Channel information feedback method, electronic device, and storage medium

Abstract

Provided in the present application are a channel information feedback method, an electronic device, and a storage medium. The method comprises: acquiring channel parameters of a measurement channel; determining a codebook set for channel quantization feedback of the channel; selecting from the codebook set a codeword Ws used for channel quantization characterization of a sub-band s; and determining an indication parameter of the codeword Ws, and feeding the indication parameter back to a sending end, wherein the codeword Ws is a matrix having r columns, the codeword Ws is composed of r column vectors, at least one of the r column vectors is composed of a base vector uS, and the base vector uS satisfies the following model: [equation 1], there being at least one column vector determined from among v^1^s, v^2^s,..., v^k^s by means of extracting a column from a matrix XS, and the matrix XS being determined on the basis of the frequency-domain position of the sub-band or a sub-band index s.

Description

Channel information feedback method, electronic device and storage medium Technical Field

[0001] The present application relates to the field of wireless communication technology, and in particular to a channel information feedback method, an electronic device, and a storage medium. Background Art

[0002] In order to further improve the communication quality gains brought by Multiple-Input Multiple-Output (MIMO) technology, large-scale antenna technology is adopted in the fifth generation of mobile communication technology (5G). Among them, the antenna of the base station can include a large number of antenna units and transceiver units. For example, the number of antenna units and transceiver units can be 128, 256 or 512, and the terminal can also be configured with an antenna array composed of a large number of antenna units. In the sixth generation of mobile communication technology, the concept of ultra-large-scale MIMO was proposed, and the number of base station antennas increased further. In addition, as a possible new technology for the sixth generation of mobile communication technology (6G), the number of units of smart metasurfaces may reach thousands or even tens of thousands, and they also face the problem of changes in channel characteristics and transmission design due to the extremely large number of units.

[0003] During communication, signals can be sent, reflected or received through multiple antennas of the base station, the Reconfigurable Intelligence Surface (RIS) and the terminal to reduce signal attenuation and improve communication quality. Generally speaking, in a 5G communication system, a codebook-based transmission scheme or a non-codebook-based transmission scheme can be adopted. Among them, for the codebook-based transmission scheme, it means that multiple codebooks are pre-configured at the base station and the terminal, each codebook contains multiple precoding matrices, and the precoding matrix contained in the selected codebook is determined, and the final determined precoding matrix is ​​used for data transmission. The base station determines the codebook parameters used by the terminal based on the sounding reference signal resources reported by the terminal, and notifies the terminal of the codebook parameters. The terminal determines the corresponding codebook based on the notification of the base station. In order to characterize the channel quantization of subband s, it is necessary to select a codeword Ws. However, for different subbands, the selected codewords Ws are extracted column by column from the same matrix Xs and combined according to a certain agreed method. When the number of antenna ports increases, the oversampling factor is increased, or the bandwidth increases, the channel quantization standards of different subbands vary greatly. At this time, for different subbands i and subband j, if their codewords Wi and Wj are extracted column by column from the same matrix and combined according to a certain agreed method, large errors may occur in the quantization channel. Summary of the Invention

[0004] The embodiments of the present application aim to provide a channel information feedback method, an electronic device, and a storage medium to solve the channel information feedback problem of a wireless communication channel. By determining a matrix based on the frequency domain position or subband index, the channel quantization accuracy can be improved and the channel feedback error can be reduced.

[0005] An embodiment of the present application provides a channel information feedback method, wherein the method includes:

[0006] Acquire channel parameters of the measurement channel; determine a codebook set for channel quantization feedback of the channel; select a codeword W for subband s channel quantization characterization from the codebook set s ; Determine the code word W s The codeword W s is a matrix with r columns, where r is greater than or equal to 1; the codeword W s By r column vectors Composition, wherein the r column vectors At least one of them is composed of basis vectors u s Composition, wherein the basis vector u s The following model is satisfied:

[0007] described There is at least one column vector in the matrix X s The extracted columns are determined in the matrix X s Determined according to the frequency domain position of the subband or the subband index s.

[0008] An embodiment of the present application further provides an electronic device, comprising:

[0009] One or more processors; a memory for storing one or more programs; when the one or more programs are executed by the one or more processors, the one or more processors implement the channel information feedback method as described in any one of the embodiments of the present application.

[0010] An embodiment of the present application further provides a computer-readable storage medium, wherein the computer-readable storage medium stores one or more programs, and the one or more programs are executed by one or more processors to implement the channel information feedback method as described in any one of the embodiments of the present application. BRIEF DESCRIPTION OF THE DRAWINGS

[0011] FIG1 is a flow chart of a channel information feedback method provided in an embodiment of the present application;

[0012] FIG2 is an example diagram of an indication parameter relationship provided in an embodiment of the present application;

[0013] FIG3 is another example diagram of an indication parameter relationship provided in an embodiment of the present application;

[0014] FIG4 is an example diagram of beamforming provided in an embodiment of the present application;

[0015] FIG5 is an example diagram of another beamforming provided in an embodiment of the present application;

[0016] FIG6 is an example diagram of another beamforming provided in an embodiment of the present application;

[0017] FIG7 is an example diagram of beam selection provided in an embodiment of the present application;

[0018] FIG8 is an example diagram of another beam selection provided in an embodiment of the present application;

[0019] FIG9 is an example diagram of another beam selection provided in an embodiment of the present application;

[0020] FIG10 is an example diagram of another beam selection provided in an embodiment of the present application;

[0021] FIG11 is a schematic structural diagram of a channel information feedback device provided in an embodiment of the present application;

[0022] FIG12 is a schematic structural diagram of an electronic device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0023] In the subsequent description, suffixes such as "module", "component" or "unit" used to represent elements are only used to facilitate the description of this application and have no specific meaning. Therefore, "module", "component" or "unit" can be used interchangeably.

[0024] FIG1 is a flow chart of a channel information feedback method provided in an embodiment of the present application. The present application is applicable to situations where channel information feedback is provided. The method can be performed by a channel information feedback device, generally applied to a receiving end. The device can be implemented in software and / or hardware. Referring to FIG1 , the method provided in an embodiment of the present application includes:

[0025] 110. Obtain channel parameters of the measurement channel.

[0026] In the embodiment of the present application, channel parameters generated by channel measurement may be obtained.

[0027] 120. Determine a codebook set for channel quantization feedback of the channel.

[0028] A codebook set for performing channel quantization feedback on a channel may be determined.

[0029] 130. Select the codeword W for the quantization representation of the subband s channel from the codebook set s .

[0030] In the embodiment of the present application, a codeword W for quantization representation of subband s can be selected from the codebook set. s .

[0031] 140. Determine codeword W s The codeword W s is a matrix with r columns, where r is greater than or equal to 1; codeword W s By r column vectors Composition, where r column vectors At least one of them is composed of basis vectors u s Composition, where the basis vector u s The following model is satisfied:

[0032] There is at least one column vector in the matrix X s The extracted columns are determined, the matrix X s Determined according to the frequency domain position of the subband or the subband index s.

[0033] In the embodiment of the present application, it is possible to determine the code word W s The codeword W s It can be composed of a matrix of r columns, and each column vector can be written as Codeword W s At least one of the column vectors is composed of basis vectors u s The basis vector u s It can be expressed as:

[0034] There is at least one column vector from the matrix X s , the matrix X s It can be determined by the frequency domain position of the subband or the subband index s.

[0035] In an exemplary embodiment, a codebook can be constructed using several precoding matrices in the embodiment of the present application. The contents of the codebook can be known to both the transmitter and the receiver. The UE measures the downlink channel based on the common pilot and obtains the channel matrix. Based on the pre-set codebook, the UE can select the precoding matrix that best matches the current channel conditions from the codebook according to a certain optimization criterion and feed back its label to the base station via the feedback link. To characterize the quantization of the subband s channel, it is necessary to select the codeword W s For different sub-bands, the selected codeword W s is from the same matrix X sThe codewords W are extracted by columns and combined according to a certain agreed method. However, when the number of antenna ports increases, the oversampling factor increases, or the bandwidth increases, the channel quantization representations of different subbands vary greatly. In this case, for different subbands i and j, if their codewords W i and W j From the same matrix X i =X j The design may have a large error with the actual quantization channel by extracting by column and combining according to a certain agreed method.

[0036] In some embodiments, for antennas in two dimensions, the matrix X corresponding to the subband s is s Using 2D codewords. Thus X s Each submatrix of has a 2-dimensional where u m and v n are the discrete Fourier vectors of the first and second dimensions, Indicates u m and v n The number of ports in the first dimension is N1, and the number of ports in the second dimension is N2. The Discrete Fourier Transform (DFT) corresponding to the ports in the first dimension is oversampled by a factor of O1, and the DFT corresponding to the ports in the second dimension is oversampled by a factor of O2. The number of discrete Fourier vectors of the first-dimensional or second-dimensional antenna is a multiple of the oversampling factor of the number of ports. Therefore, the value range of m is [1, ... O1N1], and the value range of n is [1, ... O2N2].

[0037] X s Submatrix of The form of is related to the antenna structure. Take a two-dimensional matrix array as an example:

[0038] Among them, P1 and P2 are the value range sets of m and n respectively.

[0039] For the dual polarization case, we have:

[0040] W s The dimension of depends on the dimensions of C1 and C2, that is, the number of column vectors k1 in C1, the number of column vectors k2 in C2, N1, and N2. The values ​​of k1 and k2 are directly configured by the base station, determined according to agreed rules, or determined by information such as layer, N2, and codebookMode.

[0041] In some embodiments, for antennas in two dimensions, the matrix X corresponding to the subband s is s Using 1D codeword. Thus Xs Each submatrix of has the form 1-dimensional where u m and v n are the discrete Fourier vectors of the first and second dimensions, Indicates u m and v n Kronecker product. vec indicates that the matrix is ​​vectorized by rows or columns.

[0042] X s The form of the sub-vector is related to the antenna structure. Taking a one-dimensional matrix array as an example:

[0043] For the dual polarization case, we have:

[0044] A possible matrix X s The construction method is X s =[W l,l′,m,m′,n W l,l′,m+1,m′,n W l+1,l′,m,m′,n W l+1,l′,m+1,m′,n ]

[0045] In an exemplary embodiment, when layer=1 and codebookMode=2, if N2=1, then k1=4, k2=1, and the relationship between the parameters can be shown in Figure 2, where the horizontal axis represents mindex and the vertical axis represents n index.

[0046] In another exemplary embodiment, if N2>1, then k1=2, k2=2, and the relationship between the parameters may be as shown in FIG3 , where the horizontal axis represents the m index and the vertical axis represents the n index.

[0047] In the embodiment of the present application, the selection of m and n depends on the parameter i1, and for different sub-bands i and j, X i and X j are the same; for example, when layer=1, codebookMode=2, N2>1, i1={i 11 ,i 12}Selected X s (s=i or j) The corresponding C1 indicator parameter is i 11 ,i 11 +1, the corresponding C2 indicator parameter is i 12 、i 12 +1. That is, referring to Figure 4, the same X is configured for different sub-bands. s .

[0048] In Figure 4, black dots correspond to orthogonal DFT beams without oversampling, white dots represent oversampling beams, and dots that are not black / white represent the components of X s The beam, here X s Each block B of contains 4 sub-matrices Among them, the horizontal axis coordinate dimension is N2O2, the vertical axis coordinate dimension is N1O1, and the same row beam corresponds to the same u m , the same beam corresponds to the same v n , here is u m 、u m+1 、v n 、v n+1 , which constitutes B:

[0049] Among them, the columns in B can be exchanged. It is called a sub-matrix or codeword block.

[0050] Alternatively, in Figure 4, black dots correspond to orthogonal DFT beams without oversampling, white dots represent oversampled beams, and dots that are not black / white represent the components of X s The beam, here X s Each block B of contains 2 sub-vectors Among them, u m and v n are the discrete Fourier vectors of the first and second dimensions, Indicates u m and v n Kronecker product, vec means that the matrix is ​​vectorized by row or column, the horizontal axis coordinate dimension is N2O2, the vertical axis coordinate dimension is N1O1, and the same row beam corresponds to the same u m , the same beam corresponds to the same v n , here is u m 、u m+1 、v n 、v n+1 , which constitutes B:

[0051] Among them, the columns in B can be exchanged, here are called subvectors.

[0052] However, with the increase of the number of antennas / oversampling factor / carrier / bandwidth, the same X s Not applicable to all sub-bands.

[0053] To solve this problem, make X s It is determined according to the frequency domain position of the subband or the subband index s of the subband.

[0054] In some exemplary embodiments, referring to FIG4 , when i=1, u is selected m =DFT6, DFT7, v n =DFT7, DFT8; see Figure 5, when i = 4, select u m =DFT6, DFT7, v n =DFT8, DFT9; see Figure 6, when i = 8, select u m =DFT7, DFT8, v n =DFT8, DFT9, where DFTq represents the qth DFT beam / vector, and q is an integer.

[0055] In an exemplary embodiment, let the target pointing angle be θ and the center frequency be f c Take the Uniform Linear Array (ULA) as an example for analysis. The path delay between adjacent antennas is:

[0056] Corresponding delay

[0057] Here f c represents the center frequency, λ c Indicates the wavelength corresponding to the center frequency.

[0058] In uplink transmission, assuming that the signal received by the first antenna is s(t), the signal received by the mth antenna is:

[0059] Therefore, the equivalent baseband signal is:

[0060] For broadband systems, the frequencies of different sub-bands vary significantly. Consider the pointing angles at different frequencies. During communication, the relative angle between the base station and the user remains unchanged, but changes in the sub-band frequency will cause changes in the beam pointing direction. The corresponding uplink received signal is:

[0061] Therefore, the spatial-time channel can be modeled as:

[0062] Assuming that the difference between the subband frequency and the center frequency is Δf, the corresponding spatial-frequency channel is:

[0063] Where a represents the steering vector, a(x) = [1exp(j2πx)…exp(j2π(M-1)x)] T .

[0064] For a uniform planar array (UPA), its spatial-frequency channel can be expressed as a Kronecker product. One possible scenario is:

[0065] Where θ and φ represent the elevation angle and azimuth angle of the transmission path, respectively. Based on (*1) and (*2), it can be found that the direction of the channel steering vector is related to the subcarrier frequency. For different subbands, the index is the same, but because the target channels corresponding to different subbands are different, the X corresponding to different subbands is the same. s At least, when the sub-band frequencies differ greatly, the best codewords for different sub-bands cannot be selected from the same X. s cover.

[0066] In the embodiment of the present application, there are at least two sub-bands i and j, and the corresponding matrices X i and matrix X j Satisfy at least one of the following relationships:

[0067] Matrix X i According to the matrix X j Determine, and, the matrix X i and matrix X j Not exactly the same; the matrix X i and matrix X j It is generated by the same function F, where the independent variables of function F are determined or partially determined by i and j respectively; the matrix X i and matrix X j They are constructed and generated by the same function F, where the independent variables of the function F are determined or partially determined by the frequencies corresponding to sub-band i and sub-band j respectively.

[0068] In the embodiment of the present application, sub-band i and sub-band j may correspond to different matrices X i and matrix X j , and the matrix X i Can be combined with the matrix X j There are some relationships, the matrix X i According to the matrix X j OK, but the matrix X i and matrix X j are not identical; alternatively, the matrix X i and matrix X j It can be generated by the same function F, the independent variable of which can be determined or partially determined by i and j; or, the matrix X i and matrix X j It can be generated by the same function F, and the independent variable of the function F can be determined or partially determined by the frequencies corresponding to sub-band i and sub-band j.

[0069] In some application embodiments, the matrix X s The first dimension discrete Fourier vector u m and the second-dimensional discrete Fourier vector v n The Kronecker product of .

[0070] In some embodiments of the present invention, the function F is based on the matrix X s The first dimension of the discrete Fourier vector u m Configuration parameters N1 and the second-dimensional discrete Fourier vector v n The configuration parameter N2 is determined.

[0071] In the embodiment of the application, the matrix X is determined i and matrix X j The function F can be represented by the matrix X s The first dimension of the discrete Fourier vector u m Configuration parameters N1 and the second-dimensional discrete Fourier vector v n The configuration parameter N1 and the configuration parameter N2 may be the number of rows or the number of columns of the matrix.

[0072] In some other application embodiments, the function F is based on the matrix X s The first dimension of the discrete Fourier vector u m Oversampling multiple O1 and the second dimension discrete Fourier vector v n The oversampling multiple O2 is determined.

[0073] In the embodiment of the present application, the function F can be a discrete Fourier vector u of the first dimension m Oversampling multiple O1 and the second dimension discrete Fourier vector v n The oversampling multiple O2 is determined, that is, O1 and O2 can affect the form of the function F.

[0074] In some other application embodiments, the function F is based on the matrix X S The indicator parameter i1 is determined.

[0075] In the embodiment of the present application, the matrix X S The indicator parameter i1 can be in the form of a function F that determines the composition.

[0076] In some other application embodiments, the matrix X is constructed i The discrete Fourier vector of The determined steering vector, where θ represents the target pointing angle, and f C represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0077] In some application embodiments, the matrix X is constructed S The parameter ψ of the discrete Fourier vector is close to Among them, q() represents a function, θ represents the target pointing angle, and f C represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0078] In some application embodiments, the matrix X i A set of sub-matrices is selected from a preset codebook and constructed in a preset form.

[0079] Matrix X i A set of sub-matrices is selected from a preset codebook and constructed in a preset form.

[0080] In some embodiments, the preset codebook includes:

[0081] Wherein, T represents transpose, N1 and N2 are the number of columns or dimension parameters of the first-dimensional discrete Fourier vector and the number of columns or dimension parameters of the second-dimensional discrete Fourier vector, respectively, O1 and O2 are the oversampling multiples of the first-dimensional discrete Fourier vector and the oversampling multiples of the second-dimensional discrete Fourier vector, respectively, m and n are the indicator parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively.

[0082] In some application embodiments, the parameter ψ corresponding to the middle value of the value range of m is close to Among them, q() represents a function, θ represents the target pointing angle, and f C represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0083] In other application embodiments, the middle value of the value range of m is Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f C represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0084] In some application embodiments, the matrix X i A group of sub-matrices or sub-vectors is determined based on the obtained value range of m.

[0085] In the embodiment of the present application, a group of sub-matrices or sub-vectors can be determined by the value range of m, and the matrix matrix X can be formed by the sub-matrices or sub-vectors. i .

[0086] In some application embodiments, the value range of m includes at least one of the following:

[0087] Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected in m; m includes at least m mid or m mid +1 at least one; where m mid Indicates the middle value of the range of m.

[0088] Based on the above application examples, Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0089] Based on the above application embodiment, the parameter ψ corresponding to the middle value of the value range of n is close to Among them, q() represents a function, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0090] In some application embodiments, the middle value of the range of values ​​of n is Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0091] In some application embodiments, the matrix X i A group of sub-matrices or sub-vectors is determined based on the obtained value range of n.

[0092] In the embodiment of the present application, the value range of n can be determined, and a group of sub-matrices or sub-vectors can be determined based on the value range of n. The matrix X can be determined from the group of sub-matrices or sub-vectors. i .

[0093] Based on the above application embodiment, the value range of n includes at least one of the following:

[0094] Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected in ; n includes at least n mid or n mid +1 at least one; where n mid Indicates the middle value of the range of n.

[0095] In other application embodiments, Where q() represents a function, floor(x) represents an integer not greater than x but close to x, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0096] Based on the above application embodiment, the function includes at least one of the following:

[0097] in, represents an integer not greater than x but close to x; q(x)=x; q(x)=x+1 / 2.

[0098] Based on some application examples, the value ranges of m and n are respectively and Wherein, k1 and k2 are the number of vectors of vector P1 and vector P2 respectively.

[0099] In some application embodiments, the frequency difference between sub-band i and sub-band j is greater than a preset threshold, and the value range of m includes: t is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to an agreed rule, and k1 is the number of vectors in the vector P1.

[0100] In some other application embodiments, the frequency difference between sub-band i and sub-band j is greater than a preset threshold, and the value range of n includes: r is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to an agreed rule, and k2 is the number of vectors in the vector P2.

[0101] Based on the above application embodiment, the preset threshold includes at least one of the following:

[0102] or

[0103] Among them, f c represents the center frequency, θ represents the target pointing angle, and φ represents the azimuth angle.

[0104] In an exemplary embodiment, if the bandwidth is greater than a certain threshold, different frequency resource units may correspond to different beams. In order to align different frequency beams at the same user (UE) location, the precoding for different frequency resource units should be different.

[0105] In one embodiment, the matrix X s The selection method may include determining X according to different sub-band frequencies s , for different subbands i and j, the matrix X i and matrix X j It can be constructed by a function F, whose independent variables are i and j.

[0106] Let the center frequency be f c , where the center frequency can be the frequency corresponding to twice the array element spacing, that is, f c =c / (2d), where c represents the speed of light, d represents the spacing between array elements, and d = λ c / 2. For sub-band i, let the frequency difference between it and the center frequency be Δf i .

[0107] Taking N2=1 as an example, a possible precoding matrix selection scheme is that the selected DFT vector should be as close as possible to

[0108] Taking N2=1 as an example, a possible precoding matrix selection scheme is that the parameter ψ of the selected DFT vector should be as close as possible to

[0109] The parameter ψ of the DFT vector here refers to v(ψ) = [1exp(j2πψ)…exp(j2π(M-1)ψ)] T The parameter ψ,q() in ψ represents a function, and the form of the function can include at least one of the following:

[0110] in, represents an integer not greater than x but close to x; q(x)=x; q(x)=x+1 / 2.

[0111] In some exemplary embodiments, a set of submatrices is selected from a preset codebook. or a set of subvectors And construct the matrix X in a certain form i .

[0112] In some embodiments, the preset codebook may include:

[0113] Wherein, T represents transpose, N1 and N2 are the number of columns or configuration parameters of the first-dimensional discrete Fourier vector and the number of columns or configuration parameters of the second-dimensional discrete Fourier vector, respectively, O1 and O2 are the oversampling multiples of the first-dimensional discrete Fourier vector and the oversampling multiples of the second-dimensional discrete Fourier vector, respectively, m and n are the indicator parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively.

[0114] You can set X i The corresponding selected non-repeating column submatrix or subvector v m,n The number of P, X i The values ​​of m and n in can be changed continuously or selected discontinuously according to certain rules. The embodiment of the present application takes the continuous selection of the values ​​of m and n as an example.

[0115] The middle value m of the range of m mid The corresponding ψ, that is, As close as possible

[0116] For the case where the total number of elements E in the value range of m is an odd number, the middle value m mid =(E+1) / 2.

[0117] For the case where the total number of elements E in the value range of m is an even number, the middle value m mid =E / 2 or m mid =E / 2+1.

[0118] In some application embodiments, the middle value of the range of m

[0119] The corresponding value range of m can include:

[0120] Where mod(T,2)=0, P is the matrix X i The number of non-repeating sub-matrices or sub-vectors selected in ; or, Where mod(P,2)=0, P is the matrix X i The number of non-repeating sub-matrices or sub-vectors selected in ; or, Where mod(P,2)=1, P is the matrix X iThe number of non-repeated sub-matrices or sub-vectors selected in ; or, m includes at least m mid or m mid +1 at least one; where m mid Indicates the middle value of the range of m, and mod indicates the modulo operation.

[0121] In some application embodiments, when N2 is not 1, v m,n The calculation method is the same. Based on the Kronecker product representation, first calculate u n , then calculate v m,n .

[0122] Based on the above application embodiment, assuming that the frequency difference between adjacent frequency sub-bands is Δf, the middle value m of the value range of m is mid It can be expressed as follows:

[0123] Then X i It is generated by the function F, whose independent variable can include i; for different sub-bands i and j, the corresponding m mid,i and m mid,j They are:

[0124] On this basis, in one embodiment, m mid,i and m mid,j In this case, the value ranges of m for sub-bands i and j can be configured to be different.

[0125] In other embodiments, m mid,i and m mid,j In this case, the same value range of m can be used, so that the value ranges of sub-band i and sub-band j are not completely the same.

[0126] In some embodiments, if Then m mid,i and m mid,j different.

[0127] Taking q(x)=x as an example, we have

[0128] At this time, if the maximum frequency difference of the sub-band is greater than When different sub-band m mid Different, different X is configured for different sub-bands s Especially important.

[0129] for The q(x) function in the form of q(x)=x+1 / 2 can be derived from the form of q(x). When the maximum frequency difference of the sub-band is greater than a certain threshold value, the m of different sub-bands is mid different.

[0130] In this embodiment, X i and X j can be generated by the same function F, whose independent variables include i and j respectively; in this embodiment, X i and X j It can be generated by the same function F, whose independent variables include the frequency corresponding to sub-band i and the frequency corresponding to sub-band j respectively.

[0131] In another exemplary embodiment, a set of sub-matrices is selected from a preset codebook or subvector And construct the matrix X in a certain form i .

[0132] In some embodiments, the preset codebook may include:

[0133] X i The values ​​of m and n can be changed continuously or selected discontinuously according to certain rules. m and u n The corresponding value ranges of m and n are defined as as well as

[0134] For subband j=i+q, q ​​is an integer, and its corresponding X j The values ​​of m and n are determined according to the sub-band frequency or the sub-band independent variable j.

[0135] In some embodiments of the application, if the difference between j and i is greater than a certain preset threshold, the corresponding u m The value range of m in is defined as t is a non-zero integer. The preset threshold is configured by the base station or calculated through system parameters according to an agreed rule.

[0136] In some application embodiments, the preset threshold includes:

[0137] In this embodiment of the present application, the value of t is determined by the difference between j and i or the difference between the subband frequencies, and a preset threshold. The preset threshold can be an array or set arranged in ascending order, and the value of t is determined based on the difference between different subbands i and j and the preset threshold array.

[0138] In one embodiment of the application, when the difference between j and i or the difference between the sub-band frequencies is greater than the kth value in the preset threshold but less than the k+1th value, t=k.

[0139] In some embodiments of the application, if the difference between j and i is greater than a preset threshold, the corresponding v n The range of n in is defined as r is a non-zero integer. The preset threshold is configured by the base station or calculated through system parameters according to an agreed rule.

[0140] In some application embodiments, the preset threshold includes:

[0141] The value of r is determined by the difference between j and i, or the difference in subband frequency, and a preset threshold. The preset threshold can be a set of values ​​ranging from small to large. The value of r is determined based on the difference between subband i and subband j and the preset threshold array. In one possible scenario, if the difference between j and i, or the difference in subband frequency, is greater than the kth value in the preset threshold but less than the k+1th value, then r = k.

[0142] In some application embodiments, there is an association relationship between sub-band i and sub-band j.

[0143] Based on the above application embodiment, the value ranges of m and n corresponding to sub-band i are associated with the value ranges of m and n corresponding to sub-band j.

[0144] If the value range of m corresponding to subband i is And the corresponding value range of n

[0145] In some application embodiments, the value range of m corresponding to sub-band j is The value range of n corresponding to subband j Both t and r are integers, and t and r cannot be zero at the same time.

[0146] In some other application embodiments, the value range of m corresponding to sub-band j is The value range of n corresponding to subband j is Both t and r are integers and t and r are not 0 at the same time.

[0147] In an exemplary embodiment, the value range of m for subband i is P1 = {1, 2, 3, 4}, and the corresponding value range of n is P2 = {3, 4, 5, 6}. The value range of m for subband j is {2, 3, 4, 5}, and the corresponding value range of n is {3, 4, 5, 6}.

[0148] In the embodiment of the present application, there are at least two sub-bands i and j, and the corresponding matrices X i and matrix X j Satisfy at least one of the following relationships:

[0149] Matrix X i According to the matrix X j Determine, and, the matrix X i and matrix X j Not exactly the same; the matrix X i and matrix X j It is generated by the same function F, where the independent variables of function F are determined or partially determined by i and j respectively; the matrix X i and matrix X j They are constructed and generated by the same function F, where the independent variables of the function F are determined or partially determined by the frequencies corresponding to sub-band i and sub-band j respectively.

[0150] In an exemplary embodiment, the number of ports in the first dimension of the antenna array is N1, the number of ports in the second dimension is N2, the DFT corresponding to the ports in the first dimension is oversampled by a multiple of O1, and the DFT corresponding to the ports in the second dimension is oversampled by a multiple of O2. The first-dimensional discrete Fourier vector u m and the second-dimensional discrete Fourier vector v n The number of rows or columns is determined by the configuration parameters N1 and N2 of the codebook dimension.

[0151] In the embodiment of the present application, it is assumed that N2=1. This is only an example and not a limitation. The method provided in the embodiment of the present application can be applied to the case where N2 is greater than 1.

[0152] Assume that B selects different sub-matrices from the codebook The number is 2.

[0153] Matrix X s have:

[0154] Taking N1=8, O1=2 as an example, the X selected by subband i is i It can be composed of 16-point DFT beam 6 and 16-point DFT beam 7 (written as v6 and v7), as shown in Figure 7, where the black beam represents the non-oversampling beam, the white beam is the oversampling beam, and the beams with other filling methods are the beams corresponding to the selected codeword.

[0155] For another example, suppose B selects different subvectors from the codebook The number is 4.

[0156] For the dual polarization case, we have: X s =[W l,l′,m,m′,n W l,l′,m+1,m′,n W l+1,l′,m,m′,n W l+1,l′,m+1,m′,n ]

[0157] Taking N1=8, O1=2 as an example, the X selected by subband i is i It can be composed of 16-point DFT beam 6 and 16-point DFT beam 7 (written as v6 and v7), as shown in Figure 7, where the black beam represents the non-oversampling beam, the white beam is the oversampling beam, and the beams with other filling methods are the beams corresponding to the selected codeword.

[0158] As the number of antennas increases, the beam becomes narrower. The angle range covered by the number is reduced, and the X applicable to sub-band i i May not apply to subband j.

[0159] In an exemplary embodiment, N1 is increased to N1=16 and O1=2.

[0160] X selected by subband i i A possible choice is to use 32-point DFT beam 11 and 32-point DFT beam 12 (written as v' 11 、v' 12 ) is composed as shown in Figure 8.

[0161] X selected by subband j j A possible choice is to use 32-point DFT beam 12, 32-point DFT beam 13 (written as v' 12 , v'13) composition, as shown in Figure 9.

[0162] Subband j' selected X j’ A possible choice is to use 32-point DFT beam 13, 32-point DFT beam 14 (written as v' 13 、v' 14 ) is composed as shown in Figure 10.

[0163] In the embodiment of the present application, the frequency difference between sub-band j' and sub-band i is greater than the frequency difference between sub-band j and sub-band i. Correspondingly, X j’ With X i The difference between them is greater than X j With X i The difference between.

[0164] In the embodiment of the present application, the function F is determined according to the number of columns of u or v (or according to the configuration parameters N1 and N2 of the codebook dimension).

[0165] In another exemplary embodiment, the number of ports in the first dimension of the antenna array is N1, the number of ports in the second dimension is N2, the DFT corresponding to the ports in the first dimension is oversampled by a multiple of O1, and the DFT corresponding to the ports in the second dimension is oversampled by a multiple of O2. The first-dimensional discrete Fourier vector u m and the second-dimensional discrete Fourier vector v n The number of rows or columns is determined by the configuration parameters O1 and O2 of the codebook dimension.

[0166] In the embodiment of the present application, it is assumed that N2=1. This is only an example and not a limitation. The method provided in the embodiment of the present application can be applied to the case where N2 is greater than 1.

[0167] Assume that B selects different sub-matrices from the codebook The number is 2.

[0168] Matrix X s have:

[0169] Taking N1=8, O1=2 as an example, the X selected by subband i is i It can be composed of 16-point DFT beam 6 and 16-point DFT beam 7 (written as v6 and v7), as shown in Figure 7, where the black beam represents the non-oversampling beam, the white beam is the oversampling beam, and the beams with other filling methods are the beams corresponding to the selected codeword.

[0170] When O1 or O2 increases, the beam becomes narrower. The angle range covered by the number is reduced, and the X applicable to sub-band i i May not apply to subband j.

[0171] Increase O1 to O1=4, N1=8.

[0172] X selected by subband i i A possible choice is to use 32-point DFT beam 11 and 32-point DFT beam 12 (written as v' 11 、v' 12 ) is composed as shown in Figure 8.

[0173] X selected by subband j j A possible choice is to use 32-point DFT beam 12, 32-point DFT beam 13 (written as v' 12 、v' 13 ) is composed as shown in Figure 9.

[0174] Subband j' selected X j’ A possible choice is to use 32-point DFT beam 13, 32-point DFT beam 14 (written as v' 13 、v'14 ) is composed as shown in Figure 10.

[0175] The frequency difference between sub-band j' and sub-band i is greater than the frequency difference between sub-band j and sub-band i. Correspondingly, X j 'With X i The difference between them is greater than X j With X i The difference between.

[0176] In the embodiment of the present application, the function F is determined based on O1 and O2.

[0177] In an exemplary embodiment, the configuration parameter i1 affects X s The value of. Taking layer = 1, codebookMode = 2 as an example, i1 = [i 11 ,i 12 ];i 11 Corresponding to v m,n m, i in 12 Corresponding to v m,n n. i 11 Through certain regular changes, the beam pointing direction of the corresponding DFT vector can be made close to the center position and point to the direction of small angle. At this time, the beam becomes narrower than that at large angles. m The angle range covered by the number is reduced. i May not be applicable to subband j. i 12 with i 11 The analysis is the same.

[0178] In another exemplary embodiment, let the target pointing angle be θ and the center frequency be f c Take the Uniform Linear Array (ULA) as an example for analysis. The path delay between adjacent antennas is:

[0179] Corresponding delay

[0180] Here f c represents the center frequency, λ c Indicates the wavelength corresponding to the center frequency.

[0181] In uplink transmission, assuming that the signal received by the first antenna is s(t), the signal received by the mth antenna is:

[0182] Therefore, the equivalent baseband signal is:

[0183] For broadband systems, the frequencies of different sub-bands vary significantly. Consider the pointing angles at different frequencies. During communication, the relative angle between the base station and the user remains unchanged, but changes in the sub-band frequency will cause changes in the beam pointing direction. The corresponding uplink received signal is:

[0184] Therefore, the spatial-time channel can be modeled as:

[0185] Assuming that the difference between the subband frequency and the center frequency is Δf, the corresponding spatial-frequency channel is:

[0186] Where a represents the steering vector, a(x) = [1exp(j2πx)…exp(j2π(M-1)x)] T .

[0187] For a uniform planar array (UPA), its spatial-frequency channel can be expressed as a Kronecker product. One possible scenario is:

[0188] Where θ and φ represent the elevation angle and azimuth angle of the transmission path, respectively.

[0189] For two different angles θ1 and θ2, if sinθ1>sinθ2, then for the same subband, that is, the same frequency difference Δf, we have:

[0190] For the same frequency difference, the larger the sine value of the corresponding angle, the greater the difference in beam selection. In other words, increasing sinθ values ​​make the beam more sensitive to frequency changes. At large angles, the degree to which different frequency resources point in different directions is more obvious.

[0191] In an exemplary embodiment, the correlation is expressed in the form of αsinθΔf, where α is a constant.

[0192] In the embodiment of the present application, i1 represents v m,n The choice of the subscripts m and n represents the trigonometric function of the pointing angle in two dimensions. The function F is determined in part by the value of i1.

[0193] In an exemplary embodiment, the submatrix in B The corresponding DFT vector u m The value of the parameter m can be determined according to the following formula:

[0194] Among them, g1(x) represents a function related to x or a function with x as the independent variable, and the middle value m of the range of the parameter m is mid And other parameters determine the DFT vector u corresponding to the submatrix in B m , where other parameters may include the B neutron matrix The number of etc.

[0195] In some embodiments of the present invention, the submatrix in B The corresponding DFT vector v n One of the parameters n can be determined by the following formula:

[0196] Among them, g2(x) represents a function related to x or a function with x as the independent variable, and the middle value n of the range of the parameter n is mid And other parameters determine the DFT vector v corresponding to the submatrix in B n , where other parameters may include the number of submatrices in B, etc.

[0197] In the embodiment of the present application, the selected u m and v n Determine the matrix X i , the function corresponding to this process can be recorded as F.

[0198] The function F can be determined by N1 and N2, or by O1 and O2, or according to i1.

[0199] FIG11 is a schematic diagram of the structure of a channel information feedback device provided in an embodiment of the present application. The device can execute the channel information feedback method provided in any embodiment of the present application and has the corresponding functional modules and beneficial effects of the execution method. The device can be implemented by software and / or hardware. As shown in FIG11, the device provided in an embodiment of the present application includes:

[0200] The parameter acquisition module 201 is configured to acquire channel parameters of a measurement channel.

[0201] The codebook determination module 202 is configured to determine a codebook set for channel quantization feedback of the channel.

[0202] The codeword selection unit 203 is configured to select a codeword W for quantization characterization of the subband s channel from the codebook set. s .

[0203] Information feedback module 204, used to determine the code word W s The codeword W s is a matrix with r columns, where r is greater than or equal to 1; the codeword W sBy r column vectors Composition, wherein the r column vectors At least one of them is composed of basis vectors u s Composition, wherein the basis vector u s The following model is satisfied:

[0204] described There is at least one column vector in the matrix X s The extracted columns are determined in the matrix X s Determined according to the frequency domain position of the subband or the subband index s.

[0205] Based on the above application embodiment, there are at least two sub-bands i and j in the device, and the corresponding matrices X i and matrix X j Satisfy at least one of the following relationships:

[0206] The matrix X i According to the matrix X j Determine, and, the matrix X i and the matrix X j Not exactly the same; the matrix X i and the matrix X j The matrix X is generated by the same function F, wherein the independent variables of the function F are determined or partially determined by i and j respectively; i and the matrix X j They are constructed and generated by the same function F, where the independent variables of the function F are respectively determined or partially determined by the frequencies corresponding to the sub-band i and the sub-band j.

[0207] Based on the above application embodiment, the matrix X in the device s The first dimension discrete Fourier vector u m and the second-dimensional discrete Fourier vector v n The Kronecker product of is used to generate submatrices or subvectors.

[0208] Based on the above application embodiment, the function F in the device is based on the matrix X s The first dimension of the discrete Fourier vector u m Configuration parameters N1 and the second-dimensional discrete Fourier vector v n The configuration parameter N2 is determined.

[0209] Based on the above application embodiment, the function F in the device is based on the matrix X S The first dimension of the discrete Fourier vector u m Oversampling multiple O1 and the second dimension discrete Fourier vector vn The oversampling multiple O2 is determined.

[0210] Based on the above application embodiment, the function F in the device is based on the matrix X s The indicator parameter i1 is determined.

[0211] Based on the above application embodiment, the matrix X is formed in the device i The discrete Fourier vector of The determined steering vector, where θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0212] Based on the above application embodiment, the matrix X is formed in the device s The parameter ψ of the discrete Fourier vector is close to Among them, q() represents a function, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0213] Based on the above application embodiment, the matrix X in the device i A set of sub-matrices is selected from a preset codebook and constructed in a preset form.

[0214] Based on the above application embodiment, the preset codebook in the device includes:

[0215] Wherein, T represents transpose, N1 and N2 are configuration parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively, O1 and O2 are oversampling multiples of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively, m and n are indicator parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively.

[0216] Based on the above application embodiment, the parameter ψ corresponding to the middle value of the value range of m in the device is close to Among them, q() represents a function, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0217] Based on the above application embodiment, the middle value of the value range of m in the device is Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f crepresents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0218] Based on the above application embodiment, the matrix X in the device i A set of sub-matrices or sub-vectors is determined based on the obtained value range of m.

[0219] Based on the above application embodiment, the value range of m in the device includes at least one of the following:

[0220] Where mod(P,2)=0, PP is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected in m; m includes at least m mid or m mid +1 at least one; where m mid Indicates the middle value of the range of m.

[0221] Based on the above application embodiment, the device Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0222] Based on the above application embodiment, the parameter ψ corresponding to the middle value of the value range of n in the device is close to Among them, q() represents a function, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0223] Based on the above application embodiment, the middle value of the value range of n in the device is Where q() represents a function, floor(x) represents an integer not greater than x but close to x, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0224] Based on the above application embodiment, the matrix X in the device i A set of sub-matrices or sub-vectors is determined based on the obtained value range of n.

[0225] Based on the above application embodiment, the value range of n in the device includes at least one of the following:

[0226] Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Where mod(T,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected in ; n includes at least n mid or n mid +1 at least one; where n mid Indicates the middle value of the range of n.

[0227] Based on the above application embodiment, the device Where q() represents a function, floor(x) represents an integer not greater than x but close to x, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

[0228] Based on the above application embodiment, the function in the device includes at least one of the following:

[0229] in, represents an integer not greater than x but close to x; q(x)=x; q(x)=x+1 / 2.

[0230] Based on the above application embodiment, the value ranges of m and n in the device are respectively and Where k1 and k2 are the number of vectors in set P1 and set P2 respectively.

[0231] Based on the above-mentioned application embodiment, the frequency difference between the sub-band i and the sub-band j in the device is greater than a preset threshold, and the value range of m includes: t is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to an agreed rule, and k1 is the number of vectors in the set P1.

[0232] Based on the above application embodiment, the frequency difference between the sub-band i and the sub-band j in the device is greater than a preset threshold, and the value range of n includes: r is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to agreed rules, and k2 is the number of vectors in the set P2.

[0233] Based on the above application embodiment, the preset threshold in the device includes at least one of the following:

[0234] or

[0235] Among them, f c represents the center frequency, θ represents the target pointing angle, and φ represents the azimuth angle.

[0236] Figure 12 is a structural diagram of an electronic device provided in an embodiment of the present application, which electronic device includes a processor 10 and a memory 11; the number of processors 10 in the electronic device can be one or more, and Figure 12 takes one processor 10 as an example; the processor 10 and the memory 11 in the electronic device can be connected via a bus or other means, and Figure 12 takes connection via a bus as an example.

[0237] The memory 11, as a computer-readable storage medium, can be used to store software programs, computer executable programs, and modules, such as the modules corresponding to the apparatus in the embodiment of the present application (parameter acquisition module 201, codebook determination module 202, codeword selection module 203, and information feedback module 204). The processor 10 executes various functional applications and data processing of the electronic device by running the software programs, instructions, and modules stored in the memory 11, that is, implementing the above-mentioned channel information feedback method.

[0238] The memory 11 may mainly include a program storage area and a data storage area, wherein the program storage area may store an operating system and at least one application required for a function; the data storage area may store data created based on the use of the electronic device, etc. In addition, the memory 11 may include a high-speed random access memory and may also include a non-volatile memory, such as at least one disk storage device, a flash memory device, or other non-volatile solid-state storage device. In some instances, the memory 11 may include a memory remotely located relative to the processor 10, and these remote memories may be connected to the electronic device via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0239] An embodiment of the present application further provides a storage medium containing computer-executable instructions. When the computer-executable instructions are executed by a computer processor, the computer-executable instructions are used to perform a channel information feedback method. The method includes:

[0240] Acquire channel parameters of the measurement channel; determine a codebook set for channel quantization feedback of the channel; select a codeword W for subband s channel quantization characterization from the codebook set s ; Determine the code word W s The codeword W s is a matrix with r columns, where r is greater than or equal to 1; the codeword W s By r column vectors Composition, wherein the r column vectors At least one of them is composed of basis vectors u s Composition, wherein the basis vector u s The following model is satisfied:

[0241] described There is at least one column vector in the matrix X s The extracted columns are determined in the matrix X s Determined according to the frequency domain position of the subband or the subband index s.

[0242] Through the above description of the implementation methods, those skilled in the art can clearly understand that the present application can be implemented with the help of software and necessary general-purpose hardware. Of course, it can also be implemented by hardware, but in many cases the former is a better implementation method. Based on this understanding, the technical solution of the present application can be embodied in the form of a software product. The computer software product can be stored in a computer-readable storage medium, such as a computer floppy disk, read-only memory (ROM), random access memory (RAM), flash memory (FLASH), hard disk or optical disk, etc., including a number of instructions for enabling a computer device (which can be a personal computer, server, or network device, etc.) to execute the channel information feedback method described in each embodiment of the present application.

[0243] In the embodiment of the above-mentioned device, the various units and modules included are divided only according to functional logic, but are not limited to the above-mentioned division, as long as the corresponding functions can be realized; in addition, the names of the various functional units are only for the convenience of distinguishing each other, and are not used to limit the scope of protection of this application.

[0244] Those skilled in the art will appreciate that all or some of the operations, devices, and functional modules / units in the methods disclosed above may be implemented as software, firmware, hardware, or appropriate combinations thereof.

[0245] In a hardware implementation, the division between the functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or operation may be performed by several physical components in cooperation. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, a digital signal processor, or a microprocessor, or implemented as hardware, or implemented as an integrated circuit, such as an application-specific integrated circuit. The corresponding software may be distributed on a computer-readable medium, which may include a computer storage medium (or non-transitory medium) and a communication medium (or temporary medium). As known to those of ordinary skill in the art, the term computer storage medium includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, digital versatile disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tapes, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, as is well known to those skilled in the art, communication media typically embodies computer-readable instructions, data structures, program modules, or other data in a modulated data signal such as a carrier wave or other transport mechanism, and may include any information delivery media.

Claims

1. A channel information feedback method, applied to a receiving end, comprising: Obtaining channel parameters of the measurement channel; Determining a codebook set for channel quantization feedback of the channel; The codeword W for the quantization representation of the subband s channel is selected from the codebook set s ; Determine the codeword W s and feeding back the indication parameter to the sending end; Wherein, the code word W s is a matrix with r columns, where r is greater than or equal to 1; The code word W s By r column vectors Composition, wherein the r column vectors At least one of them is composed of basis vectors u s Composition, wherein the basis vector u s The following model is satisfied: described There is at least one column vector in the matrix X s The extracted columns are determined in the matrix X s Determined according to the frequency domain position of the subband or the subband index s.

2. The method according to claim 1, further comprising: There are at least two subbands i and j, corresponding to the matrices X i and matrix X j Satisfy at least one of the following relationships: The matrix X i According to the matrix X j Determine, and, the matrix X i and the matrix X j Not exactly the same; The matrix X i and the matrix X j are generated by the same function F, wherein the independent variables of the function F are determined or partially determined by i and j respectively; The matrix X i and the matrix X j They are constructed and generated by the same function F, where the independent variables of the function F are respectively determined or partially determined by the frequencies corresponding to the sub-band i and the sub-band j.

3. The method according to claim 1, wherein: The matrix X s Generates a submatrix or subvector consisting of the Kronecker product of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector.

4. The method according to claim 2, wherein: The function F is based on the matrix X s The configuration parameters N1 of the first-dimensional discrete Fourier vector and the configuration parameters N2 of the second-dimensional discrete Fourier vector are determined.

5. The method according to claim 2, wherein: The function F is based on the matrix X s The oversampling multiple O1 of the first-dimensional discrete Fourier vector and the oversampling multiple O2 of the second-dimensional discrete Fourier vector are determined.

6. The method according to claim 2, wherein: The function F is based on the matrix X s The indicator parameter i1 is determined.

7. The method according to claim 2, wherein: Construct the matrix X i The discrete Fourier vector of The determined steering vector, where θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

8. The method according to claim 1, wherein: Construct the matrix X s The parameter ψ of the discrete Fourier vector is close to Among them, q() represents a function, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

9. The method according to claim 2, wherein the matrix X i A set of sub-matrices is selected from a preset codebook and constructed in a preset form.

10. The method according to claim 9, wherein: The preset codebook includes: Wherein, T represents transpose, N1 and N2 are configuration parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively, O1 and O2 are oversampling multiples of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively, m and n are indicator parameters of the first-dimensional discrete Fourier vector and the second-dimensional discrete Fourier vector, respectively.

11. The method according to claim 10, wherein: The parameter ψ corresponding to the middle value of the range of m is close to Among them, q() represents a function, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

12. The method according to claim 10, wherein: The middle value of the range of m Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

13. The method according to claim 2, wherein: The matrix X i A group of sub-matrices or sub-vectors is determined based on the obtained value range of m.

14. The method according to claim 10 or 13, wherein: The value range of m includes at least one of the following: Wherein, mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Wherein, mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Wherein, mod(P,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; m includes at least m mid or m mid +1 at least one; where m mid Indicates the middle value of the range of m.

15. The method according to claim 14, wherein: Where q() represents a function, floor(x) represents an integer not greater than x but close to x, θ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

16. The method according to claim 10, wherein: The parameter ψ corresponding to the middle value of the range of n is close to Among them, q() represents a function, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

17. The method according to claim 10, wherein: The middle value of the range of n Where q() represents a function, floor(x) represents an integer not greater than x but close to x, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

18. The method according to claim 2, wherein: The matrix X i A group of sub-matrices or sub-vectors is determined based on the obtained value range of n.

19. The method according to claim 10 or 18, wherein: The value range of n includes at least one of the following: Wherein, mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Wherein, mod(P,2)=0, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; Wherein, mod(P,2)=1, P is the matrix X i The number of non-repeated sub-matrices or sub-vectors selected; n includes at least n mid or n mid +1 at least one; where n mid Indicates the middle value of the range of n.

20. The method according to claim 19, wherein: Where q() represents a function, floor(x) represents an integer not greater than x but close to x, φ represents the target pointing angle, and f c represents the center frequency, and Δf represents the frequency difference between the sub-band and the center frequency.

21. The method according to any one of claims 8, 11, 12, 15, 16 or 17, wherein: The function includes at least one of the following: in, represents an integer not greater than x but close to x; q(x)=x; q(x)=x+1 / 2.

22. The method according to claim 10, wherein: The value ranges of m and n are and Where k1 and k2 are the number of vectors in set P1 and set P2 respectively.

23. The method according to claim 10, wherein: The frequency difference between sub-band i and sub-band j is greater than a preset threshold, and the value range of m includes: t is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to an agreed rule, and k1 is the number of vectors in the set P1.

24. The method according to claim 10, wherein: The frequency difference between sub-band i and sub-band j is greater than a preset threshold, and the value range of n includes: r is a non-zero integer, the preset threshold is configured by the base station or determined by system parameters according to agreed rules, and k2 is the number of vectors in the set P2.

25. The method according to claim 23 or 24, wherein: The preset threshold includes at least one of the following: or Among them, f c represents the center frequency, θ represents the target pointing angle, and φ represents the azimuth angle.

26. An electronic device comprising: at least one processor; a memory configured to store at least one program; When the at least one program is executed by the at least one processor, the at least one processor implements the channel information feedback method according to any one of claims 1 to 25.

27. A computer-readable storage medium storing at least one program, wherein the at least one program is executed by at least one processor to implement the channel information feedback method according to any one of claims 1 to 25.

Images