Orthogonal time-frequency-space cross-domain multiple access method

Abstract

The invention discloses an orthogonal time-frequency-space cross-domain multiple access method, which is applied to an RIS-assisted MIMO-OTFS system. The base station superposes information prepared to be transmitted to each user in a power domain, and OTFS modulation is carried out to generate a transmission signal; transmitting signals are reflected by the RIS to reach a receiving end, and time domain receiving signals of a user are constructed; each group of users performs OTFS demodulation on the time domain received signals to obtain information sent by the base station; on the basis, optimization solving is carried out on three important factors which influence the system performance, namely a beam forming vector of a base station antenna, power allocated to each piece of user information by a base station and an RIS phase shift matrix, and an original non-convex optimization problem is converted into a convex optimization problem for solving, so that rapid convergence of an algorithm is ensured, and meanwhile, the system performance is effectively improved. The system rate of the OTFS cross-domain multiple access system assisted by the RIS is maximized, and compared with a traditional orthogonal multiple access system, higher system rate and more user access are achieved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless multiple access, and in particular to an orthogonal time-frequency-space cross-domain multiple access method. Background Art

[0002] In recent years, with the advancement of technology, communication scenarios have become increasingly diverse, and communication needs have become increasingly differentiated. Many high-speed mobile scenarios have emerged, including vehicle communications, high-speed rail communications, unmanned aerial vehicle (UAV) communications, and low-Earth Orbit (LEO) satellite communications. In these high-speed mobile communication scenarios, the high relative speeds of the transmitter and receiver and the severe Doppler frequency offset lead to severe 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 technology that modulates information in the Delay-Doppler (DD) domain. It can convert a dual-dispersion 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] Smart Reflecting Surfaces (RIS) can significantly improve the performance of OTFS systems when the direct path is obstructed by constructing reflection paths and adjusting the reflection coefficients of the reflective elements. Choosing the reflection coefficients of the reflective elements is crucial to improving the performance of RIS-assisted OTFS systems. Furthermore, the number of mobile users accessing future communication systems will increase significantly. Given limited time-frequency resources, traditional orthogonal multiple access (OMA) technology will struggle to provide service to a large number of users. Non-orthogonal multiple access (NOMA) technology, however, can accommodate more users and improve system speed compared to OMA. Current research also considers using NOMA for user access in RIS-OTFS systems, but the transmitter uses a single antenna and only optimizes the RIS phase shift coefficient, ignoring the joint optimization of beamforming, RIS phase shift coefficient, and power allocation in RIS-OTFS multi-antenna systems. Consequently, the system loses degrees of freedom and cannot achieve higher system speeds. Summary of the Invention

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

[0005] In order to achieve the above tasks, the present invention adopts the following technical solutions:

[0006] An orthogonal time-frequency-space cross-domain multiple access method is applied to a RIS-assisted MIMO-OTFS system; the system includes a base station, an intelligent reflector, and K groups of users. Each group of users includes two users, and the two users perform multiple access in a non-orthogonal manner; the number of transmitting antennas of the base station is N t , N t ≥K, each user is equipped with only one antenna; the number of reflective antenna units in 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 transmission signal. t Root antenna transmission;

[0008] Step 2: The base station's transmitted signal is reflected by the RIS and reaches the receiving end; 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 cth user in the kth group is It can be expressed as:

[0010]

[0011] Among them F N Represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M represents the M-dimensional identity matrix, r k,c represents the time domain received signal of the cth user in the kth group;

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

[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 kth group, and then The second user’s information is subtracted from the information, and then constellation demapping is performed to obtain the information sent by the base station to itself.

[0014] Furthermore, the step 1 specifically includes:

[0015] The base station performs constellation mapping on the information of the two users in the kth group and superimposes them 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 kth group of users respectively; l and z represent the delay index value and Doppler index value respectively; M and N represent the maximum delay index value and the maximum Doppler index value respectively; α k,1 With α k,2 Denote the power allocation coefficients of the first user and the second user respectively, which satisfy:

[0018] α k,1 +α k,2 =1

[0019] The constellation symbols of the kth group of users are superimposed and transformed into time domain signals after OTFS modulation:

[0020]

[0021] Among them, s k represents the time domain information of the kth group of users obtained after OTFS modulation; Represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M represents the M-dimensional identity matrix; represents the Kronecker product; definition but It can be expressed as where vec(·) represents a matrix vectorized 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 sends it:

[0023]

[0024] Among them, I MN represents the M×N dimensional identity matrix, w k represents the beamforming vector of the kth group of users.

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

[0026] The time domain received signal r of the cth user in the kth group k,c It can be expressed as:

[0027] r k,c =G k,c ΘHs+n

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

[0029]

[0030] Define H BR,g,f represents the channel response matrix between the gth transmitting antenna of the base station and the fth reflection unit of the RIS (g=1,2...N t , f=1,2...N r ), which constitutes the submatrix with the gth row and fth column in H, H BR,g,f Specifically expressed as:

[0031]

[0032] In the above formula, P1 represents the total number of multipaths between the base station and RIS. They represent the fading coefficient, delay coefficient, and Doppler coefficient of the i-th (i=0, 1...P1-1) path between the g-th transmitting antenna of the base station and the f-th reflector unit of the RIS, respectively. π is the delay matrix, which is in the following form:

[0033]

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

[0035]

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

[0037] G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, specifically:

[0038]

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

[0040]

[0041] Where, P k,c represents the total number of multipaths from RIS to the cth user in the kth group; They represent the fading coefficient, delay coefficient, and Doppler coefficient of the transmission from the f-th reflection unit of the RIS to the c-th user in the k-th group through the a-th path;

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

[0043]

[0044] Where diag(·) means that the elements form a diagonal matrix. Represents the reflection coefficient of each RIS reflection unit, I MN represents the M×N dimensional identity matrix, θ f represents the reflection phase of the f-th reflection unit of RIS.

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

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

[0047] The optimization problem is constructed with the goal of maximizing the system rate. The optimization goal 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 when maximizing the channel capacity of all groups of users. k,c , RIS phase shift matrix Θ, and use these three parameters to configure the system.

[0048] Furthermore, determining the received signal-to-noise ratio of the user includes:

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

[0050]

[0051] where σ 2 represents the noise power;

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

[0053]

[0054] Among them, min(·) means taking the minimum value, V k,1 ,V k,2 Unified expression:

[0055]

[0056] G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, H represents the equivalent channel matrix between the base station and RIS, and w k represents the beamforming vector of the kth group of users, I MN Represents the M×N dimensional unit matrix, c is the index, and the value is 1 or 2; α k,1 With α k,2 represent the power allocation coefficients of the first user and the second user respectively;

[0057] Ω k,1 (w,Θ),Ω k,2 (w,Θ) is uniformly expressed as:

[0058]

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

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

[0061]

[0062] Where R k,1,min ,R k,2,min They represent the minimum channel capacity of the first user and the second user in the kth group, P max represents the maximum transmission energy of the base station; θ f represents the reflection phase of the fth RIS transmitting unit, R k,1 、R k,2 The channel capacity between the first user and the second user in the kth group is expressed 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 the joint optimization sub-problem of beamforming vector and power allocation and the optimization sub-problem of RIS phase shift matrix, and these sub-problems are solved separately, thus converting the optimization problem into a non-convex problem and solving it using the CVX toolkit.

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

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

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

[0069] The present invention jointly optimizes beamforming, RIS phase shift, and power allocation, maximizing 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, this system achieves higher system rates and more user access. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0071] Figure 2 This is the convergence analysis diagram of the RIS phase shift coefficient optimization subproblem;

[0072] Figure 3 The following is a performance comparison chart of NOMA and OMA. DETAILED DESCRIPTION

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

[0074] In the RIS-assisted MIMO-OTFS system, there is a base station, a smart reflector, and K groups of users. Each group of users includes two users, and these two users perform multiple access in a non-orthogonal manner. In addition, it is assumed that the first user in each group has stronger decoding ability and the second user has weaker decoding ability. The number of transmitting antennas of the base station is N. t , N t ≥K, each user is equipped with only one antenna; the number of reflective antenna units in RIS is N r .

[0075] The technical solution of the present invention is:

[0076] Step 1: The base station superimposes the information to be transmitted to each user in the power domain and performs OTFS modulation. t Antenna transmission.

[0077] The base station performs constellation mapping on the information of the two users in the kth group and superimposes them 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 kth group of users respectively; l and z represent the delay index value and Doppler index value respectively; M and N represent the maximum delay index value and the maximum Doppler index value respectively; α k,1 With α k,2 Denote the power allocation coefficients of the first user and the second user respectively, which satisfy:

[0080] α k,1 +α k,2 =1

[0081] The constellation symbols of the kth group of users are superimposed and transformed into time domain signals after OTFS modulation:

[0082]

[0083] Among them, s k represents the time domain information of the kth group of users obtained after OTFS modulation; Represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M represents the M-dimensional identity matrix; represents the Kronecker product; definition but It can be expressed as where vec(·) represents a matrix vectorized 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 sends it:

[0085]

[0086] Among them, I MN represents the M×N dimensional identity matrix, w k represents the beamforming vector of the kth group of users, which can be specifically expressed as:

[0087]

[0088] in, Represents vector w respectively k The specific element value in (·) T Represents vector transpose.

[0089] Step 2: The base station's transmission signal is reflected by the RIS and reaches the receiving end.

[0090] The time domain received signal r of the cth user in the kth group k,c It can be expressed as:

[0091] r k,c =G k,c ΘHs+n

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

[0093]

[0094] Define H BR,g,f represents the channel response matrix between the gth transmitting antenna of the base station and the fth reflection unit of the RIS (g=1,2...N t , f=1,2...N r ), which constitutes the submatrix with the gth row and fth column in H, H BR,g,f Specifically expressed as:

[0095]

[0096] In the above formula, P1 represents the total number of multipaths between the base station and RIS. They represent the fading coefficient, delay coefficient, and Doppler coefficient of the i-th (i=0, 1...P1-1) path between the g-th transmitting antenna of the base station and the f-th reflector unit of the RIS, respectively. π is the delay matrix, which is in the following form:

[0097]

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

[0099]

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

[0101] G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, specifically:

[0102]

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

[0104]

[0105] Where, P k,c represents the total number of multipaths from RIS to the cth user in the kth group; They represent the fading coefficient, delay coefficient, and Doppler coefficient of the transmission from the f-th reflection unit of the RIS to the c-th user in the k-th group through the a-th path respectively; the forms of π and Δ are as above.

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

[0107]

[0108] Where diag(·) means that the elements form a diagonal matrix. Represents the reflection coefficient of each RIS reflection unit, I MN represents the M×N dimensional identity matrix, θ f represents the reflection phase of the f-th reflection unit of RIS.

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

[0110] Each group of users performs OTFS demodulation on the time domain received signal, where the demodulated signal of the cth user in the kth group is It can be expressed as:

[0111]

[0112] Among them F N Represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M Represents the M-dimensional identity matrix.

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

[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 kth group, and then The second user’s information is subtracted from the information, and then constellation demapping is performed to obtain the information sent by the base station to itself.

[0115] Based on the above solution, the present invention aims at the beamforming vector w of the base station antenna and the power α allocated by the base station to each user information. k,c , RIS phase shift matrix Θ, three important factors that affect system performance, are optimized and solved to maximize the system rate.

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

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

[0118]

[0119] where σ 2 Represents the noise power.

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

[0121]

[0122] Among them, min(·) means taking the minimum value, V k,1 ,V k,2 It can be expressed uniformly as:

[0123]

[0124] G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, H represents the equivalent channel matrix between the base station and RIS, and w k represents the beamforming vector of the kth group of users, I MN Represents the M×N dimensional unit matrix, c is the index, and the value is 1 or 2; α k,1 With α k,2 Represent the power allocation coefficients of the first user and the second user respectively.

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

[0126]

[0127] in,‖·‖ 2 Represents the square of the norm of matrix F.

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

[0129]

[0130] Where R k,1,min ,R k,2,min They represent the minimum channel capacity of the first user and the second user in the kth group, P max represents the maximum transmission energy of the base station; θ f represents the reflection phase of the fth RIS transmitting unit, R k,1 、R k,2 The channel capacity between the first user and the second user in the kth 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 for solution.

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

[0135] When solving the joint optimization subproblem of beamforming and power allocation, the RIS phase shift coefficient is fixed and defined as B k,c =(G k,c ΘH) H (G k,c ΘH), where (·) H Denotes the conjugate transpose of the matrix, 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] Where, (·) (e) and(·) (e-1) denote the variable values ​​obtained in the e-th and e-1-th iterations respectively, Rank(·) denotes the rank of the matrix; Tr(·) denotes the trace of the matrix; β k,1 , β k,2 represents the auxiliary parameter of the signal-to-noise ratio of the first and second users in the kth group introduced during solution; k,1 ,υ k,2 ,υ k,3 Auxiliary variables introduced to deal with bilinear non-convex constraints; μ k,1 , μ k,2Auxiliary variables introduced to deal with fractional constraints; c k,1 , c k,2 In order to tighten the upper bound of the constraint and speed up the convergence of the algorithm, the intermediate auxiliary variables are introduced. The update rules in each iteration are as follows;

[0142]

[0143] Γ k,1 (Q) and Γ k,2 (Q) is uniformly expressed as:

[0144]

[0145] Where c is equal to 1 or 2; γ k,1,min with γ k,2,min Specifically:

[0146]

[0147] The rank-one constraint in C12 can be ignored for now. The entire problem is a convex optimization problem that can be solved using the CVX toolkit. For this sub-optimization problem, the resulting 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 specified based on the solution accuracy. After solving this sub-problem, the resulting beamforming vector and power allocation coefficient 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, β′ represents the equivalent channel matrix from the fth RIS transmitting unit to the cth user in the kth group. k,1 , β′ k,2 μ′ represents the auxiliary parameter of the signal-to-noise ratio of the first and second users in the kth group introduced during solution; k,1 , μ′ k,2 Auxiliary variables introduced to deal with fractional constraints; c′ k , c″ k,1 , c″k,2 In order to tighten the upper bound of the constraint and speed up the convergence of the algorithm, the intermediate auxiliary variables are introduced. The update rules in each iteration are as follows:

[0153]

[0154] Where: (·) (e) and(·) (e-1) Represents the variable values ​​obtained in the e-th and e-1-th iterations respectively. In addition: This part

[0155]

[0156] We can ignore the rank-one constraint in C10. The entire problem is a convex optimization problem, which can be solved using the CVX toolkit. After optimizing the matrix V, we can use the Gaussian randomization method to obtain the corresponding θ.

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

[0158] Example:

[0159] Figure 1 This is a convergence analysis diagram for the joint optimization algorithm for beamforming and power allocation. The simulation demonstrates the convergence of the sub-optimization algorithms for different numbers of antennas. It can be seen that the proposed joint optimization algorithm for beamforming and power allocation achieves rapid convergence for different numbers of transmit antennas.

[0160] Figure 2 This is a convergence analysis diagram of the RIS phase shift coefficient optimization algorithm. The simulation shows the convergence of the sub-optimization algorithm with different numbers of RIS reflector units. It can be seen that the optimization algorithm proposed in this invention can converge quickly with different RIS reflector units.

[0161] Figure 3 The RIS-OTFS-NOMA system rate is compared with the RIS-OTFS-OMA system rate. It can be seen that the NOMA access scheme proposed in the present invention can achieve a higher system rate. In addition, the performance of the system without the optimization method is simulated. It can be seen that the optimization scheme proposed in the present invention can greatly improve the system rate.

[0162] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the various embodiments of the present application, and should all be included in the scope of protection of the present application.

Claims

1. An orthogonal time-frequency-space cross-domain multiple access method, characterized in that: The method is applied to a RIS-assisted MIMO-OTFS system; the system includes a base station, an intelligent reflector, and K groups of users. Each group of users includes two users, and the two users perform multiple access in a non-orthogonal manner; the number of transmitting antennas of the base station is N t , N t ≥K, each user is equipped with only one antenna; the number of reflective antenna units in RIS is N r ; Step 1: The base station superimposes the information to be transmitted to each user in the power domain, performs OTFS modulation, and generates a transmission signal. t Antenna transmission; Step 2: The base station's transmission signal is reflected by the RIS and reaches the receiving end; the user's time domain receiving signal is constructed; Step 3: Each group of users performs OTFS demodulation on the time domain received signal, where the demodulated signal of the cth user in the kth group is It can be expressed as: where F N represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M represents the M-dimensional identity matrix, r k,c represents the time domain received signal of the cth user in the kth group; Then the second user in group k directly decodes its own demodulated signal That is, the second user in group k passes Directly perform constellation demapping to obtain the information transmitted by the base station to itself. The first user in the kth group first demodulates the signal Perform constellation demapping to obtain the information transmitted by the base station to the second user in the kth group, and then Subtract the second user’s information from the received signal, and then perform constellation demapping to obtain the information sent by the base station to itself.

2. The orthogonal time-frequency-space cross-domain multiple access method according to claim 1, characterized in that: The step 1 specifically includes: After constellation mapping, the base station superimposes the information of the two users in the kth group in the power domain to obtain the superimposed constellation symbol: 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 user and the second user in the kth group of users respectively; l, z represent the delay index value and Doppler index value respectively, M, N represent the maximum delay index value and the maximum Doppler index value respectively; α k,1 With α k,2 They represent the power allocation coefficients of the first user and the second user, respectively, which satisfy: α k,1 +α k,2 ＝1 The constellation symbols after superposition of the kth group of users are transformed into time domain signals after OTFS modulation: Among them, s k represents the time domain information of the kth group of users obtained after OTFS modulation; represents the conjugate transpose of the N-dimensional Fourier transform matrix; I M represents the M-dimensional identity matrix; represents the Kronecker product; definition but It can be expressed as Where vec(·) represents a matrix vectorization operation. The base station generates a transmission signal s from the time domain signal of the K groups of users after OTFS modulation and sends it: Among them, I MN represents the M×N dimensional identity matrix, w k represents the beamforming vector of the kth group of users.

3. The orthogonal time-frequency-space cross-domain multiple access method according to claim 1, characterized in that: The process of constructing the user-side time domain received signal is as follows: The time domain received signal r of the cth user in the kth group k,c It can be expressed as: r k,c =G k,c ΘHs+n Where c represents the user index value, which takes the value of 1 or 2; n represents the noise vector; H represents the equivalent channel matrix between the base station and the RIS, which is expressed as: Definition H BR,g,f represents the channel response matrix between the gth transmitting antenna of the base station and the fth reflection unit of the RIS (g = 1, 2...N t ,f=1,2...N r ), which constitutes the submatrix with the gth row and fth column in H, H BR,g,f Specifically expressed as: In the above formula, P1 represents the total number of multipaths between the base station and RIS. They represent the fading coefficient, delay coefficient, and Doppler coefficient of the i-th (i=0,1...P1-1) path between the g-th transmitting antenna of the base station and the f-th reflection unit of the RIS, respectively. Π is the delay matrix. The specific form is as follows: Δ is the Doppler frequency shift matrix, which can be specifically expressed as: In the above formula, e represents a natural constant and j is an imaginary unit; G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, specifically: definition represents the channel response matrix from the fth reflection unit of RIS to the cth user in the kth group, which constitutes G k,c The f-th sub-matrix of Specifically: Where P k,c represents the total number of multipaths from RIS to the cth user in the kth group; They represent the fading coefficient, delay coefficient, and Doppler coefficient of the f-th reflection unit of RIS reaching the c-th user in the k-th group through the a-th path; Θ represents the phase shift matrix of RIS, which can be expressed as: Where diag(·) means that the elements form a diagonal matrix. Represents the reflection coefficient of each RIS reflection unit, I MN represents the M×N dimensional identity matrix, θ f represents the reflection phase of the fth reflection unit of RIS.

4. The orthogonal time-frequency-space cross-domain multiple access method according to claim 1, characterized in that: The orthogonal time-frequency-space cross-domain multiple access method further includes: Determine the user's received signal-to-noise ratio; The optimization problem is constructed with the goal of maximizing the system rate. The optimization goal is to obtain the beamforming vector w of the base station antenna and the power α allocated by the base station to each user information when maximizing the channel capacity of all groups of users. k,c , RIS phase shift matrix Θ, and use these three parameters to configure the system.

5. The orthogonal time-frequency-space cross-domain multiple access method according to claim 4, characterized in that: The determining of the received signal-to-noise ratio of the user includes: The received signal-to-noise ratio γ of the first user in the kth group k,1 It is expressed as: where σ 2 represents the noise power; The received signal-to-noise ratio γ of the second user in the kth group k,2 It is expressed as: Among them, min(·) means taking the minimum value, V k,1 ,V k,2 The unified expression is: G k,c represents the equivalent channel matrix from RIS to the cth user in the kth group, H represents the equivalent channel matrix between the base station and RIS, and w k represents the beamforming vector of the kth group of users, I MN represents the M×N dimensional unit matrix, c is the index, and its value is 1 or 2; α k,1 With α k,2 represent the power allocation coefficients of the first user and the second user respectively; Ω k,1 (w,Θ),Ω k,2 (w,Θ) is uniformly expressed as: Among them, ||·|| 2 Represents the square of the norm of the matrix F.

6. The orthogonal time-frequency-space cross-domain multiple access method according to claim 4, characterized in that: The target optimization problem is expressed as follows: s.t.C1:R k,1 ≥R k,1,min C2:R k,2 ≥R k,2,min C3: C4:α k,1 +α k,2 ＝1 C5:α k,1 ＞0,α k,2 ＞0 C6:θ f ∈(-π,π],f=1,2,…,N r In the formula, R k,1,min ,R k,2,min They represent the minimum channel capacity of the first user and the second user in the kth group, respectively, max Indicates the maximum transmission energy of the base station; θ f represents the reflection phase of the fth RIS transmitting unit, R k,1 , R k,2 It represents the channel capacity between the first user and the second user in the kth group, expressed as: R k,1 =log2(1+γ k,1 ) R k,2 =log2(1+γ k,2 )。 7. The orthogonal time-frequency-space cross-domain multiple access method according to claim 4, characterized in that: The optimization problem is decomposed into the joint optimization subproblem of beamforming vector and power allocation and the optimization subproblem of RIS phase shift matrix and solved separately, thus converting the optimization problem into a non-convex problem and solving it using the CVX toolkit.

8. A terminal device comprising a processor, a memory and a computer program stored in the memory; characterized in that: When the processor executes the computer program, it implements the orthogonal time-frequency-space cross-domain multiple access method according to any one of claims 1-7.

9. A computer-readable storage medium, wherein a computer program is stored in the medium; characterized in that: When the computer program is executed by a processor, the orthogonal time-frequency-space cross-domain multiple access method according to any one of claims 1-7 is implemented.

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