A quadrature time-frequency-space cross-domain multiple access method

Abstract

This invention discloses an orthogonal time-frequency-space cross-domain multiple access method applied to a RIS-assisted MIMO-OTFS system. The base station superimposes the information to be transmitted to each user in the power domain, performs OTFS modulation, and generates a transmit signal. The transmit signal is reflected by the RIS to reach the receiver, constructing the user's time-domain received signal. Each group of users demodulates the time-domain received signal using OTFS to obtain the information sent to them by the base station. Based on this, optimization is performed on three important factors affecting system performance: the beamforming vector of the base station antenna, the power allocated by the base station to each user's information, and the RIS phase shift matrix. The original non-convex optimization problem is transformed into a convex optimization problem for solution. While ensuring rapid convergence of the algorithm, the system rate of the RIS-assisted OTFS cross-domain multiple access system is maximized, achieving a higher system rate and more user access compared to traditional orthogonal multiple access systems.

Description

Technical Field

[0001] This invention relates to the field of wireless multiple access technology, and more specifically to an orthogonal time-frequency-space cross-domain multiple access method. Background Technology

[0002] In recent years, with the development of technology, communication scenarios have become increasingly diversified, and communication needs have become increasingly differentiated. Many high-speed mobile scenarios have emerged, such as vehicle communication, high-speed rail communication, unmanned aerial vehicle (UAV) communication, and low-Earth orbit (LEO) satellite communication. In these high-speed mobile communication scenarios, due to the large relative movement speeds of the transmitting and receiving ends, severe Doppler frequency offset leads to serious inter-carrier interference in traditional Orthogonal Frequency Division Multiplexing (OFDM), significantly reducing system performance. Unlike OFDM, Orthogonal Time-Frequency Space (OTFS) is a two-dimensional modulation technique that modulates information in Delay-Doppler (DD). It can convert a bidispersive channel into a two-dimensional quasi-time-invariant channel and achieve two-dimensional interleaving, thereby obtaining full time-frequency gain. Due to the modulation characteristics of OTFS, it can provide more reliable communication services in high-speed mobile scenarios.

[0003] Intelligent Reflectors (RIS) can significantly improve the performance of OTFS systems when the direct path is blocked by constructing reflection paths and adjusting the reflection coefficients of the reflecting elements. The selection of the reflection coefficients of the reflecting elements is crucial to improving the performance of RIS-assisted OTFS systems. Furthermore, the number of mobile users accessing the system will continue to increase in the future. With limited time and frequency resources, traditional Orthogonal Multiple Access (OMA) technology is insufficient to serve a large number of users; Non-Orthogonal Multiple Access (NOMA) technology, compared to OMA, can accommodate more users and improve system speed. Current research has considered using NOMA for user access in RIS-OTFS systems, but its transmitter focuses on a single antenna and only optimizes the RIS phase shift coefficient, without considering the joint optimization of beamforming, RIS phase shift coefficient, and power allocation in a multi-antenna RIS-OTFS system. Therefore, this system loses degrees of freedom and cannot achieve higher system speeds. Summary of the Invention

[0004] The purpose of this invention is to provide an orthogonal time-frequency-space cross-domain multiple access method to maximize the system rate.

[0005] To achieve the above objectives, the present invention employs the following technical solution:

[0006] An orthogonal time-frequency-space cross-domain multiple access method is proposed and applied to a RIS-assisted MIMO-OTFS system. The system includes a base station, a smart reflector, and K user groups. Each user group contains two users who access the system via multiple access in a non-orthogonal manner. The base station has N transmit antennas. t N t ≥K, each user is equipped with only one antenna; the number of reflective antenna elements in the RIS is N. r ;

[0007] Step 1: The base station superimposes the information to be transmitted to each user in the power domain, performs OTFS modulation, and generates a transmit signal, which is then transmitted by N. t Root antenna transmits;

[0008] Step 2: The base station's transmitted signal reaches the receiver after being reflected by RIS; the user's time-domain received signal is constructed.

[0009] Step 3: Each group of users performs OTFS demodulation on the time-domain received signal, where the demodulated signal of the c-th user in the k-th group is... It can be represented as:

[0010]

[0011] Where F N I represents the conjugate transpose of an N-dimensional Fourier transform matrix; M Let r represent an M-dimensional identity matrix. k,c This represents the time-domain received signal of the c-th user in the k-th group;

[0012] Then the second user in the kth group directly decodes its own demodulated signal. That is, the second user in the kth group passes Directly perform constellation demapping to obtain the information transmitted to itself by the base station.

[0013] The first user in group k first demodulates the signal. Perform constellation demapping to obtain the information transmitted by the base station to the second user in the k-th group, then from... The information of the second user is subtracted from the first user's information, and then constellation demapping is performed to obtain the information sent to itself by the base station.

[0014] Furthermore, step 1 specifically includes:

[0015] After mapping the information of the two users in the k-th group to a constellation, the base station superimposes the information in the power domain to obtain the superimposed constellation symbol:

[0016]

[0017] Where k = 1, 2, ..., K, l = 0, 1, ..., M-1, z = 0, 1, ..., N-1; X k,1 [l,z] and X k,2 [l, z] represent the constellation symbols of the first and second users in the k-th group, respectively; l and z represent the time delay index value and the Doppler index value, respectively; M and N represent the maximum time delay index value and the maximum Doppler index value, respectively; α k,1 With α k,2 Let these represent the power allocation coefficients for the first user and the second user, respectively, which satisfy the following:

[0018] α k,1 +α k,2 =1

[0019] The constellation symbol after the k-th group of users is superimposed is transformed into a time-domain signal after OTFS modulation:

[0020]

[0021] Among them, s k This represents the time-domain information of the k-th user group obtained after OTFS modulation; I represents the conjugate transpose of an N-dimensional Fourier transform matrix; M Represents an M-dimensional identity matrix; Represents the Kronecker product; Definition but It can be represented as Where vec(·) represents matrix vectorization operation.

[0022] The base station generates a transmission signal s from the time-domain signals of the K groups of users after OTFS modulation and transmits it.

[0023]

[0024] Among them, I MN Let w represent an M×N dimensional identity matrix. k This represents the beamforming vector for the k-th user group.

[0025] Furthermore, the process of constructing the user terminal time-domain received signal is as follows:

[0026] The time-domain received signal r of the c-th user in group k k,c It can be represented as:

[0027] r k,c =G k,c ΘHs+n

[0028] Where c represents the user index value, taking the value 1 or 2; n represents the noise vector; H represents the equivalent channel matrix between the base station and the RIS, expressed as:

[0029]

[0030] Define H BR,g,f This represents the channel response matrix (g = 1, 2, ..., N) between the g-th transmit antenna of the base station and the f-th reflection element of the RIS. t f = 1, 2...N r ), which constitute a submatrix in the g-th row and f-th column of H, H BR,g,f Specifically, it is expressed as follows:

[0031]

[0032] In the above formula, P1 represents the total number of multipaths between the base station and the RIS. Let represent the fading coefficient, time delay coefficient, and Doppler coefficient of the i-th (i = 0, 1, ..., P1-1) path between the g-th transmit antenna of the base station and the f-th reflection element of RIS, respectively. Π is the time delay matrix, and its specific form is shown below:

[0033]

[0034] Δ is the Doppler frequency shift matrix, which can be specifically expressed as:

[0035]

[0036] In the above formula, e represents the natural constant, and j is the imaginary unit;

[0037] G k,c The equivalent channel matrix from RIS to the c-th user in the k-th group is as follows:

[0038]

[0039] definition This represents the channel response matrix from the f-th reflection unit of the RIS to the c-th user in the k-th group, which constitutes G. k,c The f-th submatrix Specifically:

[0040]

[0041] In the formula, P k,c This represents the total number of multipaths from RIS to the c-th user in the k-th group; These represent the fading coefficient, delay coefficient, and Doppler coefficient of the f-th reflection unit of the RIS reaching the c-th user in the k-th group via the a-th path, respectively.

[0042] Θ represents the phase shift matrix of RIS, which can be expressed as:

[0043]

[0044] Where diag(·) represents a diagonal matrix constructed using its elements. I represents the reflection coefficient of each RIS reflection unit. MN Let θ represent an M×N dimensional identity matrix. f This represents the reflection phase of the f-th reflection unit of the RIS.

[0045] Furthermore, the orthogonal time-frequency-space cross-domain multiple access method also includes:

[0046] Determine the user's received signal-to-noise ratio;

[0047] An optimization problem is constructed with the goal of maximizing the system rate. The optimization objective is to find the beamforming vector w of the base station antenna and the power α allocated by the base station to each user information while maximizing the channel capacity of all user groups. k,c The system configuration is performed using the RIS phase shift matrix Θ and these three parameters.

[0048] Further, determining the user's received signal-to-noise ratio includes:

[0049] The received signal-to-noise ratio γ of the first user in group k k,1 Represented as:

[0050]

[0051] Where σ 2 Indicates noise power;

[0052] The received signal-to-noise ratio γ of the second user in group k k,2 Represented as:

[0053]

[0054] Where min(·) represents taking the minimum value, V k,1 V k,2 Unified representation:

[0055]

[0056] G k,c Let H represent the equivalent channel matrix from RIS to the c-th user in the k-th group, and let H represent the equivalent channel matrix between the base station and RIS. k I represents the beamforming vector of the k-th user group. MN This represents an M×N dimensional identity matrix, where c is the index, taking the value 1 or 2; α k,1 With α k,2 These represent the power allocation coefficients for the first user and the second user, respectively.

[0057] Ω k,1 (w,Θ), Ω k,2 (w,Θ) can be uniformly represented as:

[0058]

[0059] Among them, ||·|| 2 This represents the square of the F norm of a matrix.

[0060] Furthermore, the objective optimization problem is expressed as follows:

[0061]

[0062] In the formula, R k,1,min ,R k,2,min Let P represent the minimum channel capacity of the first and second users in the k-th group, respectively. max θ represents the maximum transmission energy of the base station. f R represents the reflection phase of the f-th RIS emitter unit. k,1 R k,2 The channel capacity of the first and second users in the k-th group is represented as:

[0063] R k,1 =log2(1+γ) k,1 )

[0064] R k,2 =log2(1+γ) k,2 ).

[0065] Furthermore, the optimization problem is decomposed into a joint optimization subproblem of beamforming vector and power allocation, and a RIS phase shift matrix optimization subproblem, and solved separately, thereby transforming the optimization problem into a non-convex problem that can be solved using the CVX toolkit.

[0066] A terminal device includes a processor, a memory, and a computer program stored in the memory; when the processor executes the computer program, it implements the orthogonal time-frequency-space cross-domain multiple access method.

[0067] A computer-readable storage medium storing a computer program; when the computer program is executed by a processor, it implements the orthogonal time-frequency-space cross-domain multiple access method.

[0068] Compared with the prior art, the present invention has the following technical features:

[0069] This invention combines optimized beamforming, RIS phase shifting, and power allocation to maximize the system rate of the RIS-assisted OTFS cross-domain multiple access system while ensuring rapid algorithm convergence. Compared with traditional orthogonal multiple access systems, it achieves a higher system rate and more user access. Attached Figure Description

[0070] Figure 1 Convergence analysis diagram for the joint optimization subproblem of beamforming and power allocation;

[0071] Figure 2 Convergence analysis diagram for the RIS phase shift coefficient optimization subproblem;

[0072] Figure 3 This is a performance comparison chart between NOMA and OMA. Detailed Implementation

[0073] This invention addresses the RIS-assisted OTFS cross-domain multiple access system by constructing an optimization problem with the goal of maximizing system rate. It jointly optimizes active beamforming, RIS phase shift coefficients, and power allocation coefficients. Furthermore, it employs semidefinite programming (SDP), continuous convex approximation (SCA), and Schur complement methods to transform the original non-convex optimization problem into a convex optimization problem for solution.

[0074] In a RIS-assisted MIMO-OTFS system, there is one base station, one smart reflector, and K user groups. Each user group contains two users who access each other via multiple access in a non-orthogonal manner. Furthermore, it is assumed that the first user in each group has stronger decoding capabilities, while the second user has weaker decoding capabilities. The base station has N transmit antennas. t N t ≥K, each user is equipped with only one antenna; the number of reflective antenna elements in the RIS is N. r .

[0075] The technical solution of this invention is as follows:

[0076] Step 1: The base station superimposes the information to be transmitted to each user in the power domain, performs OTFS modulation, and then outputs it to N. t The antenna transmits.

[0077] After mapping the information of the two users in the k-th group to a constellation, the base station superimposes the information in the power domain to obtain the superimposed constellation symbol:

[0078]

[0079] Where k = 1, 2, ..., K, l = 0, 1, ..., M-1, z = 0, 1, ..., N-1; X k,1 [l,z] and X k,2[l, z] represent the constellation symbols of the first and second users in the k-th group, respectively; l and z represent the time delay index value and the Doppler index value, respectively; M and N represent the maximum time delay index value and the maximum Doppler index value, respectively; α k,1 With α k,2 Let these represent the power allocation coefficients for the first user and the second user, respectively, which satisfy the following:

[0080] α k,1 +α k,2 =1

[0081] The constellation symbol after the k-th group of users is superimposed is transformed into a time-domain signal after OTFS modulation:

[0082]

[0083] Among them, s k This represents the time-domain information of the k-th user group obtained after OTFS modulation; I represents the conjugate transpose of an N-dimensional Fourier transform matrix; M Represents an M-dimensional identity matrix; Represents the Kronecker product; Definition but It can be represented as Where vec(·) represents matrix vectorization operation.

[0084] The base station generates a transmission signal s from the time-domain signals of the K groups of users after OTFS modulation and transmits it.

[0085]

[0086] Among them, I MN Let w represent an M×N dimensional identity matrix. k The beamforming vector for the k-th user group can be specifically represented as:

[0087]

[0088] in, Representing vectors w respectively k The specific element value, (·) T This represents the transpose of a vector.

[0089] Step 2: The base station's transmitted signal reaches the receiver after being reflected by the RIS.

[0090] The time-domain received signal r of the c-th user in group k k,c It can be represented as:

[0091] r k,c =G k,c ΘHs+n

[0092] Where c represents the user index value, taking the value 1 or 2; n represents the noise vector; H represents the equivalent channel matrix between the base station and the RIS, which can be specifically represented as:

[0093]

[0094] Define H BR,g,f This represents the channel response matrix (g = 1, 2, ..., N) between the g-th transmit antenna of the base station and the f-th reflection element of the RIS. t f = 1, 2...N r ), which constitute a submatrix in the g-th row and f-th column of H, H BR,g,f Specifically, it is expressed as follows:

[0095]

[0096] In the above formula, P1 represents the total number of multipaths between the base station and the RIS. Let represent the fading coefficient, time delay coefficient, and Doppler coefficient of the i-th (i = 0, 1, ..., P1-1) path between the g-th transmit antenna of the base station and the f-th reflection element of RIS, respectively. Π is the time delay matrix, and its specific form is shown below:

[0097]

[0098] Δ is the Doppler frequency shift matrix, which can be specifically expressed as:

[0099]

[0100] In the above formula, e represents the natural constant, and j is the imaginary unit.

[0101] G k,c The equivalent channel matrix from RIS to the c-th user in the k-th group is as follows:

[0102]

[0103] definition This represents the channel response matrix from the f-th reflection unit of the RIS to the c-th user in the k-th group, which constitutes G. k,c The f-th submatrix Specifically:

[0104]

[0105] In the formula, P k,c This represents the total number of multipaths from RIS to the c-th user in the k-th group; Let Π and Δ represent the fading coefficient, delay coefficient, and Doppler coefficient of the f-th reflection unit of the RIS reaching the c-th user in the k-th group via the a-th path, respectively; Π and Δ are in the form of the above.

[0106] Θ represents the phase shift matrix of RIS, which can be expressed as:

[0107]

[0108] Where diag(·) represents a diagonal matrix constructed using its elements. I represents the reflection coefficient of each RIS reflection unit. MN Let θ represent an M×N dimensional identity matrix. f This represents the reflection phase of the f-th reflection unit of the RIS.

[0109] Step 3: Each user performs OTFS demodulation to obtain the information sent by the base station.

[0110] Each group of users will demodulate the time-domain received signal using OTFS, where the demodulated signal of the c-th user in the k-th group is... It can be represented as:

[0111]

[0112] Where F N I represents the conjugate transpose of an N-dimensional Fourier transform matrix; M This represents an M-dimensional identity matrix.

[0113] Then the second user in the kth group directly decodes its own demodulated signal. That is, the second user in the kth group passes Directly perform constellation demapping to obtain the information transmitted to itself by the base station.

[0114] The first user in group k first demodulates the signal. Perform constellation demapping to obtain the information transmitted by the base station to the second user in the k-th group, then from... The information of the second user is subtracted from the first user's information, and then constellation demapping is performed to obtain the information sent to itself by the base station.

[0115] Based on the above scheme, this invention addresses the beamforming vector w of the base station antenna and the power α allocated by the base station to each user. k,c We optimize the solution for three important factors that affect system performance: the RIS phase shift matrix Θ, in order to maximize the system speed.

[0116] Step 4: Determine the user's received signal-to-noise ratio.

[0117] The received signal-to-noise ratio γ of the first user in group k k,1It can be represented as:

[0118]

[0119] Where σ 2 Indicates noise power.

[0120] The received signal-to-noise ratio γ of the second user in group k k,2 It can be represented as:

[0121]

[0122] Where min(·) represents taking the minimum value, V k,1 V k,2 It can be uniformly represented as:

[0123]

[0124] G k,c Let H represent the equivalent channel matrix from RIS to the c-th user in the k-th group, and let H represent the equivalent channel matrix between the base station and RIS. k I represents the beamforming vector of the k-th user group. MN This represents an M×N dimensional identity matrix, where c is the index, taking the value 1 or 2; α k,1 With α k,2 These represent the power allocation coefficients for the first user and the second user, respectively.

[0125] Ω k,1 (w,Θ), Ω k,2 (w,Θ) can be uniformly represented as:

[0126]

[0127] in,‖·‖ 2 This represents the square of the F norm of a matrix.

[0128] Step 5: Construct an optimization problem with the goal of maximizing system speed.

[0129]

[0130] In the formula, R k,1,min ,R k,2,min Let P represent the minimum channel capacity of the first and second users in the k-th group, respectively. max θ represents the maximum transmission energy of the base station. f R represents the reflection phase of the f-th RIS emitter unit. k,1 R k,2 The channel capacity of the first and second users in the k-th group can be expressed as:

[0131] Rk,1 =log2(1+γ) k,1 )

[0132] R k,2 =log2(1+γ) k,2 )

[0133] Step 6: Decouple the optimization problem into two sub-optimization problems and solve them.

[0134] Since the beamforming vector, RIS phase shift matrix, and power allocation coefficient of the base station are tightly coupled in the original optimization problem, making it difficult to solve, the original problem is decomposed into a joint optimization subproblem of beamforming vector and power allocation, and an optimization subproblem of RIS phase shift matrix.

[0135] When solving the joint optimization subproblem of beamforming and power allocation, the RIS phase shift coefficient is kept constant, and the following definition is made: B k,c =(G k,c ΘH) H (G k,c ΘH), where (·) H Let the conjugate transpose of the matrix be used. Then the joint optimization subproblem of beamforming and power allocation can be reformulated as:

[0136]

[0137] C10:0<α k,1 <1

[0138] C11:Q k ≥0

[0139] C12:Rank(Q k ) = 1

[0140] C13:β k,1 ≥γ k,1,min ,β k,2 ≥γ k,2,min

[0141] In the formula, (·) (e) and(·) (e-1) Let represent the variable values ​​obtained in the e-th and (e-1)-th iterations, respectively; Rank(·) represents the rank of the matrix; Tr(·) represents the trace of the matrix; β k,1 ,β k,2 υ represents the signal-to-noise ratio auxiliary parameter introduced during the solution process for the first and second users in the k-th group; k,1 υ k,2 υ k,3 An auxiliary variable introduced to handle bilinear nonconvex constraints; μ k,1 μ k,2Auxiliary variables introduced to handle fractional constraints; c k,1 c k,2 The intermediate auxiliary variables introduced to tighten the upper bound of the constraints and accelerate the convergence of the algorithm are updated according to the following rules in each iteration;

[0142]

[0143] Γ k,1 (Q) and Γ k,2 (Q) can be uniformly represented as:

[0144]

[0145] Where c equals 1 or 2; γ k,1,min With γ k,2,min Specifically:

[0146]

[0147] We can initially ignore the rank-one constraint in C12; the entire problem is a convex optimization problem, solvable using the CVX toolkit. For this sub-optimization problem, the obtained beamforming vector matrix is ​​a rank-one solution. Therefore, the joint optimization sub-problem of beamforming and power allocation is iterated until the change in system rate is less than ε1, where ε1 is a value defined by the solver based on the required accuracy. After solving this sub-problem, the obtained beamforming vector and power allocation coefficients are fixed, and the RIS phase shift matrix is ​​optimized. The RIS phase shift matrix optimization sub-problem can be expressed as:

[0148]

[0149] C6:V≥0

[0150] C7:Rank(V)=1

[0151] C8:β′ k,1 ≥γ k,1,min ,β′ k,2 ≥γ k,2,min

[0152] Where V = θ H θ, Let β′ represent the equivalent channel matrix from the f-th RIS transmitter unit to the c-th user in the k-th group. k,1 ,β′ k,2 μ′ represents the signal-to-noise ratio auxiliary parameter introduced during the solution process for the first and second users in the k-th group. k,1 , μ′ k,2 Auxiliary variables introduced to handle fractional constraints; c′ k ,c″ k,1 ,c″k,2 The intermediate auxiliary variables introduced to tighten the upper bound of the constraints and accelerate the convergence of the algorithm are updated according to the following rules in each iteration:

[0153]

[0154] In the formula: (·) (e) and(·) (e-1) These represent the variable values ​​obtained in the e-th and (e-1)-th iterations, respectively. Additionally: this part...

[0155]

[0156] We can ignore the rank-one constraint in C10 for now. The whole problem is a convex optimization problem, which can be solved using the CVX toolkit. After the matrix V is obtained through optimization, the corresponding θ can be obtained by Gaussian randomization.

[0157] The two subproblems, beamforming and power allocation joint optimization and RIS phase shift matrix optimization, are iteratively solved until the change in system rate is less than Δ. At this point, the beamforming vector, RIS phase shift coefficient, and power allocation coefficient of the base station are output. The base station configures the transmitting antenna according to the obtained beamforming vector, allocates power to users according to the obtained power allocation coefficient, and configures the phase shift of each reflection unit according to the obtained RIS phase shift coefficient. This achieves a higher system rate and improves the service quality of the base station when serving multi-user communication.

[0158] Example:

[0159] Figure 1 The figure shows the convergence analysis of the joint optimization algorithm for beamforming and power allocation; the simulation results in the figure demonstrate the convergence of the sub-optimization algorithm under different numbers of antennas. It can be seen that the joint optimization algorithm for beamforming and power allocation proposed in this invention can achieve fast convergence under different numbers of transmit antennas.

[0160] Figure 2 The figure shows the convergence analysis of the RIS phase shift coefficient optimization algorithm. The simulation results in the figure demonstrate the convergence of the sub-optimization algorithm under different numbers of RIS reflection units. It can be seen that the optimization algorithm proposed in this invention can converge quickly under different numbers of RIS reflection units.

[0161] Figure 3 The system speeds of RIS-OTFS-NOMA and RIS-OTFS-OMA were compared, showing that the NOMA access scheme proposed in this invention can achieve a higher system speed. In addition, the system performance without optimization methods was simulated, showing that the optimization scheme proposed in this invention can greatly improve the system speed.

[0162] The above embodiments are only used to illustrate the technical solutions of this application, and are not intended to limit them. Although this application has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some of the technical features. Such modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the spirit and scope of the technical solutions of the embodiments of this application, and should all be included within the protection scope of this application.

Claims

1. A method of orthogonal time, frequency, space cross-domain multiple access, the method comprising: The method is applied to a RIS-assisted MIMO-OTFS system; the system includes a base station, a smart reflector, and Users are grouped, with each group containing two users who access the network via multiple access in a non-orthogonal manner; the base station has the following transmit antennas: , Each user is equipped with only one antenna; the number of reflective antenna elements in the RIS is... ; Step 1, the base station superimposes the information to be transmitted to each user in the power domain, generates a transmission signal after OTFS modulation, and transmits the signal by Root antenna transmission; Step 2: The base station's transmitted signal reaches the receiver after being reflected by RIS; the user's time-domain received signal is constructed. Step 3: Each group of users performs OTFS demodulation on the time-domain received signal, where the first... The first in the group Demodulation signal for individual users Represented as: in This represents the conjugate transpose of an N-dimensional Fourier transform matrix; Represents an M-dimensional identity matrix. Indicates the first The first in the group Time-domain received signals for each user; Next the second user in the group decodes his own demodulated signal directly i.e. the second user in the group obtains the information transmitted by the base station to himself by direct constellation demapping.​​ No. The first user in the group first demodulated the signal. Perform constellation demapping to obtain the base station's transmission to the first The information of the second user in the group, then from Subtract the information of the second user from the middle, and then perform constellation demapping to obtain the information sent to itself by the base station; The orthogonal time-frequency-space cross-domain multiple access method further includes: Determine the user's received signal-to-noise ratio; including: First user in the group Signal-to-noise ratio of the first user in the group is represented as: wherein denotes the noise power; The first user in the group The received signal-to-noise ratio of the second user in the group Is represented as: wherein denotes taking the minimum value, is represented uniformly as: Indicates RIS to the 1st The first in the group Equivalent channel matrix for each user This represents the equivalent channel matrix between the base station and the RIS. Indicates the first Beamforming vectors for group users, Represents an M×N dimensional identity matrix. The index is 1 or 2; and These represent the power allocation coefficients for the first user and the second user, respectively. Represents the phase shift matrix of RIS; , These represent the maximum value of the delay index and the maximum value of the Doppler index, respectively. , may be expressed uniformly as: wherein denotes the square of the matrix F norm; An optimization problem is constructed with the goal of maximizing the system rate, and the optimization objective is to obtain the beamforming vectors of the base station antennas when maximizing the channel capacity of all groups of users , the power allocated by the base station to each user information , the RIS phase shift matrix , and the system configuration is performed by using the three parameters The objective optimization problem is expressed as follows: In the formula, They represent the first The minimum channel capacity for the first and second users in the group. This indicates the maximum transmission energy of the base station; Indicates the first The reflection phase of each RIS emitter unit Indicates the first The channel capacity of the first and second users in the group is expressed as follows: ； The optimization problem is decomposed into a joint optimization subproblem of beamforming vector and power allocation, and a RIS phase shift matrix optimization subproblem, and solved separately. This transforms the optimization problem into a non-convex problem that can be solved using the CVX toolkit.

2. The orthogonal time frequency space multi-access method of claim 1, wherein, Step 1 specifically includes: The base station will be the first After the information of two users in the group is mapped to a constellation, it is superimposed in the power domain to obtain the superimposed constellation symbol: in, ; and They represent the first The zodiac symbols of the first and second users in the group; , These represent the time delay index value and the Doppler index value, respectively. , These represent the maximum value of the delay index and the maximum value of the Doppler index, respectively. and Let these represent the power allocation coefficients for the first user and the second user, respectively, which satisfy the following: The first The superimposed constellation symbols of the group users are transformed into time domain signals after OTFS modulation: in, This indicates the first [unit / item] obtained after OTFS modulation. Time-domain information of group users; This represents the conjugate transpose of an N-dimensional Fourier transform matrix; Represents an M-dimensional identity matrix; Represents the Kronecker product; Definition ,but Represented as ,in Indicates matrix vectorization operations; The base station will be modulated by OTFS Group user time-domain signal generation and transmission signal And send it: wherein, denotes an M x N dimensional identity matrix, denotes the beamforming vector of the group of users.

3. The orthogonal time frequency space multi-access method of claim 2, wherein, The process of constructing the user terminal time-domain received signal is as follows: The first time-domain received signal of the first user in the group is represented as: wherein, denotes a user index value, taking values 1 or 2; denotes a noise vector; denotes an equivalent channel matrix between the base station and the RIS, denoted as: definition Indicates the base station number root transmit antenna to RIS Channel response matrix between reflection units , Its composition The Middle Line 1 Submatrix of columns, Specifically, it is expressed as follows: In the above formula This represents the total number of multipaths between the base station and the RIS. , , They represent the base station number root transmit antenna to RIS The first reflection unit between the first reflection unit The fading coefficient, delay coefficient, and Doppler coefficient of each path. The time delay matrix is ​​shown in the following form: is the Doppler shift matrix, specifically represented as: In the above formulae, e represents the natural constant, j is the imaginary unit; represents an equivalent channel matrix of the RIS to the user in the th group, specifically: definition Representing the first RIS The first reflecting unit to the second The first in the group The channel response matrix of each user is composed of The Submatrices, Specifically: In the formula, Indicates RIS to the 1st The first in the group The total number of multipaths for each user; , , They represent the first, second, and third RIS, respectively. The first reflective unit passes through the first The path to the first The first in the group Fading coefficient, delay coefficient, and Doppler coefficient for each user; The phase shift matrix representing the RIS is denoted as: in This indicates that the elements form a diagonal matrix. This represents the reflection coefficient of each RIS reflection unit. Represents an M×N dimensional identity matrix. Representing the first RIS The reflection phase of each reflecting unit.

4. A terminal device comprising a processor, a memory, and a computer program stored in the memory; characterized in that, When the processor executes a computer program, it implements the orthogonal time-frequency-space cross-domain multiple access method according to any one of claims 1-3.

5. A computer readable storage medium having stored therein a computer program; characterized in that, When the computer program is executed by the processor, it implements the orthogonal time-frequency-space cross-domain multiple access method according to any one of claims 1-3.

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