Channel matrix processing method, device, and storage medium

Abstract

Embodiments of the present application provide a channel matrix processing method, device and storage medium, and belong to the field of communication. The method comprises: acquiring a channel matrix and a unitary matrix; performing unitary transformation on the channel matrix according to the unitary matrix to obtain a beam space matrix corresponding to the channel matrix; and performing de-redundancy processing on the channel matrix according to the beam space matrix and the unitary matrix to obtain a target channel matrix. The technical scheme of the present application can generate a target channel matrix with very low redundancy, so that the key generated based on the target channel matrix is more secure, and the security of information transmission is greatly improved.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to a channel matrix processing method, device, and storage medium. Background Technology

[0002] With the development of fifth-generation mobile communication technology, the amount of data exchanged in wireless channels will increase exponentially. Multiple-in multiple-out (MIMO) systems have become a common communication technology. Using MIMO systems allows for the exchange of more confidential information, such as financial data, personal privacy, and military secrets. Therefore, modern communication places higher demands on the security of wireless channels. However, the broadcast nature of wireless channels threatens the reliability of transmission. Third parties can more easily eavesdrop on the data transmitted in the channel and may even launch attacks, leading to information leaks and disruptions to legitimate communications.

[0003] Current traditional encryption technologies rely on computational complexity and assume limited attacker computing power, facing difficulties in key distribution and management. Key extraction technologies based on the physical layer characteristics of wireless channels utilize the inherent properties of wireless channels, such as time-varying nature, uniqueness, and reciprocity, to generate shared keys for communicating parties. However, in the physical layer key generation process of MIMO systems, the slow channel changes, or the increased channel probing frequency to improve key generation rate, lead to high redundancy between adjacent sampled values. Existing technologies use principal component analysis (PCA) or discrete cosine transform (DCT) to reduce redundancy in sampled values, but the redundancy reduction effect is unsatisfactory, resulting in low security of the key generated from sampled values. Therefore, how to reduce the redundancy of sampled values ​​and improve the security of the generated key is an urgent problem to be solved. Summary of the Invention

[0004] The present invention provides a channel matrix processing method, a terminal device, and a storage medium, which aims to reduce the redundancy of CSI sample values ​​so as to make the generated key more secure.

[0005] In a first aspect, the present invention provides a channel matrix processing method, comprising:

[0006] Obtain the channel matrix and the unitary matrix;

[0007] Perform a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix;

[0008] Based on the beam space matrix and the unitary matrix, the channel matrix is ​​deredundant to obtain the target channel matrix.

[0009] Secondly, embodiments of the present invention also provide a terminal device, the terminal device including a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for implementing communication between the processor and the memory, wherein when the computer program is executed by the processor, it implements the steps of any of the channel matrix processing methods provided in this specification.

[0010] Thirdly, embodiments of the present invention also provide a storage medium for computer-readable storage, characterized in that the storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of any of the channel matrix processing methods provided in this specification.

[0011] This invention provides a channel matrix processing method, a terminal device, and a storage medium. By obtaining a channel matrix and a unitary matrix, and then performing a unitary transformation on the channel matrix based on the unitary matrix, a beam space matrix corresponding to the channel matrix can be obtained. Based on the beam space matrix and the unitary matrix, the channel matrix is ​​deredundant, resulting in a very low redundancy of the generated target channel matrix. This makes the key generated based on the target channel matrix more secure, greatly improving the security of information transmission. Attached Figure Description

[0012] Figure 1 This is a flowchart illustrating a channel matrix processing method provided in an embodiment of the present invention;

[0013] Figure 2 A schematic diagram of a scenario for the channel matrix processing method provided in this embodiment of the invention;

[0014] Figure 3 for Figure 1 A flowchart illustrating the sub-steps of the channel matrix processing method in [the document / technology].

[0015] Figure 4 A flowchart illustrating another channel matrix processing method provided in an embodiment of the present invention;

[0016] Figure 5 This is a schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention. Detailed Implementation

[0017] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some, not all, of the embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.

[0018] The flowchart shown in the attached diagram is for illustrative purposes only and does not necessarily include all content and operations / steps, nor does it necessarily have to be performed in the order described. For example, some operations / steps can be broken down, combined, or partially merged, so the actual execution order may change depending on the actual situation.

[0019] It should be understood that the terminology used in this specification is for the purpose of describing particular embodiments only and is not intended to limit the invention. As used in this specification and the appended claims, the singular forms “a,” “an,” and “the” are intended to include the plural forms unless the context clearly indicates otherwise.

[0020] This invention provides a channel matrix processing method, a terminal device, and a storage medium. The channel matrix processing method can be applied to a terminal device, such as a mobile phone, tablet computer, laptop computer, desktop computer, or personal digital assistant. The method can also be applied to a communication system. For example, the communication system acquires a channel matrix and a unitary matrix; then performs a unitary transformation on the channel matrix based on the unitary matrix to obtain the beamspace matrix corresponding to the channel matrix; subsequently, based on the beamspace matrix and the unitary matrix, it performs redundancy removal processing on the channel matrix to obtain the target channel matrix.

[0021] The following detailed description of some embodiments of the present invention is provided in conjunction with the accompanying drawings. Unless otherwise specified, the following embodiments and features can be combined with each other.

[0022] Please refer to Figure 1 , Figure 1 This is a flowchart illustrating a channel matrix processing method provided in an embodiment of the present invention.

[0023] like Figure 1 As shown, the channel matrix processing method may include steps S101 to S103.

[0024] Step S101: Obtain the channel matrix and unitary matrix.

[0025] When the first terminal device and the second terminal device send pilot signals to each other, the first terminal device collects Channel State Information (CSI) sample values, obtaining multiple CSI sample values, and generates a channel matrix based on these multiple CSI sample values. The first and second terminal devices can be configured according to actual conditions, and this application embodiment does not impose specific limitations on this. For example, the first terminal device may be a mobile phone, and the second terminal device may be a computer. The first terminal device includes a first antenna array, and the second terminal device includes a second antenna array. The first and second antenna arrays can be configured according to actual conditions, and this application embodiment does not impose specific limitations on this.

[0026] In one embodiment, each sub-channel matrix is ​​determined based on each CSI sample value, and all sub-channel matrices are superimposed to obtain the channel matrix. Specifically, when there is only one CSI sample value, there is only one sub-channel matrix, which is the channel matrix. When there are multiple CSI sample values, there are a corresponding number of sub-channel matrices. These multiple sub-channel matrices are superimposed to obtain the channel matrix. By calculating the sub-channel matrix corresponding to each CSI sample value and then superimposing multiple sub-channel matrices, the channel matrix can be accurately obtained.

[0027] In one embodiment, the CSI sampled values ​​include the angle of arrival (AOA) of the ray corresponding to each antenna in the receiver antenna array and the total number of antennas, the angle of arrival (AOA) of the ray corresponding to each antenna in the transmitter antenna array and the total number of antennas, and the power value of each ray in the scattering cluster. The sub-channel matrix can be determined based on the CSI sampled values ​​by: obtaining sub-channel matrix coefficients, wherein the sub-channel matrix coefficients are determined by the total number of transmitter antennas, the total number of receiver antennas, the total number of scattering clusters, and the number of propagation paths in each scattering cluster; and determining the sub-channel matrix based on the sub-channel matrix coefficients, according to the departure angle, the angle of arrival, and the power value of each ray in the scattering cluster.

[0028] It should be noted that the channel matrix in this embodiment can be established based on a clustered channel model or other models. This embodiment does not specifically limit this, such as the Saleh-Valenzuela channel model, the 3GPP TR 38.900 channel model, the METIS channel model, and the MIWEBA model, etc.

[0029] For example, such as Figure 2As shown, the first terminal device 10 transmits information to the second terminal device 20. The first terminal device 10 transmits the signal to the cluster 30, and then the cluster 30 transmits the information to the second terminal device 20. The angle 40 between the transmission ray from the first terminal device 10 to the cluster 30 and the horizontal is the departure angle, and the angle 50 between the transmission ray from the cluster 30 to the second terminal device 20 and the horizontal is the arrival angle.

[0030] In one embodiment, the sub-channel matrix coefficients are obtained by multiplying the total number of transmitting antennas and the total number of receiving antennas to obtain the first sub-channel matrix coefficients, multiplying the total number of scattering clusters and the number of propagation paths in the scattering clusters to obtain the second sub-channel matrix coefficients, and then taking the square root of the first sub-channel matrix coefficients divided by the second sub-channel matrix coefficients to obtain the sub-channel matrix coefficients.

[0031] In one embodiment, the subchannel matrix is ​​determined based on the subchannel matrix coefficients, according to the departure angle, arrival angle, and the power value of each ray in the scattering cluster. This can be achieved by: determining the transmitter array response vector based on the departure angle of the transmitter and the total number of antennas; determining the receiver array response vector based on the arrival angle of the receiver and the total number of antennas; and generating the subchannel matrix based on the subchannel matrix coefficients, the transmitter array response vector, the receiver array response vector, and the power value of each ray in the scattering cluster. By calculating the subchannel matrix coefficients, the transmitter array response vector, the receiver array response vector, and the power value of each ray in the scattering cluster, the subchannel matrix can be accurately determined.

[0032] For example, the method to determine the transmitter array response vector based on the transmitter's departure angle and the total number of antennas can be: obtaining the array response vector formula, which is... Where a is the array vector. Let N be the departure angle of the transmitting end, N be the total number of antennas in the transmitting end's antenna array, k be a constant, and d be the antenna spacing in the antenna array. λ represents the millimeter-wave wavelength. Based on this array response vector formula, and taking into account the total number of antennas in the transmitting antenna array, the millimeter-wave wavelength, and the departure angle of the transmitting end, the transmitting array response vector is determined. Using this array response vector formula and the total number of antennas in the transmitting antenna array, the millimeter-wave wavelength, and the departure angle of the transmitting end, the transmitting array response vector can be accurately determined.

[0033] For example, the method to determine the receiver array response vector based on the receiver's angle of arrival and the total number of antennas can be: obtaining the array response vector formula, which is... Where a is the array vector, θ is the angle of arrival at the receiver, N is the total number of antennas in the receiver's antenna array, k is a constant, and d is the antenna spacing in the antenna array. λ represents the millimeter-wave wavelength. Based on this array response vector formula, and taking into account the total number of antennas in the receiver antenna array, the millimeter-wave wavelength, and the angle of arrival at the receiver, the receiver array response vector is determined. Using this array response vector formula and the total number of antennas in the receiver antenna array, the millimeter-wave wavelength, and the angle of arrival at the receiver, the receiver array response vector can be accurately determined.

[0034] For example, the subchannel matrix can be generated based on the subchannel matrix coefficients, the transmitter array response vector, the receiver array response vector, and the power value of each ray in the scattering cluster by obtaining the subchannel matrix formula, which is: in, For the sub-channel matrix coefficients, N is the number of sub-channel matrix coefficients. t N represents the total number of antennas in the transmitting antenna array. r N represents the total number of antennas in the receiver antenna array. cl N represents the total number of scattering clusters. ray The number of propagation paths in the scattering cluster. Let a be the power value of the rays in the scattering cluster. r (θ il ) represents the receiver array response vector. The subchannel matrix is ​​the conjugate transpose of the transmitter array response vector. Based on this subchannel matrix formula, and according to the subchannel matrix coefficients, the total number of antennas in the transmitter antenna array, the total number of scattering clusters, the number of propagation paths in the scattering clusters, the power values ​​of the rays in the scattering clusters, and the response vectors of the receiver and transmitter arrays, the subchannel matrix is ​​generated. This subchannel matrix formula allows for accurate generation of the subchannel matrix.

[0035] For example, the sub-channel matrix includes sub-channel matrix H1, sub-channel matrix H2, sub-channel matrix H3, sub-channel matrix H4, sub-channel matrix H5, sub-channel matrix H6, sub-channel matrix H7, sub-channel matrix H8, sub-channel matrix H9 and sub-channel matrix H 10 For sub-channel matrices H1, H2, H3, H4, H5, H6, H7, H8, H9 and H... 10 By superimposing the matrices, the channel matrix is ​​obtained as follows: The channel matrix dimension is N r N represents the total number of antennas at the receiving end. t This represents the total number of antennas at the transmitting end.

[0036] In one embodiment, the unitary matrix includes a first unitary matrix and a second unitary matrix. The first unitary matrix is ​​determined based on the departure angle of the ray corresponding to each antenna in the transmitting antenna array and the total number of antennas. The second unitary matrix is ​​determined based on the arrival angle of the ray corresponding to each antenna in the receiving antenna array and the total number of antennas.

[0037] For example, the first unitary matrix can be determined as follows: Obtain the transmitting antenna array and perform a two-dimensional discrete Fourier transform on the transmitting antenna array to obtain the first unitary matrix. Specifically, obtain the antenna spacing, the total number of antennas, and the departure angle of the ray corresponding to each antenna in the transmitting antenna array, and obtain the formula for the unitary matrix. The formula for the unitary matrix is: Where U is a unitary matrix and N is the total number of antennas. For array vectors, Let λ be the millimeter-wave wavelength and d be the antenna spacing. Based on this unitary matrix formula, and according to the antenna spacing, total number of antennas, departure angle of the ray corresponding to each antenna, and millimeter-wave wavelength in the transmitting antenna array, the first unitary matrix is ​​generated. The first unitary matrix can be accurately determined using this unitary matrix calculation formula.

[0038] For example, the second unitary matrix can be determined as follows: Obtain the receiving antenna array and perform a two-dimensional discrete Fourier transform on the array to obtain the second unitary matrix. Specifically, obtain the antenna spacing, the total number of antennas, and the angle of arrival of the ray corresponding to each antenna in the receiving antenna array, and obtain the formula for the unitary matrix. The formula for the unitary matrix is: ·, aθN-1T, where U is the unitary matrix, N is the total number of antennas, aθ0 is the array vector, θi=sin⁻¹λiNd, λ is the millimeter-wave wavelength, and d is the antenna spacing. Based on this unitary matrix formula, and according to the antenna spacing, total number of antennas, angle of arrival of the ray corresponding to each antenna, and millimeter-wave wavelength in the receiver antenna array, a second unitary matrix is ​​generated. The second unitary matrix can be accurately determined using this unitary matrix calculation formula.

[0039] Step S102: Perform a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix.

[0040] The unitary matrix includes a first unitary matrix and a second unitary matrix. The first unitary matrix is ​​determined based on the departure angle of the ray corresponding to each antenna in the transmitting antenna array and the total number of antennas. The second unitary matrix is ​​determined based on the arrival angle of the ray corresponding to each antenna in the receiving antenna array and the total number of antennas.

[0041] In one embodiment, the conjugate transpose of the second unitary matrix is ​​determined; the conjugate transpose, the channel matrix, and the first unitary matrix are multiplied to obtain the beamspace matrix corresponding to the channel matrix. By multiplying the conjugate transpose, the channel matrix, and the first unitary matrix, the beamspace matrix corresponding to the channel matrix can be accurately obtained, improving the efficiency and accuracy of subsequent redundancy removal processing of the channel matrix.

[0042] For example, the formula for obtaining the beam space matrix is: Among them, H b For the beam space matrix, Let H be the conjugate transpose of the second unitary matrix, and let H be the channel matrix. t Given the first unitary matrix, based on this beamspace matrix formula, the conjugate transpose of the second unitary matrix, the channel matrix, and the first unitary matrix are substituted into the beamspace matrix formula to calculate the beamspace matrix corresponding to the channel matrix. This beamspace matrix formula allows for accurate calculation of the beamspace matrix.

[0043] Step S103: Based on the beam space matrix and the unitary matrix, perform redundancy removal processing on the channel matrix to obtain the target channel matrix.

[0044] The channel matrix generated from CSI sample values ​​has high redundancy, which makes the security of the key generated from the channel matrix low. Therefore, it is necessary to remove redundancy from the channel matrix.

[0045] In one embodiment, such as Figure 3 As shown, step S103 includes sub-steps S1031 to S1032.

[0046] Sub-step S1031: Determine the transformation matrix corresponding to the channel matrix based on the beam space matrix and the unitary matrix.

[0047] For example, the sum of squares of each row or column element of the beamspace matrix is ​​determined; at least one index value is determined based on the sum of squares of each row or column element of the beamspace matrix; the column corresponding to the index value is selected from the unitary matrix as the target column, and a transformation matrix corresponding to the channel matrix is ​​constructed based on each target column. The selected index value can be set according to actual conditions, and this embodiment does not specifically limit this; for example, one index value or multiple index values ​​can be selected. By selecting the target column from the unitary matrix, the transformation matrix of the channel matrix can be constructed based on the target column.

[0048] In one embodiment, determining at least one index value based on the sum of squares of each row element or each column element of the beam space matrix can be done by: sorting the row numbers or column numbers of the beam space matrix according to the sum of squares of each row element or each column element of the beam space matrix to obtain a row number sorting queue or a column number sorting queue; selecting at least one matrix row number from the row number sorting queue as an index value, or selecting at least one matrix column number from the column number sorting queue as an index value.

[0049] In one embodiment, the unitary matrix includes a first unitary matrix. When a target column is selected from the first unitary matrix, and a transformation matrix corresponding to the channel matrix is ​​constructed based on each target column, the method can be as follows: determine the sum of squares of the elements in each column of the beam space matrix; sort the column numbers of each matrix in the beam space matrix according to the sum of squares of the elements in each column to obtain a column number sorting queue; select at least one matrix column number from the column number sorting queue as an index value; select the column corresponding to the index value from the first unitary matrix as a target column; and perform matrix combination on at least one target column to obtain the transformation matrix corresponding to the channel matrix.

[0050] It should be noted that the sorting method for the column numbers of the beam space matrix based on the sum of squares of each column element can be set according to the actual situation. For example, the column numbers can be sorted in descending order based on the sum of squares of each column element, or in ascending order based on the sum of squares of each column element, to obtain the column number sorting queue.

[0051] For example, the way to select at least one matrix column number as an index value from the column number sorting queue is as follows: if the column number sorting queue is obtained from largest to smallest as {4, 2, 1, 5, 3}, if one index value is selected, then column number 4 is used as the index value; if two index values ​​are selected, then column number 4 and column number 2 are used as the index values.

[0052] In one embodiment, the unitary matrix includes a second unitary matrix. When a target column is selected from the second unitary matrix, and a transformation matrix corresponding to the channel matrix is ​​constructed based on each target column, the method can be as follows: determine the sum of squares of each row element of the beam space matrix; sort the row numbers of the beam space matrix according to the sum of squares of each row element to obtain a row number sorting queue; select at least one matrix row number from the row number sorting queue as an index value; select the column corresponding to the index value from the second unitary matrix as a target column; and perform matrix combination on at least one target column to obtain the transformation matrix corresponding to the channel matrix.

[0053] It should be noted that the method of sorting the row numbers of the beam space matrix according to the sum of squares of the elements in each row can be set according to the actual situation. For example, the row numbers can be sorted in descending order according to the sum of squares of the elements in each row, or they can be sorted in ascending order according to the sum of squares of the elements in each row.

[0054] For example, the way to select at least one matrix row number as an index value from the column number sorting queue is as follows: the row number sorting queue from largest to smallest is {3, 5, 1, 2, 4}. If one index value is selected, then row number 3 is used as the index value. If two index values ​​are selected, then row number 3 and row number 5 are used as the index values.

[0055] Sub-step S1032: Perform redundancy removal processing on the channel matrix according to the transformation matrix to obtain the target channel matrix.

[0056] The target channel matrix formula is obtained. Based on this formula, and using the transformation matrix and channel matrix, the target channel matrix is ​​derived. This formula includes a first target channel matrix formula and a second target channel matrix formula. By substituting the transformation matrix and channel matrix into this formula, redundancy can be effectively removed from the channel matrix, resulting in the target channel matrix.

[0057] In one embodiment, when the target channel matrix formula is a first target channel matrix formula, the first target channel matrix formula is H. c =HV, where H c Let H be the target channel matrix, H be the channel matrix, and V be the transformation matrix. Based on this first target channel matrix, the channel matrix and the transformation matrix determined according to the first unitary matrix are substituted into the formula for the first target channel matrix to perform calculations, thus obtaining the target channel matrix. Through this first channel matrix formula and the transformation matrix, redundant parameters in the channel matrix can be effectively removed, resulting in the target channel matrix.

[0058] In one embodiment, when the target channel matrix formula is a second target channel matrix formula, the second target channel matrix formula is H. c =V H H, where H c Let H be the target channel matrix, and V be the channel matrix. H Let be the conjugate transpose transformation matrix. Based on this second target channel matrix, substitute the channel matrix and the conjugate transpose transformation matrix determined according to the second unitary matrix into the formula for the second target channel matrix to obtain the target channel matrix. Through this second channel matrix formula and the conjugate transpose transformation matrix, redundant parameters in the channel matrix can be effectively removed, thus obtaining the target channel matrix.

[0059] The channel matrix processing method provided in the above embodiments obtains the channel matrix and the unitary matrix, and then performs a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix. Based on the beam space matrix and the unitary matrix, the channel matrix is ​​deredundant, resulting in a very low redundancy of the generated target channel matrix. This makes the key generated based on the target channel matrix more secure and greatly improves the security of information transmission.

[0060] Please refer to Figure 4 , Figure 4 This is a flowchart illustrating another channel matrix processing method provided in an embodiment of the present invention.

[0061] like Figure 4 As shown, the channel matrix processing method may include steps S201 to S204.

[0062] Step S201: Obtain the channel matrix and unitary matrix.

[0063] When the first terminal device and the second terminal device send pilot signals to each other, they collect Channel State Information (CSI) sample values ​​to obtain multiple CSI sample values. Based on these multiple CSI sample values, a channel matrix is ​​generated. The first and second terminal devices can be configured according to actual conditions; this embodiment does not impose specific limitations on this. For example, the first terminal device can be a mobile phone, and the second terminal device can be a computer. It should be noted that the CSI sample values ​​can be collected as a single value or multiple values.

[0064] In one embodiment, each sub-channel matrix is ​​determined based on each CSI sample value, and all sub-channel matrices are superimposed to obtain the channel matrix. Specifically, when there is only one CSI sample value, there is only one sub-channel matrix, which is the channel matrix. When there are multiple CSI sample values, there are a corresponding number of sub-channel matrices. These multiple sub-channel matrices are superimposed to obtain the channel matrix. By calculating the sub-channel matrix corresponding to each CSI sample value and then superimposing multiple sub-channel matrices, the channel matrix can be accurately obtained.

[0065] In one embodiment, the unitary matrix includes a first unitary matrix and a second unitary matrix. The first unitary matrix is ​​determined based on the departure angle of the ray corresponding to each antenna in the transmitting antenna array and the total number of antennas. The second unitary matrix is ​​determined based on the arrival angle of the ray corresponding to each antenna in the receiving antenna array and the total number of antennas.

[0066] Step S202: Perform a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix.

[0067] In one embodiment, the conjugate transpose of the second unitary matrix is ​​determined; multiplication is performed on the conjugate transpose, the channel matrix, and the first unitary matrix to obtain the beamspace matrix corresponding to the channel matrix. By performing multiplication on the conjugate transpose, the channel matrix, and the first unitary matrix, the beamspace matrix corresponding to the channel matrix can be accurately obtained, improving the efficiency and accuracy of subsequent redundancy removal processing of the channel matrix.

[0068] Step S203: Based on the beam space matrix and the unitary matrix, perform redundancy removal processing on the channel matrix to obtain the target channel matrix.

[0069] Determine the sum of squares of each row or column element of the beam space matrix; determine at least one index value based on the sum of squares of each row or column element of the beam space matrix; select the column corresponding to the index value from the unitary matrix as the target column, and construct the transformation matrix corresponding to the channel matrix based on each target column. Perform redundancy removal processing on the channel matrix based on the transformation matrix to obtain the target channel matrix.

[0070] In one embodiment, determining at least one index value based on the sum of squares of each row element or each column element of the beam space matrix can be done by: sorting the row numbers or column numbers of the beam space matrix according to the sum of squares of each row element or each column element of the beam space matrix to obtain a row number sorting queue or a column number sorting queue; selecting at least one matrix row number from the row number sorting queue as an index value, or selecting at least one matrix column number from the column number sorting queue as an index value.

[0071] Step S204: Divide the target channel matrix into multiple target sub-channel matrices, and generate a key sequence based on the multiple target sub-channel matrices.

[0072] The target channel matrix is ​​divided into multiple target sub-channel matrices. Based on a preset key generation method, a key sequence is generated according to these multiple target sub-channel matrices. The preset key generation method can be set according to actual conditions, and this embodiment does not impose specific limitations on it. For example, the preset key generation method can be a multi-bit adaptive method. By dividing the target channel matrix into multiple target sub-channel matrices and then using the preset key generation method, the key sequence can be accurately obtained.

[0073] In one embodiment, the superposition order of the sub-channel matrices into a channel matrix is ​​obtained. The matrix splitting order is then obtained by reversing this superposition order. The target channel matrix is ​​split according to this matrix splitting order to obtain multiple target sub-channel matrices. A multi-bit adaptive method is used to map the analog measurement values ​​in each target sub-channel matrix into bit values, thereby generating a key sequence. The multi-bit adaptive method enables the mapping of analog measurement values ​​in the target sub-channel matrices into bit values, resulting in a key sequence.

[0074] The channel matrix processing method provided in the above embodiments obtains the channel matrix and the unitary matrix, and then performs a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix. Based on the beam space matrix and the unitary matrix, the channel matrix is ​​deredundant, resulting in a very low redundancy of the generated target channel matrix. The target channel matrix is ​​split into multiple target sub-channel matrices, and based on the multiple target sub-channel matrices, a more secure key sequence can be generated, which greatly improves the security of information transmission.

[0075] Please see Figure 5 , Figure 5 This is a schematic block diagram of the structure of a terminal device provided in an embodiment of the present invention.

[0076] like Figure 5 As shown, the terminal device 300 includes a processor 301 and a memory 302, which are connected by a bus 303, such as an I2C (Inter-integrated Circuit) bus.

[0077] Specifically, processor 301 provides computing and control capabilities to support the operation of the entire terminal device. Processor 301 can be a Central Processing Unit (CPU), but it can also be other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), field-programmable gate arrays (FPGAs), or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. The general-purpose processor can be a microprocessor or any conventional processor.

[0078] Specifically, the memory 302 can be a Flash chip, a read-only memory (ROM) disk, an optical disk, a USB flash drive, or a portable hard drive, etc.

[0079] Those skilled in the art will understand that Figure 5 The structure shown is merely a block diagram of a portion of the structure related to the present invention and does not constitute a limitation on the terminal device to which the present invention is applied. A specific terminal device may include more or fewer components than those shown in the figure, or combine certain components, or have different component arrangements.

[0080] The processor is used to run a computer program stored in a memory, and to implement any of the channel matrix processing methods provided in the embodiments of the present invention when executing the computer program.

[0081] In one embodiment, the processor is configured to run a computer program stored in memory, and when executing the computer program, perform the following steps:

[0082] Obtain the channel matrix and the unitary matrix;

[0083] Perform a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix;

[0084] Based on the beam space matrix and the unitary matrix, the channel matrix is ​​deredundant to obtain the target channel matrix.

[0085] In one embodiment, when the processor performs redundancy removal processing on the channel matrix based on the beam space matrix and the unitary matrix to obtain the target channel matrix, it is configured to:

[0086] Based on the beam space matrix and the unitary matrix, determine the transformation matrix corresponding to the channel matrix;

[0087] The target channel matrix is ​​obtained by performing redundancy removal on the channel matrix based on the transformation matrix.

[0088] In one embodiment, when the processor determines the transformation matrix corresponding to the channel matrix based on the beam space matrix and the unitary matrix, it is configured to:

[0089] Determine the sum of squares of each row or column element of the beam space matrix;

[0090] Determine at least one index value based on the sum of squares of the elements in each row or column of the beam space matrix;

[0091] Select the column corresponding to the index value from the unitary matrix as the target column, and construct the transformation matrix corresponding to the channel matrix according to each target column.

[0092] In one embodiment, the processor, when implementing the determination of at least one index value based on the sum of squares of each row or column element of the beam space matrix, is configured to:

[0093] Based on the sum of squares of the elements in each row or column of the beam space matrix, the row numbers or column numbers of the beam space matrix are sorted to obtain a row number sorting queue or a column number sorting queue.

[0094] Select at least one matrix row number as an index value from the row number sorting queue, or select at least one matrix column number as an index value from the column number sorting queue.

[0095] In one embodiment, the processor, when implementing the acquisition of the channel matrix, is configured to:

[0096] Multiple Channel State Information (CSI) sample values ​​are acquired, and a channel matrix is ​​generated based on the multiple CSI sample values.

[0097] In one embodiment, the processor is configured to implement:

[0098] The unitary matrix includes a first unitary matrix and a second unitary matrix. The first unitary matrix is ​​determined based on the departure angle of the ray corresponding to each antenna in the transmitting antenna array and the total number of antennas. The second unitary matrix is ​​determined based on the arrival angle of the ray corresponding to each antenna in the receiving antenna array and the total number of antennas.

[0099] In one embodiment, when the processor performs a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix, it is configured to:

[0100] Determine the conjugate transpose of the first unitary matrix;

[0101] Multiply the conjugate transpose matrix, the channel matrix, and the second unitary matrix to obtain the beam space matrix corresponding to the channel matrix.

[0102] In one embodiment, the processor is further configured to implement:

[0103] The target channel matrix is ​​split into multiple target sub-channel matrices, and a key sequence is generated based on the multiple target sub-channel matrices.

[0104] It should be noted that those skilled in the art will understand that, for the sake of convenience and brevity, the specific working process of the terminal device described above can be referred to the corresponding process in the aforementioned channel matrix processing method embodiments, and will not be repeated here.

[0105] This invention also provides a storage medium for computer-readable storage, the storage medium storing one or more programs that can be executed by one or more processors to implement the steps of any of the channel matrix processing methods provided in this specification.

[0106] The storage medium can be an internal storage unit of the terminal device described in the foregoing embodiments, such as the hard drive or memory of the terminal device. Alternatively, the storage medium can be an external storage device of the terminal device, such as a plug-in hard drive, Smart Media Card (SMC), Secure Digital (SD) card, or Flash Card equipped on the terminal device.

[0107] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between 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 step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media 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 include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, 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, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0108] It should be understood that the term "and / or" as used in this specification and the appended claims refers to any combination and all possible combinations of one or more of the associated listed items, and includes such combinations. It should be noted that, herein, the terms "comprising," "including," or any other variations thereof are intended to cover a non-exclusive inclusion, such that a process, method, article, or system 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 system. Without further limitation, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or system that includes that element.

[0109] The sequence numbers of the above embodiments of the present invention are merely for descriptive purposes and do not represent the superiority or inferiority of the embodiments. The above descriptions are only specific implementations of the present invention, but the scope of protection of the present invention is not limited thereto. Any person skilled in the art can easily conceive of various equivalent modifications or substitutions within the technical scope disclosed in the present invention, and these modifications or substitutions should all be covered within the scope of protection of the present invention. Therefore, the scope of protection of the present invention should be determined by the scope of the claims.

Claims

1. A channel matrix processing method, characterized in that, include: Obtain the channel matrix and the unitary matrix; Perform a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix; Determine the sum of squares of each row or column element of the beam space matrix; Determine at least one index value based on the sum of squares of the elements in each row or column of the beam space matrix; Select the column corresponding to the index value from the unitary matrix as the target column, and construct the transformation matrix corresponding to the channel matrix according to each target column; The channel matrix is ​​deredundanted based on the transformation matrix to obtain the target channel matrix.

2. The channel matrix processing method according to claim 1, characterized in that, Determining at least one index value based on the sum of squares of each row or column element of the beam space matrix includes: Based on the sum of squares of the elements in each row or column of the beam space matrix, the row numbers or column numbers of the beam space matrix are sorted to obtain a row number sorting queue or a column number sorting queue. Select at least one matrix row number as an index value from the row number sorting queue, or select at least one matrix column number as an index value from the column number sorting queue.

3. The channel matrix processing method according to claim 1, characterized in that, The acquisition of the channel matrix includes: Multiple Channel State Information (CSI) sample values ​​are acquired, and a channel matrix is ​​generated based on the multiple CSI sample values.

4. The channel matrix processing method according to any one of claims 1-3, characterized in that, The unitary matrix includes a first unitary matrix and a second unitary matrix. The first unitary matrix is ​​determined based on the departure angle of the ray corresponding to each antenna in the transmitting antenna array and the total number of antennas. The second unitary matrix is ​​determined based on the arrival angle of the ray corresponding to each antenna in the receiving antenna array and the total number of antennas.

5. The channel matrix processing method according to claim 4, characterized in that, The step of performing a unitary transformation on the channel matrix based on the unitary matrix to obtain the beam space matrix corresponding to the channel matrix includes: Determine the conjugate transpose of the first unitary matrix; Multiply the conjugate transpose matrix, the channel matrix, and the second unitary matrix to obtain the beam space matrix corresponding to the channel matrix.

6. The channel matrix processing method according to any one of claims 1-3, characterized in that, The method further includes: The target channel matrix is ​​split into multiple target sub-channel matrices, and a key sequence is generated based on the multiple target sub-channel matrices.

7. A terminal device, characterized in that, The terminal device includes a processor, a memory, a computer program stored in the memory and executable by the processor, and a data bus for implementing communication between the processor and the memory, wherein when the computer program is executed by the processor, it implements the steps of the channel matrix processing method as described in any one of claims 1 to 6.

8. A storage medium for computer-readable storage, characterized in that, The storage medium stores one or more programs, which can be executed by one or more processors to implement the steps of the channel matrix processing method according to any one of claims 1 to 6.

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