A NOMA system uplink transmission method assisted by multiple intelligent reflectors

Abstract

The present invention discloses a method for uplink transmission of a NOMA system assisted by multiple intelligent reflective surfaces, the method comprising: obtaining system parameters of the NOMA system and user parameters in the system; clustering users according to the gain of the direct channel, and obtaining a clustering result in which each subcarrier schedules a central user and an edge user; based on the obtained parameters and clustering results, obtaining a total received signal expression at the base station and a signal-to-interference-noise ratio expression of each user; according to the obtained expression, optimizing the transmit power and phase offset using a preset optimization method, obtaining an optimal phase offset, and obtaining an optimal solution for the total transmit power of the NOMA system using the relationship between the transmit power and the phase offset. The present invention jointly optimizes the user transmit power and the phase offset of the intelligent reflective surface, and can reduce the total transmit power consumption of the multiple intelligent reflective surface assisted NOMA system under the premise of satisfying the user's minimum transmission rate.

Description

Technical Field

[0001] The present invention relates to a multi-intelligent reflector-assisted NOMA system uplink transmission method, belonging to the technical field of non-orthogonal multiple access in wireless communications. Background Art

[0002] Intelligent reflecting surface (IRS) can use artificial electromagnetic materials to reshape the phase shift of the incident signal, and has the ability to improve spectrum and energy efficiency. Therefore, with the help of IRS, the user's service quality can be effectively improved. In addition, non-orthogonal multiple access (NOMA) can carry the number of concurrent users without being limited by the number of system resource blocks. Compared with traditional orthogonal multiple access (OMA), it can make a better compromise between system spectrum efficiency and user fairness. Therefore, the integration of NOMA and IRS can further improve the performance of the system.

[0003] At present, the transmission method of the multi-IRS-assisted NOMA system does not fully jointly optimize the user's transmission power and the phase offset of the IRS. For the random phase shift IRS-NOMA scheme, the channel state information is not fully utilized to regulate the phase shift of the IRS. For the IRS-OMA scheme, the advantages of multi-user superposition transmission and interference cancellation of the same resource are not utilized. For the NOMA scheme without IRS assistance, the advantages of IRS in useful signal enhancement and interference channel cancellation cannot be utilized. Therefore, the above schemes do not efficiently utilize the power resources of the system. Summary of the invention

[0004] The purpose of the present invention is to overcome the deficiencies in the prior art and provide a multi-intelligent reflector-assisted NOMA system uplink transmission method, which can reduce the total transmission power consumption of the multi-intelligent reflector-assisted NOMA system under the premise of meeting the user's minimum transmission rate. To achieve the above purpose, the present invention is implemented by adopting the following technical solutions:

[0005] In a first aspect, the present invention provides a NOMA system uplink transmission method assisted by multiple intelligent reflectors, comprising:

[0006] Obtain the system parameters of the NOMA system and the user parameters in the system;

[0007] The users are clustered according to the gain of the direct channel, and a clustering result is obtained in which one central user and one edge user are scheduled for each subcarrier;

[0008] Based on the acquired parameters and clustering results, the total received signal expression at the base station and the signal-to-interference-noise ratio expression of each user are obtained;

[0009] According to the obtained expression, the preset optimization method is used to optimize the transmit power and phase offset to obtain the optimal phase offset. The relationship between transmit power and phase offset is used to obtain the optimal solution for the total transmit power of the NOMA system.

[0010] In combination with the first aspect, further, clustering users according to gains of direct channels includes:

[0011] Find the central user and edge user with the largest channel difference and match them with channel 1;

[0012] Delete the two matched users, select the central user and the edge user with the largest difference from the remaining users, and match them to channel 2;

[0013] The central users and the marginal users are assigned one by one in turn until all users have completed the assignment.

[0014] In combination with the first aspect, further, the preset optimization method includes:

[0015] Under the premise of meeting the minimum transmission rate requirements of each user, an optimization model P1 of transmission power and phase offset is established. The optimization goal is to minimize the total transmission power of the NOMA system, and the optimization variables are the transmission power of each user and the phase offset of the smart reflector.

[0016] When the optimization model P1 takes the optimal value, the constraint condition about the minimum rate requirement in the optimization model P1 takes the equal sign, and the optimization model P1 is transformed into the optimization model P2 of pure phase shift;

[0017] Optimize the signal-to-interference-noise ratio expression of each user and transform the pure phase shift optimization model P2 into the optimization model P3;

[0018] The closed-form solution of the optimal phase offset is obtained by solving the optimization model P3, and the optimal solution of the total system transmit power is obtained by using the relationship between transmit power and phase offset.

[0019] In combination with the first aspect, further, the optimization model P1 is represented by the following formula:

[0020]

[0021] stQ1: γ C，i ≥γ C，i (th) 1≤i≤K

[0022] Q2: γ E，j ≥γ E，j (th) 1≤j≤K

[0023]

[0024] (1) In C，i represents the energy allocation coefficient of central user i, β E，j represents the energy allocation coefficient of edge user j, γ C，i represents the signal-to-interference-noise ratio of the central user i, γ C，i (th) represents the minimum data rate of the central user i, γ E，j represents the signal-to-interference-noise ratio of edge user j, γ E，j (th) represents the minimum data rate of edge user j, Φ j represents the phase shift matrix of the jth smart reflector, N j Indicates the number of reflective elements in each smart reflective surface, represents the nth reflection element in edge user j, n = {1, 2, ..., N j}, K represents the number of edge users and the number of center users in the cell, and P represents the total transmission power of the NOMA system.

[0025] In combination with the first aspect, further, converting the optimization model P1 into the pure phase shift optimization model P2 includes:

[0026] When the optimization model P1 obtains the optimal solution, the constraint conditions 1 and 2 regarding the minimum rate requirement are equal, and the transmission power required by the cell edge users and the center users is obtained. The transmission power required by the cell edge users β E，j 2 for:

[0027]

[0028] (2) represents the noise power, represents the channel coefficient from edge user j to the base station, G j represents the channel coefficient from the jth RIS to the base station, represents the channel coefficient from edge user j to the smart reflection surface;

[0029] The transmission power required by the user in the cell center β C，i 2 for:

[0030]

[0031] (3) In C，i represents the channel coefficient from the central user i to the base station;

[0032] Substituting equations (2) and (3) into the objective function of the optimization model P1, the total transmit power is:

[0033]

[0034] Then the optimization model P2 of pure phase shift is expressed by the following formula:

[0035]

[0036]

[0037] In combination with the first aspect, further, the optimization model P3 is represented by the following formula:

[0038]

[0039]

[0040] (6) Represents vector g j The conjugate transpose of j and g j It is expressed by the following formula:

[0041]

[0042]

[0043] In combination with the first aspect, further, the closed-form solution of the optimal phase offset is expressed by the following formula:

[0044]

[0045] (8) In [g j ] n Represents vector g j The optimal phase shift for the nth element of is:

[0046]

[0047] The relationship between transmit power and phase shift is used to obtain the optimal solution for the total transmit power of the system.

[0048] In a second aspect, the present invention provides a NOMA system uplink transmission transposition assisted by multiple intelligent reflectors, including:

[0049] Acquisition module: used to obtain system parameters of the NOMA system and user parameters in the system;

[0050] Clustering module: used to cluster users according to the gain of the direct channel, and obtain a clustering result in which each subcarrier schedules a central user and an edge user;

[0051] Calculation module: used to obtain the total received signal expression at the base station and the signal to interference and noise ratio expression of each user based on the acquired parameters and clustering results;

[0052] Optimization module: It is used to optimize the transmit power and phase offset according to the obtained expression using a preset optimization method to obtain the optimal phase offset, and use the relationship between the transmit power and the phase offset to obtain the optimal solution for the total transmit power of the NOMA system.

[0053] In a third aspect, the present invention provides a NOMA system uplink transmission system assisted by multiple intelligent reflectors, including a processor and a storage medium;

[0054] The storage medium is used to store instructions;

[0055] The processor is used to operate according to the instructions to execute the steps of the method described in the first aspect.

[0056] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein the program, when executed by a processor, implements the steps of the method described in the first aspect.

[0057] Compared with the prior art, the beneficial effects achieved by the NOMA system uplink transmission method assisted by multiple intelligent reflectors provided in the embodiment of the present invention include:

[0058] The present invention obtains system parameters of the NOMA system and user parameters in the system; clusters users according to the gain of the direct channel, and obtains a clustering result in which each subcarrier schedules a central user and an edge user; the present invention can complete the one-to-one allocation of central users and edge users;

[0059] Based on the acquired parameters and clustering results, the present invention obtains the total received signal expression at the base station and the signal to interference and noise ratio expression of each user; according to the obtained expression, the transmission power and phase offset are optimized by a preset optimization method to obtain the optimal phase offset, and the relationship between the transmission power and the phase offset is used to obtain the optimal solution for the total transmission power of the NOMA system. The present invention jointly optimizes the user's transmission power and the phase offset of the smart reflector surface to achieve a high degree of integration of the smart reflector surface and the NOMA technology, and can reduce the total transmission power consumption of the multi-intelligent reflector-assisted NOMA system while meeting the user's minimum transmission rate. BRIEF DESCRIPTION OF THE DRAWINGS

[0060] Figure 1 This is a system model diagram of a NOMA system uplink transmission method assisted by multiple intelligent reflectors provided in Example 1 of the present invention;

[0061] Figure 2is a curve diagram of total transmit power consumption of a NOMA system under different signal-to-interference-noise ratio conditions provided by Example 2 of the present invention;

[0062] Figure 3 This is a curve diagram of total transmission power consumption of systems with different numbers of reflective elements in the smart reflective surface provided by Example 2 of the present invention. DETAILED DESCRIPTION

[0063] The present invention will be further described below in conjunction with the accompanying drawings. The following embodiments are only used to more clearly illustrate the technical solution of the present invention, and cannot be used to limit the protection scope of the present invention.

[0064] Embodiment 1:

[0065] This embodiment provides a NOMA system uplink transmission method assisted by multiple intelligent reflectors, including:

[0066] Obtain the system parameters of the NOMA system and the user parameters in the system;

[0067] The users are clustered according to the gain of the direct channel, and a clustering result is obtained in which one central user and one edge user are scheduled for each subcarrier;

[0068] Based on the acquired parameters and clustering results, the total received signal expression at the base station and the signal-to-interference-noise ratio expression of each user are obtained;

[0069] According to the obtained expression, the preset optimization method is used to optimize the transmit power and phase offset to obtain the optimal phase offset. The relationship between transmit power and phase offset is used to obtain the optimal solution for the total transmit power of the NOMA system.

[0070] The specific steps include:

[0071] Step 1: Obtain the system parameters of the NOMA system and the user parameters in the system.

[0072] like Figure 1 The figure shows the model diagram of the multi-carrier NOMA system in this embodiment. There are K central users and K edge users, and the base station and the users are equipped with a single antenna. The coverage radius of the cell is R B , the central users are randomly distributed in a radius of R N To R C In the annular area, edge users are randomly distributed around the intelligent reflective surface with R I Assume that there are K smart reflectors distributed at the edge of the cell, each smart reflector is assigned an edge user, and the distance between the kth smart reflector and the base station is D kThe system contains K sub-channels. Since the number of channels is less than the number of users in the system, each channel is allocated to one central user and one edge user at the same time, and the two users use NOMA to transmit data.

[0073] Step 2: Cluster the users according to the gain of the direct channel, and obtain a clustering result in which each subcarrier schedules one central user and one edge user.

[0074] Step 2.1: According to the characteristics of NOMA technology, the greater the difference between the two user channels, the greater the performance improvement. Since the channel gain position is reflected during allocation, allocation is performed based on the gain of the direct channel. Find the central user and edge user with the largest channel difference and match them to channel 1.

[0075] The expression for the maximum value of channel 1 difference is:

[0076]

[0077] In formula (1), h m1 Indicates the maximum value of channel 1 difference, h C，i represents the channel coefficient from the central user i to the base station, represents the channel coefficient from edge user j to the base station.

[0078] The central user with the largest channel difference is α1, and the edge user is β1, which are assigned to channel 1.

[0079] Step 2.2: Delete the two matched users, select the central user and edge user with the largest difference from the remaining users, and match them to channel 2.

[0080] Among the remaining users, the maximum value of channel 2 difference is expressed as:

[0081]

[0082] In formula (2), h m2 Indicates the maximum value of channel 2 difference, h C，i represents the channel coefficient from the central user i to the base station, represents the channel coefficient from edge user j to the base station.

[0083] The central user with the largest channel difference is α2, and the edge user is β2, so they are assigned to channel 2.

[0084] Step 2.3: Assign the central users and edge users one by one in turn until all users have completed the assignment.

[0085] When the nth channel is allocated, the maximum value of the channel difference among the remaining users is expressed as:

[0086]

[0087] In formula (3), h mn represents the maximum value of the nth channel difference, h C，i represents the channel coefficient from the central user i to the base station, represents the channel coefficient from edge user j to the base station.

[0088] The obtained h C，i The central user i is set to α n , The marginal user j is set to β n Thus, the one-to-one allocation between central users and marginal users is completed.

[0089] Step 3: Based on the acquired parameters and clustering results, the total received signal expression at the base station and the signal to interference and noise ratio expression of each user are obtained.

[0090] Step 3.1: Obtain a mathematical expression of the total received signal at the base station receiving end on each subchannel.

[0091] In NOMA mode, two users in the same cluster send signals to the base station on the same time-frequency resources. The total received signal z at the base station is expressed by the following formula:

[0092]

[0093] In formula (4), h C，i represents the channel coefficient from the central user i to the base station, β C，i represents the energy allocation coefficient of central user i, β E，j represents the energy allocation coefficient of edge user j, x C，i represents the transmission signal of the central user i, x E，j represents the transmission signal of edge user j, represents the channel coefficient from edge user j to the base station, G j represents the channel coefficient from the jth RIS to the base station, represents the channel coefficient from edge user j to RIS, K represents the number of central users in the cell and the number of edge users in the cell, Φ j represents the phase shift matrix of the jth smart reflector, N j Indicates the number of reflective elements in each smart reflective surface, represents the phase shift of the nth smart reflector in edge user j, n = {1, 2, ..., N j}, p represents the Gaussian noise at the base station Represents the noise power.

[0094] Step 3.2: Get the signal-to-interference-and-noise ratio expression of each user.

[0095] According to the NOMA uplink demodulation principle, the signals of the central user and the edge user are demodulated in order from small to large according to the propagation distance. When the signal of the central user is demodulated, it is deleted from the total received signal, and then the signal of the edge user is demodulated, and the signal-to-interference-noise ratio expression of each user is obtained respectively.

[0096] In order to obtain the same received power at the base station, the cell center user with better channel conditions needs less transmission power than the edge user. First, the signal of the center user i is decoded at the BS. The expression of the demodulated signal of the center user i at the base station is:

[0097]

[0098] In formula (5), represents the demodulated signal of the central user i at the base station.

[0099] Before decoding the edge user's signal, the recovered signal of the center user is subtracted, and the expression of the demodulated signal of edge user j at the base station is:

[0100]

[0101] In formula (6), represents the demodulated signal of edge user j at the base station.

[0102] When decoding the information of the central user, the signal from the edge user is regarded as noise, so the expression of the signal to interference and noise ratio of the central user i at the base station is:

[0103]

[0104] In formula (7), γ C，i represents the signal to interference and noise ratio of the central user i at the base station.

[0105] When decoding the information of edge users, there is only the white noise of the system itself, so the expression of the signal to interference and noise ratio of edge user j at the base station is:

[0106]

[0107] In formula (8), γ E，j represents the signal to interference and noise ratio of edge user j at the base station.

[0108] Step 4: According to the obtained expression, the preset optimization method is used to optimize the transmit power and phase offset to obtain the optimal phase offset, and the relationship between the transmit power and the phase offset is used to obtain the optimal solution for the total transmit power of the NOMA system.

[0109] Step 4.1: Under the premise of meeting the minimum transmission rate requirements of each user, establish the optimization model P1 of transmission power and phase offset. The optimization goal is to minimize the total transmission power of the NOMA system, and the optimization variables are the transmission power of each user and the phase offset of the smart reflection surface.

[0110] The optimization model P1 is expressed by the following formula:

[0111]

[0112] stQ1: γ C，i ≥γ C，i (th) 1≤i≤K

[0113] Q2: γ E，j ≥γ E，j (th) 1≤j≤K

[0114]

[0115] In (9), γ C，i represents the signal-to-interference-noise ratio of the central user i, γ C，i (th) represents the minimum data rate of the central user i, γ E，j represents the signal-to-interference-noise ratio of edge user j, γ E，j (th) represents the minimum data rate of edge user j, K represents the number of edge users and the number of central users in the cell, and P represents the total transmission power of the NOMA system.

[0116] Among them, constraints 1 and 2 are used to limit the service quality of each user.

[0117] Step 4.2: When the optimization model P1 takes the optimal value, the constraint condition regarding the minimum rate requirement in the optimization model P1 takes the equal sign, and the optimization model P1 is converted into the pure phase shift optimization model P2.

[0118] By using some characteristics of optimization theory, the optimization model P1 is transformed into a pure phase shift optimization problem. By invoking this contradiction, it can be obtained that when the optimization model P1 obtains the optimal solution, when constraints 1 and 2 are equal, the transmission power required by the cell edge user is:

[0119]

[0120] The transmission power required by the user in the cell center is:

[0121]

[0122] Substituting equations (10) and (11) into the objective function of the optimization model P1, the total transmission power is:

[0123]

[0124] The optimization model P2 of pure phase shift is expressed by the following formula:

[0125]

[0126]

[0127] Step 43: Optimize the signal-to-interference-noise ratio expression of each user, and transform the pure phase shift optimization model P2 into the optimization model P3.

[0128] The signal to interference noise ratio is expressed in a compact form as follows:

[0129]

[0130]

[0131] The optimization model P3 is expressed by the following formula:

[0132]

[0133]

[0134] (15) Represents vector g j The conjugate transpose of .

[0135] Step 4.4: Solve the optimization model P3 to obtain the closed-form solution of the optimal phase offset, and use the relationship between the transmit power and the phase offset to obtain the optimal solution of the total transmit power of the system.

[0136] The closed-form solution for the optimal phase shift is expressed as follows:

[0137]

[0138] In (16), [g j ] n Represents vector g j The optimal phase shift for the nth element of is:

[0139]

[0140] The relationship between transmit power and phase shift is used to obtain the optimal solution for the total transmit power of the system.

[0141] The present invention jointly optimizes the user transmission power and the phase offset of the smart reflector to achieve a high degree of integration of the smart reflector and NOMA technology. Under the premise of meeting the user's minimum transmission rate, it can reduce the total transmission power consumption of the multi-intelligent reflector-assisted NOMA system.

[0142] Embodiment 2:

[0143] The embodiment of the present invention adopts the method described in the first embodiment to perform simulation operation.

[0144] The system parameters are as follows: the coverage radius of the cell R B = 200m, the central user coverage area is a ring area, the inner radius R N =20, outer radius R C =70, the number of antennas for each user is 1, the number of central users and edge users is K, K = 5, the noise power The channel is modeled as the product of path loss and small-scale fading, where the path loss exponent η from the central user to the base station is C =3.5, the path loss index from edge users to base stations is η E =4.5, path loss index η from RIS to base station I，B =4, path loss index η from edge user to RIS E，I =3, small-scale fading obeys Ricean fading, and the Ricean K factor of each channel is 4.

[0145] Figure 2 The total transmission power consumption curve of the NOMA system under different signal-to-interference-noise ratio conditions is given, where the number of reflective elements N in the smart reflective surface j =128, and four cases are considered respectively: the uplink transmission method of the OMA system assisted by the smart reflector, the uplink transmission method of the NOMA system without the assistance of the smart reflector, the uplink transmission of the NOMA system assisted by the smart reflector under random phase conditions, and the uplink transmission of the NOMA system assisted by the smart reflector after optimizing the phase shift. Figure 2 It can be seen that the total transmission power is significantly improved after optimizing the phase shift. In addition, the total transmission power under the OMA scheme is greater than that of NOMA, which can prove that the NOMA system has better performance. Finally, it can be seen from the figure that the performance of the NOMA system without adding smart reflectors is significantly lower, which fully illustrates the advantages of the smart reflector-assisted NOMA system.

[0146] Figure 3 The total transmission power consumption curve of the system with different numbers of reflection elements in the smart reflection surface, and the SINR threshold values ​​of the central user and the edge user are given. Four cases are considered at the same time: the uplink transmission method of the OMA system assisted by the smart reflector, the uplink transmission method of the NOMA system without the assistance of the smart reflector, the uplink transmission of the NOMA system assisted by the smart reflector under random phase conditions, and the uplink transmission of the NOMA system assisted by the smart reflector after optimizing the phase shift. It can be found that the total transmission power decreases with the increase of the number of reflection elements in the smart reflector. The reason is that a large number of smart reflector elements produce enhanced received signal power. Under different conditions of the number of reflection elements, the total transmission power consumption of the method of the present invention is lower than that of other NOMA methods and traditional orthogonal multiple access methods.

[0147] Embodiment three:

[0148] The embodiment of this aspect provides a multi-intelligent reflector-assisted NOMA system uplink transmission transposition, including:

[0149] Acquisition module: used to obtain system parameters of the NOMA system and user parameters in the system;

[0150] Clustering module: used to cluster users according to the gain of the direct channel, and obtain a clustering result in which each subcarrier schedules a central user and an edge user;

[0151] Calculation module: used to obtain the total received signal expression at the base station and the signal to interference and noise ratio expression of each user based on the acquired parameters and clustering results;

[0152] Optimization module: It is used to optimize the transmit power and phase offset according to the obtained expression using a preset optimization method to obtain the optimal phase offset, and use the relationship between the transmit power and the phase offset to obtain the optimal solution for the total transmit power of the NOMA system.

[0153] Embodiment 4:

[0154] An embodiment of the present invention provides a NOMA system uplink transmission system assisted by multiple intelligent reflectors, including a processor and a storage medium;

[0155] The storage medium is used to store instructions;

[0156] The processor is used to operate according to the instructions to execute the steps of the method described in embodiment 1.

[0157] Embodiment No:

[0158] An embodiment of the present invention further provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the method described in the first embodiment are implemented.

[0159] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0160] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0161] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0162] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0163] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the technical principles of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A NOMA system uplink transmission method assisted by multiple intelligent reflectors, characterized in that: include: Obtain the system parameters of the NOMA system and the user parameters in the system; The users are clustered according to the gain of the direct channel, and a clustering result is obtained in which one central user and one edge user are scheduled for each subcarrier; Based on the acquired parameters and clustering results, the total received signal expression at the base station and the signal-to-interference-noise ratio expression of each user are obtained; According to the obtained expression, the transmit power and phase offset are optimized by using the preset optimization method to obtain the optimal phase offset, and the optimal solution of the total transmit power of the NOMA system is obtained by using the relationship between the transmit power and the phase offset; Wherein, the preset optimization method includes: Under the premise of meeting the minimum transmission rate requirements of each user, an optimization model P1 of transmission power and phase offset is established. The optimization goal is to minimize the total transmission power of the NOMA system, and the optimization variables are the transmission power of each user and the phase offset of the smart reflection surface. The optimization model P1 is expressed by the following formula: (1) In C,i represents the energy allocation coefficient of central user i, β E,j represents the energy allocation coefficient of edge user j, γ C,i represents the signal-to-interference-noise ratio of the central user i, γ C,i (th) represents the minimum data rate of the central user i, γ E,j represents the signal-to-interference-noise ratio of edge user j, γ E,j (th) represents the minimum data rate of edge user j, Φ j represents the phase shift matrix of the jth smart reflector, N j Indicates the number of reflective elements in each smart reflective surface, represents the nth reflection element in edge user j, n={1,2,…,N j }, K represents the number of edge users and the number of center users in the cell, and P represents the total transmission power of the NOMA system; When the optimization model P1 takes the optimal value, the constraint condition on the minimum rate requirement in the optimization model P1 takes the equal sign, and the optimization model P1 is converted into the pure phase shift optimization model P2; wherein, the conversion of the optimization model P1 into the pure phase shift optimization model P2 includes: When the optimization model P1 obtains the optimal solution, the constraint conditions 1 and 2 regarding the minimum rate requirement are equal, and the transmission power required by the cell edge users and the center users is obtained. The transmission power required by the cell edge users β E,j 2 for: (2) represents the noise power, represents the channel coefficient from edge user j to the base station, G j represents the channel coefficient from the jth RIS to the base station, represents the channel coefficient from edge user j to the smart reflection surface; The transmission power required by the user in the cell center β C,i 2 for: (3) In C,i represents the channel coefficient from the central user i to the base station; Substituting equations (2) and (3) into the objective function of the optimization model P1, the total transmit power is: The optimization model P2 of pure phase shift is expressed by the following formula: The signal-to-interference-to-noise ratio expression of each user is optimized, and the optimization model P2 of pure phase shift is transformed into the optimization model P3; wherein the optimization model P3 is expressed by the following formula: (6) Represents vector g j The conjugate transpose of j and g j It is expressed by the following formula: Solve the optimization model P3 to obtain the closed-form solution of the optimal phase offset, and use the relationship between the transmit power and the phase offset to obtain the optimal solution of the total transmit power of the system; The closed-form solution of the optimal phase shift is expressed by the following formula: (8) In [g j ] n Represents vector g j The optimal phase shift for the nth element of is: The relationship between transmit power and phase shift is used to obtain the optimal solution for the total transmit power of the system.

2. The NOMA system uplink transmission method assisted by multiple intelligent reflectors according to claim 1 is characterized in that: The clustering of users according to the gains of the direct channels includes: Find the central user and edge user with the largest channel difference and match them with channel 1; Delete the two matched users, select the central user and the edge user with the largest difference from the remaining users, and match them to channel 2; The central users and the marginal users are assigned one by one in turn until all users have completed the assignment.

3. A multi-intelligent reflector-assisted NOMA system uplink transmission device based on the multi-intelligent reflector-assisted NOMA system uplink transmission method according to claim 1, characterized in that: include: Acquisition module: used to obtain system parameters of the NOMA system and user parameters in the system; Clustering module: used to cluster users according to the gain of the direct channel, scheduling one central user and one IRS-assisted edge user per subcarrier; Calculation module: used to obtain the total received signal expression at the base station and the signal to interference and noise ratio expression of each user based on the acquired parameters and clustering results; Optimization module: It is used to optimize the transmit power and phase offset according to the obtained expression using a preset optimization method to obtain the optimal phase offset, and use the relationship between the transmit power and the phase offset to obtain the optimal solution for the total transmit power of the NOMA system.

4. A NOMA system uplink transmission system assisted by multiple intelligent reflectors, characterized in that: including processor and storage medium; The storage medium is used to store instructions; The processor is used to operate according to the instructions to execute the steps of the method according to any one of claims 1 to 2.

5. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are implemented.

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