A game theory-based NOMA-D2D mode selection and power allocation method, system and storage medium
By constructing a potential game process based on game theory and using particle swarm optimization to optimize NOMA-D2D mode selection and power allocation, the problem of uneven user communication rates in cellular networks is solved, and the system spectrum utilization and user transmission quality are improved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- JILIN UNIVERSITY
- Filing Date
- 2023-05-08
- Publication Date
- 2026-07-24
AI Technical Summary
In NOMA-D2D based cellular networks, existing technologies struggle to effectively address the imbalance in user communication rates under different channel conditions, resulting in low system spectrum resource utilization, poor fairness among users, and difficulty in meeting the communication needs of different users.
A game theory-based approach is adopted to construct a potential game process. The communication mode selection and power allocation of D2D users are optimized through particle swarm optimization, which is transformed into a convex problem for solution, ensuring that the communication needs of user equipment in the system are met.
While making full use of system channel resources, it improves the sum rate of user equipment within the system, enhances the transmission quality of system users, and achieves fairness among users and maximizes spectrum utilization.
Smart Images
Figure CN116761189B_ABST
Abstract
Description
Technical Field
[0001] This invention belongs to the field of communication technology, and in particular relates to a NOMA-D2D mode selection and power allocation method, system and storage medium based on game theory. Background Technology
[0002] With the emergence of scenarios such as the Internet of Things (IoT), intelligent connected transportation, and smart cities, the number of mobile terminal devices in these scenarios has surged, leading to increased demands on user device speed, latency, and network capacity. To address the continuously growing demands for network communication, researchers both domestically and internationally are constantly exploring new network architectures and communication technologies. D2D communication and NOMA technologies are both considered important technologies capable of effectively alleviating the pressure on wireless networks.
[0003] D2D technology is one of the key technologies in 5G. When using D2D technology for communication, users do not need to rely on base stations for relaying. They can share resources and information by reusing the spectrum resources of cellular users in the system. This method can provide users with interference-controlled, stable, and reliable services. Using D2D technology can not only improve the system's transmission rate and spectrum utilization, but also reduce communication latency and provide stable and reliable service quality. NOMA technology encodes the signals of each user at the transmitting end in a non-orthogonal superposition and then transmits them. At the receiving end, it uses Successive Interference Cancellation (SIC) technology to eliminate artificially introduced interference and achieve correct decoding. The use of NOMA technology can realize a new multiple access power dimension while ensuring user needs and service quality. It can utilize the system's spectrum resources more efficiently and improve the system's sum rate. Furthermore, NOMA technology can be used in scenarios with user overload and has the potential to solve large-scale access problems. Both of these technologies can effectively alleviate spectrum resource pressure in the system. Combining D2D communication technology with NOMA technology can better solve the fairness problem between users, achieve the goal of maximizing system throughput, improve the spectrum utilization of the communication system, and expand the coverage of a single cell.
[0004] In NOMA-based D2D cellular networks, the introduction of NOMA introduces coupled resource management problems, and the use of NOMA technology has drastically different impacts on two types of users. For example, users with better channel conditions prefer NOMA technology because they can achieve higher personal data rates compared to OMA technology. However, for users with poorer channel conditions, the communication rate using NOMA technology may be lower than that using OMA technology. Therefore, it is crucial to adopt appropriate schemes for selecting communication modes and allocating power coefficients for D2D users. Summary of the Invention
[0005] The main objective of this invention is to overcome the shortcomings and deficiencies of the prior art and provide a NOMA-D2D mode selection and power allocation method, system, and storage medium based on game theory. While making full use of system channel resources, it can meet the communication needs of different users, effectively improve the sum rate of user equipment in the system, and enhance the transmission quality of system users.
[0006] According to one aspect of the present invention, a game theory-based NOMA-D2D mode selection and power allocation method is provided, the method comprising the following steps: S101: In a cellular network based on NOMA-D2D communication, a system model including base stations, D2D users and cellular users is constructed, and the communication mode of the D2D users is initialized, the communication mode including multiplexing mode and NOMA mode; S102: Based on the constructed system model and combined with the channel fading model between the user and the base station, calculate the interference experienced by the user in the system, and then obtain the signal-to-interference-plus-noise ratio and the user's rate. With the goal of maximizing the system and user rates, establish an optimization problem. S103: Based on the established optimization problem, the D2D user communication mode selection problem is constructed as a potential game process, and the communication mode of the D2D user is updated in each iteration; S104: Based on the obtained communication patterns of D2D users, for D2D users who have completed pattern selection, the non-convex fractional optimization problem is transformed into a convex problem, and the particle swarm optimization algorithm is used to solve it. S105: Repeat S103 and S104 iteratively until convergence or the maximum number of iterations is reached to find the optimal communication mode and the optimal power allocation ratio for D2D users.
[0007] Preferably, step S101 specifically includes: S1011: In the system model, define the D2D user set D, the cellular user set C, and the subcarrier set K, where a D2D user pair consists of one transmitter and two receivers; S1012: When a D2D user selects a communication mode, if the user selects the multiplexing mode, the D2D user directly reuses the cellular user's channel for communication; if the user selects the NOMA mode, the user uses NOMA technology to reuse the cellular user's channel for communication. S1013: Definition Select factors for D2D user mode when When D2D users select NOMA mode for communication; when At that time, D2D users select multiplexing mode for communication.
[0008] Preferably, in step S102, by combining the channel fading model between the user and the base station, the signal-to-interference-plus-noise ratio (SINR) of the D2D user equipment under different modes and the user's communication rate are calculated to establish an optimization problem, specifically including: S1021: For cellular users in the network, the interference they experience from other cellular users within the system is: in This indicates that the assigned intra-group channel gain is less than the user's cellular user set. The interference it receives from D2D users within the group is in, This represents the set of D2D users whose channel gain within the group is less than that of the user; thus, the signal-to-noise ratio of the cellular user is obtained.
[0009] S1022: For D2D users operating in multiplexing mode in the network, they are subject to interference from cellular users within the same group, intra-group interference, and inter-group interference. The various interferences at the D2D user receiver are as follows: Therefore, the signal-to-noise ratio of D2D users operating in multiplexing mode is obtained as follows:
[0010] S1023: For D2D users operating in NOMA mode, the inter-group interference at the user's receiver is: Therefore, the signal-to-noise ratio for D2D users operating in NOMA mode is:
[0011] S1024: Based on the signal-to-noise ratio experienced by each user in the system, the data rate of cellular users within the network is obtained as follows: The rate of D2D users working in reuse mode is: And the rate for D2D users in NOMA mode is:
[0012] Wherein, SINR_u2 is the signal-to-noise ratio of another D2D user operating in multiplexing mode; SINR_i2 is the signal-to-noise ratio of another D2D user operating in NOMA mode; S1025: The optimization problem is defined as follows:
[0013]
[0014] Among them, C1 guarantees that each user selects only one mode; C2 constrains that there can be at most df users in each subcarrier; C3 guarantees that there can be at most one multiplexing mode D2D user in each group; C4 and C5 guarantee the minimum transmission rate for cellular users and D2D users in the system; C6 and C7 constrain the non-negativity of power and its upper bound; C8 and C9 constrain the decoding order of D2D users; C 10 Representative model selection decision; Q u Q i This represents the difference between the signal-to-noise ratio (SNR) of the first receiver and the SNR of the second receiver.
[0015] Preferably, in step S1025, during decoding, the signal-to-noise ratio (SNR) of the first receiver in the group needs to be greater than that of the second receiver, specifically:
[0016] Among them, P D Indicates the transmit power of D2D users. This represents the power allocation factor for D2D users. This represents the channel gain coefficient of the D2D user receiver, and N0 is additive white Gaussian noise.
[0017] Preferably, in step S103, the step of constructing the user communication mode selection as a potential game process is as follows: For each D2D device in the system model, D i When the communication patterns of other D2D users operating on the same channel within the system are already given... When a user selects a communication mode with the goal of maximizing their own speed, this mode selection problem can be represented as: The choice of communication mode is constructed as a game. N represents the participants in the game, i.e., the D2D terminal devices within the system; D i The policy space, i.e., the communication patterns; R i The rate function representing the participants.
[0018] Preferably, the specific steps of power allocation in step S104 are as follows: S1041: The optimization problem for power allocation to D2D users within the system is as follows:
[0019]
[0020] Using the formula log2(1+SINR)≥blog2SINR+C, the problem is transformed into a convex problem, and then a power allocation process is performed.
[0021] S1042: The existing power allocation optimization problem is transformed to obtain a new lower bound for the objective function: in,
[0022] S1043: The optimization problem after transformation is expressed as:
[0023]
[0024] in, This is the power conversion factor.
[0025] Preferably, in step S1043, the following steps are set: Rearranging the function yields two results about and The concave function transforms the optimization problem into a convex optimization problem.
[0026] According to another aspect of the present invention, the present invention also provides a game theory-based NOMA-D2D mode selection and power allocation system, the system comprising: The first construction module is used to construct a system model containing base stations, D2D users and cellular users in a cellular network based on NOMA-D2D communication, and to initialize the communication mode of the D2D users, wherein the communication mode includes multiplexing mode and NOMA mode. The second construction module is used to calculate the interference experienced by users in the system based on the constructed system model and the channel fading model between users and base stations, thereby obtaining the signal-to-interference-plus-noise ratio and the user's rate, and to establish an optimization problem with the goal of maximizing the system and user rates. The first conversion module is used to construct the D2D user communication mode selection problem into a potential game process based on the established optimization problem, and to update the communication mode of D2D users in each iteration. The second conversion module is used to convert the non-convex fractional optimization problem into a convex problem for D2D users who have completed mode selection, based on the obtained communication mode of the D2D users, and then solve it using the particle swarm optimization algorithm. The iterative calculation module is used to repeatedly perform the construction and solution process until convergence or the maximum number of iterations is reached, in order to determine the optimal communication mode and the optimal power allocation ratio for D2D users.
[0027] According to another aspect of the present invention, the present invention also provides a game theory-based NOMA-D2D mode selection and power allocation system, the system comprising: a processor and a memory, the memory storing computer-executable instructions, which, when executed by the processor, implement the above-described method steps.
[0028] According to another aspect of the present invention, the present invention also provides a computer-readable storage medium storing computer-executable instructions that, when executed by a processor, implement the above-described method steps.
[0029] Beneficial effects: The method provided by this invention can fully utilize system channel resources while meeting the communication needs of different users, and can also effectively improve the sum and speed of user equipment in the system and enhance the transmission quality of system users.
[0030] The features and advantages of the present invention will become clear from the following accompanying drawings and a detailed description of specific embodiments thereof. Attached Figure Description
[0031] Figure 1 This is a schematic diagram of a cellular network system model based on NOMA-D2D; Figure 2 This is a schematic diagram of the NOMA-D2D mode selection and power allocation method based on game theory; Figure 3 This is a schematic diagram of a NOMA-D2D mode selection and power allocation system based on game theory. Detailed Implementation
[0032] The technical solutions of the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings. Obviously, the described embodiments are only some embodiments of the present invention, and not all embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of the present invention.
[0033] Example 1
[0034] refer to Figure 1 and Figure 2 This embodiment provides a game theory-based NOMA-D2D mode selection and power allocation method, which includes the following steps: S101: In a cellular network based on NOMA-D2D communication, a system model including base stations, D2D users and cellular users is constructed, and the communication mode of the D2D users is initialized, the communication mode including multiplexing mode and NOMA mode; S102: Based on the constructed system model and combined with the channel fading model between the user and the base station, calculate the interference experienced by the user in the system, and then obtain the signal-to-interference-plus-noise ratio and the user's rate. With the goal of maximizing the system and user rates, establish an optimization problem. S103: Based on the established optimization problem, the D2D user communication mode selection problem is constructed as a potential game process, and the communication mode of the D2D user is updated in each iteration; S104: Based on the obtained communication patterns of D2D users, for D2D users who have completed pattern selection, the non-convex fractional optimization problem is transformed into a convex problem, and the particle swarm optimization algorithm is used to solve it. S105: Repeat S103 and S104 iteratively until convergence or the maximum number of iterations is reached to find the optimal communication mode and the optimal power allocation ratio for D2D users.
[0035] In this embodiment, while making full use of system channel resources, the communication needs of different users can be met, effectively improving the sum rate of user equipment within the system and enhancing the transmission quality of system users.
[0036] Preferably, step S101 specifically includes: S1011: In the system model, define the D2D user set D, the cellular user set C, and the subcarrier set K, where a D2D user pair consists of one transmitter and two receivers; S1012: When a D2D user selects a communication mode, if the user selects the multiplexing mode, the D2D user directly reuses the cellular user's channel for communication; if the user selects the NOMA mode, the user uses NOMA technology to reuse the cellular user's channel for communication. S1013: Definition Select factors for D2D user mode when When D2D users select NOMA mode for communication; when At that time, D2D users select multiplexing mode for communication.
[0037] Preferably, in step S102, by combining the channel fading model between the user and the base station, the signal-to-interference-plus-noise ratio (SINR) of the D2D user equipment under different modes and the user's communication rate are calculated to establish an optimization problem, specifically including: S1021: For cellular users in the network, the interference they experience from other cellular users within the system is: in This indicates that the assigned intra-group channel gain is less than the user's cellular user set. The interference it receives from D2D users within the group is in, This represents the set of D2D users whose channel gain within the group is less than that of the user; thus, the signal-to-noise ratio of the cellular user is obtained.
[0038] S1022: For D2D users operating in multiplexing mode in the network, they are subject to interference from cellular users within the same group, intra-group interference, and inter-group interference. The various interferences at the D2D user receiver are as follows: Therefore, the signal-to-noise ratio of D2D users operating in multiplexing mode is obtained as follows:
[0039] S1023: For D2D users operating in NOMA mode, the inter-group interference at the user's receiver is: Therefore, the signal-to-noise ratio for D2D users operating in NOMA mode is:
[0040] S1024: Based on the signal-to-noise ratio experienced by each user in the system, the data rate of cellular users within the network is obtained as follows: The rate of D2D users working in reuse mode is: And the rate for D2D users in NOMA mode is:
[0041] Wherein, SINR_u2 is the signal-to-noise ratio of another D2D user operating in multiplexing mode; SINR_i2 is the signal-to-noise ratio of another D2D user operating in NOMA mode; S1025: The optimization problem is as follows:
[0042]
[0043] Among them, C1 guarantees that each user selects only one mode; C2 constrains that there can be at most df users in each subcarrier; C3 guarantees that there can be at most one multiplexing mode D2D user in each group; C4 and C5 guarantee the minimum transmission rate for cellular users and D2D users in the system; C6 and C7 constrain the non-negativity of power and its upper bound; C8 and C9 constrain the decoding order of D2D users; C 10 Representative model selection decision; Q u Q i This represents the difference between the signal-to-noise ratio (SNR) of the first receiver and the SNR of the second receiver.
[0044] Preferably, in step S1025, during decoding, the signal-to-noise ratio (SNR) of the first receiver in the group needs to be greater than that of the second receiver, specifically:
[0045] Among them, P D Indicates the transmit power of D2D users. This represents the power allocation factor for D2D users. This represents the channel gain coefficient of the D2D user receiver, and N0 is additive white Gaussian noise.
[0046] Preferably, in step S103, the step of constructing the user communication mode selection as a potential game process is as follows: For each D2D device in the system model, D i When the communication patterns of other D2D users operating on the same channel within the system are already given... When a user selects a communication mode with the goal of maximizing their own speed, this mode selection problem can be represented as: The choice of communication mode is constructed as a game. N represents the participants in the game, i.e., the D2D terminal devices within the system; D i The policy space, i.e., the communication patterns; R i The rate function represents the participant.
[0047] Preferably, the specific steps of power allocation in step S104 are as follows: S1041: The optimization problem for power allocation to D2D users within the system is as follows:
[0048]
[0049] Using the formula log2(1+SINR)≥blog2SINR+C, the problem is transformed into a convex problem, and then a power allocation process is performed.
[0050] S1042: The existing power allocation optimization problem is transformed to obtain a new lower bound for the objective function: in,
[0051] S1043: The optimization problem after transformation is expressed as:
[0052]
[0053] in, This is the power conversion factor.
[0054] Preferably, in step S1043, the following steps are set: Rearranging the function yields two results about and The concave function transforms the optimization problem into a convex optimization problem.
[0055] In this embodiment, a cellular network system model based on NOMA-D2D is first constructed. D2D user communication modes are divided into D2D multiplexing mode communication and uplink NOMA mode communication, and communication models are constructed for each. Considering the characteristics of each user, the interference experienced by each user is analyzed. Using Shannon's formula, the transmission rate of each user is obtained, and an optimization problem is constructed with the goal of maximizing the system's overall speed. Analysis of the optimization problem reveals that in NOMA mode, some users with poor channel conditions may not be able to achieve their maximum speed after accessing the channel; in multiplexing mode, channel resources are limited, and multiple user access may cause congestion, thus affecting the system's communication quality. To address these issues, a potential game process is constructed to select the communication mode for D2D users within the system. By transforming the original problem, power allocation is performed on users in the communication system, and the optimal mode selection and power allocation results are obtained through iterative iteration. This embodiment's method, on the one hand, fully utilizes system channel resources while meeting the communication needs of different users; on the other hand, it effectively improves the overall speed of user equipment within the system, thereby enhancing the system's transmission quality.
[0056] Example 2
[0057] Figure 3 This is a schematic diagram of a NOMA-D2D mode selection and power allocation system based on game theory. (Example) Figure 3 As shown, this embodiment provides a game theory-based NOMA-D2D mode selection and power allocation system, the system comprising: The first construction module is used to construct a system model containing base stations, D2D users and cellular users in a cellular network based on NOMA-D2D communication, and to initialize the communication mode of the D2D users, wherein the communication mode includes multiplexing mode and NOMA mode. The second construction module is used to calculate the interference experienced by users in the system based on the constructed system model and the channel fading model between users and base stations, thereby obtaining the signal-to-interference-plus-noise ratio and the user's rate, and to establish an optimization problem with the goal of maximizing the system and user rates. The first conversion module is used to construct the D2D user communication mode selection problem into a potential game process based on the established optimization problem, and to update the communication mode of D2D users in each iteration. The second conversion module is used to convert the non-convex fractional optimization problem into a convex problem for D2D users who have completed mode selection, based on the obtained communication mode of the D2D users, and then solve it using the particle swarm optimization algorithm. The iterative calculation module is used to repeatedly perform the construction and solution process until convergence or the maximum number of iterations is reached, in order to determine the optimal communication mode and the optimal power allocation ratio for D2D users.
[0058] The specific implementation process of the functions implemented by each module in this embodiment 2 is the same as the implementation process of each step in embodiment 1, and will not be repeated here.
[0059] Example 3
[0060] According to another aspect of the present invention, this embodiment provides a NOMA-D2D mode selection and power allocation system based on game theory. The system includes a processor and a memory. The memory stores computer-executable instructions. When the computer-executable instructions are executed by the processor, they implement the method steps in Embodiment 1. The specific implementation process can be referred to the implementation process of the method steps in Embodiment 1, and will not be repeated here.
[0061] Example 4
[0062] According to another aspect of the present invention, the present invention also provides a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, implement the method steps in Embodiment 1. The specific implementation process can be referred to the implementation process of the method steps in Embodiment 1, and will not be repeated here.
[0063] The above description is only a preferred embodiment of the present invention and does not limit the patent scope of the present invention. All equivalent structural transformations made under the concept of the present invention using the contents of the present invention specification and drawings, or direct / indirect applications in other related technical fields, are included within the patent protection scope of the present invention.
Claims
1. A game theory-based NOMA-D2D mode selection and power allocation method, characterized in that, The method includes the following steps: S101: In a cellular network based on NOMA-D2D communication, a system model including base stations, D2D users and cellular users is constructed, and the communication mode of the D2D users is initialized, the communication mode including multiplexing mode and NOMA mode; S102: Based on the constructed system model and combined with the channel fading model between the user and the base station, calculate the interference experienced by the user in the system, and then obtain the signal-to-interference-plus-noise ratio and the user's rate. With the goal of maximizing the system and user rates, establish an optimization problem. S103: Based on the established optimization problem, the D2D user communication mode selection problem is constructed as a potential game process, and the communication mode of the D2D user is updated in each iteration; S104: Based on the obtained communication patterns of D2D users, for D2D users who have completed pattern selection, the non-convex fractional optimization problem is transformed into a convex problem, and the particle swarm optimization algorithm is used to solve it. S105: Repeat S103 and S104 iteratively until convergence or the maximum number of iterations is reached to find the optimal communication mode and the optimal power allocation ratio for D2D users. In step S102, combining the channel fading model between the user and the base station, the signal-to-interference-noise ratio (SINR) and the user's communication rate of the D2D user equipment under different modes are calculated to establish an optimization problem, specifically including: S1021: For cellular users in the network, the interference they experience from other cellular users within the system is: in This indicates that the assigned intra-group channel gain is less than the user's cellular user set. The interference it receives from D2D users within the group is in, This represents the set of D2D users whose channel gain within the group is less than that of the user; thus, the signal-to-noise ratio of the cellular user is obtained. S1022: For D2D users operating in multiplexing mode in the network, they are subject to interference from cellular users within the same group, intra-group interference, and inter-group interference. The various interferences at the D2D user receiver are as follows: Therefore, the signal-to-noise ratio of D2D users operating in multiplexing mode is obtained as follows: S1023: For D2D users operating in NOMA mode, the inter-group interference at the user's receiver is: Therefore, the signal-to-noise ratio for D2D users operating in NOMA mode is: S1024: Based on the signal-to-noise ratio experienced by each user in the system, the data rate of cellular users within the network is obtained as follows: The rate of D2D users working in reuse mode is: And the rate for D2D users in NOMA mode is: Wherein, SINR_u2 is the signal-to-noise ratio of another D2D user operating in multiplexing mode; SINR_i2 is the signal-to-noise ratio of another D2D user operating in NOMA mode; S1025: The optimization problem is as follows: Among them, C1 guarantees that each user selects only one mode; C2 constrains that there can be at most df users in each subcarrier; C3 guarantees that there can be at most one multiplexing mode D2D user in each group; C4 and C5 guarantee the minimum transmission rate for cellular users and D2D users in the system; C6 and C7 constrain the non-negativity of power and its upper bound; C8 and C9 constrain the decoding order of D2D users; C 10 Representative model selection decision; Q u、 Q i This represents the difference between the signal-to-noise ratio (SNR) of the first receiver and the SNR of the second receiver.
2. The method according to claim 1, characterized in that, Step S101 specifically includes: S1011: In the system model, define the D2D user set D, the cellular user set C, and the subcarrier set K, where a D2D user pair consists of one transmitter and two receivers; S1012: When a D2D user selects a communication mode, if the user selects the multiplexing mode, the D2D user directly reuses the cellular user's channel for communication; if the user selects the NOMA mode, the user uses NOMA technology to reuse the cellular user's channel for communication. S1013: Definition Select factors for D2D user mode when When D2D users select NOMA mode for communication; when At that time, D2D users select multiplexing mode for communication.
3. The method according to claim 2, characterized in that, In step S1025, during decoding, the signal-to-noise ratio (SNR) of the first receiver in the group needs to be greater than that of the second receiver. Specifically: Among them, P D Indicates the transmit power of D2D users. This represents the power allocation factor for D2D users. This represents the channel gain coefficient of the D2D user receiver, and N0 is additive white Gaussian noise.
4. The method according to claim 1, characterized in that, In step S103, the steps for constructing the user communication mode selection as a potential game process are as follows: For each D2D device in the system model, D i When the communication patterns of other D2D users operating on the same channel within the system are already given... When a user selects a communication mode with the goal of maximizing their own speed, this mode selection problem can be represented as: The choice of communication mode is constructed as a game. N represents the participants in the game, i.e., the D2D terminal devices within the system; D i The policy space, i.e., the communication patterns; R i The rate function represents the participant.
5. The method according to claim 1, characterized in that, In step S104, the specific steps of power allocation are as follows: S1041: The optimization problem for power allocation to D2D users within the system is as follows: Using the formula log2(1+SINR)≥blog2SINR+C, the problem is transformed into a convex problem, and then a power allocation process is performed. S1042: The existing power allocation optimization problem is transformed to obtain a new lower bound for the objective function: in, S1043: The optimization problem after transformation is expressed as: in, This is the power conversion factor.
6. The method according to claim 5, characterized in that, In step S1043, set Rearranging the function yields two related... and The concave function transforms the optimization problem into a convex optimization problem.
7. A game theory-based NOMA-D2D mode selection and power allocation system, characterized in that, The system includes: The first construction module is used to construct a system model containing base stations, D2D users and cellular users in a cellular network based on NOMA-D2D communication, and to initialize the communication mode of the D2D users, wherein the communication mode includes multiplexing mode and NOMA mode. The second construction module is used to calculate the interference experienced by users in the system based on the constructed system model and the channel fading model between users and base stations, thereby obtaining the signal-to-interference-plus-noise ratio and the user's rate, and to establish an optimization problem with the goal of maximizing the system and user rates. The first conversion module is used to construct the D2D user communication mode selection problem into a potential game process based on the established optimization problem, and to update the communication mode of D2D users in each iteration. The second conversion module is used to convert the non-convex fractional optimization problem into a convex problem for D2D users who have completed mode selection, based on the obtained communication mode of the D2D users, and then solve it using the particle swarm optimization algorithm. The iterative calculation module is used to repeatedly iterate the construction and solution process until convergence or the maximum number of iterations is reached, to find the optimal communication mode and the optimal power allocation ratio for D2D users. Among them, combining the channel fading model between users and base stations, the signal-to-interference-noise ratio (SINR) and user communication rate of D2D user equipment are calculated under different modes, and an optimization problem is established, which specifically includes: S1021: For cellular users in the network, the interference they experience from other cellular users within the system is: in This indicates that the assigned intra-group channel gain is less than the user's cellular user set. The interference it receives from D2D users within the group is in, This represents the set of D2D users whose channel gain within the group is less than that of the user; thus, the signal-to-noise ratio of the cellular user is obtained. S1022: For D2D users operating in multiplexing mode in the network, they are subject to interference from cellular users within the same group, intra-group interference, and inter-group interference. The various interferences at the D2D user receiver are as follows: Therefore, the signal-to-noise ratio of D2D users operating in multiplexing mode is obtained as follows: S1023: For D2D users operating in NOMA mode, the inter-group interference at the user's receiver is: Therefore, the signal-to-noise ratio for D2D users operating in NOMA mode is: S1024: Based on the signal-to-noise ratio experienced by each user in the system, the data rate of cellular users within the network is obtained as follows: The rate of D2D users working in reuse mode is: And the rate for D2D users in NOMA mode is: Wherein, SINR_u2 is the signal-to-noise ratio of another D2D user operating in multiplexing mode; SINR_i2 is the signal-to-noise ratio of another D2D user operating in NOMA mode; S1025: The optimization problem is as follows: Among them, C1 guarantees that each user selects only one mode; C2 constrains that there can be at most df users in each subcarrier; C3 guarantees that there can be at most one multiplexing mode D2D user in each group; C4 and C5 guarantee the minimum transmission rate for cellular users and D2D users in the system; C6 and C7 constrain the non-negativity of power and its upper bound; C8 and C9 constrain the decoding order of D2D users; C 10 Representative model selection decision; Q u、 Q i This represents the difference between the signal-to-noise ratio (SNR) of the first receiver and the SNR of the second receiver.
8. A game theory-based NOMA-D2D mode selection and power allocation system, characterized in that, The system includes a processor and a memory, the memory storing computer-executable instructions, which, when executed by the processor, implement the method as described in any one of claims 1-6.
9. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions that, when executed by a processor, implement the method as described in any one of claims 1-6.