging coefficient is obtained based on the second codebook index, the third merging coefficient, and the fourth merging coefficient.

25. The method according to claim 23, characterized in that, Determining the second merging coefficient includes: The third matrix is ​​obtained based on the channel state information of any sub-band within the CSI reported bandwidth. The third matrix is ​​a matrix composed of the largest principal eigenvector of the first sub-band correlation matrix. The first sub-band correlation matrix is ​​a sub-band correlation matrix calculated based on the downlink channel state information of the sub-band. The second merging coefficient is obtained based on the first codebook index, the first merging coefficient, the third matrix, the second codebook index, and the third merging coefficient.

26. A method for determining a precoding matrix, characterized in that, Applied to network devices, including: Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more of the intermediate matrices form a precoding matrix; Receive target information sent by the terminal; Determine the target precoding matrix based on the target information; The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient. Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

27. The method according to claim 26, characterized in that, The first information also includes: a second codebook index; Wherein, the second codebook index is an index of the basis vectors selected from the second codebook, including the index of the basis vectors in the second codebook, or including the index of the basis vectors in the second codebook and the index of the intermediate basis vectors. The second codebook is a codebook composed of basis vectors. The second codebook and the first codebook correspond to different vector spaces. The second merging coefficient is used to perform linear merging based on the first set of basis vectors and the second codebook basis vector indicated by the second codebook index to obtain the precoding matrix.

28. The method according to claim 26, characterized in that, The first information also includes: a second codebook index and a third merging coefficient; Wherein, the second codebook index is an index of the basis vectors selected from the second codebook, including the index of the basis vectors in the second codebook, or including the index of the basis vectors in the second codebook and the index of the intermediate basis vectors. The second codebook is a codebook composed of basis vectors. The second codebook and the first codebook correspond to different vector spaces. The second merging coefficient is used to perform linear merging based on the first basis vector set to obtain a second basis vector set; The third merging coefficient is used to linearly merge the basis vector indicated by the second codebook index and the second set of basis vectors to obtain the precoding matrix.

29. An apparatus for determining a precoding matrix, characterized in that, Applications in terminals include: memory, transceiver, and processor. A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations: A precoding matrix is ​​generated using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient. Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

30. An apparatus for determining a precoding matrix, characterized in that, Applications in network devices, including: memory, transceivers, and processors. A memory for storing computer programs; a transceiver for sending and receiving data under the control of the processor; and a processor for reading the computer programs from the memory and performing the following operations: Send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more of the intermediate matrices form a precoding matrix; Receive target information sent by the terminal; Determine the target precoding matrix based on the target information; The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient. Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

31. An apparatus for determining a precoding matrix, characterized in that, Applied to terminals, including: The first processing unit is configured to generate a precoding matrix using one or more intermediate matrices, wherein the values ​​of the intermediate matrices are determined based on first information, the first information including: a first codebook index, a first merging coefficient, and a second merging coefficient; Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

32. An apparatus for determining a precoding matrix, characterized in that, Applied to network devices, including: The first sending unit is used to send codebook parameters to the terminal, wherein the codebook parameters are used to determine the values ​​of intermediate matrices, and one or more intermediate matrices form a precoding matrix; The first receiving unit is used to receive target information sent by the terminal; The first processing unit is used to determine the target precoding matrix based on the target information; The value of the intermediate matrix is ​​determined based on the first information, which includes: a first codebook index, a first merging coefficient, and a second merging coefficient. Wherein, the first codebook index is an index selected from the basis vectors of the first codebook, and the first codebook is a codebook composed of multiple basis vectors; The first merging coefficient is used to linearly merge the basis vectors indicated by the first codebook index to obtain a first set of basis vectors; The second merging coefficient is used to perform linear merging based on the first set of basis vectors, wherein the result of the linear merging is used to obtain the precoding matrix.

33. A processor-readable storage medium, characterized in that, The processor-readable storage medium stores a program for causing the processor to perform the method as described in any one of claims 1 to 28.

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