Wireless communication system and communication method based on AFSS-assisted ground network

Abstract

The present application relates to a wireless communication system and a communication method based on an AFSS-assisted ground network. The system provides a controller for constructing an AFSS strategy set for the ground network, and based on the AFSS strategy set, constructs an objective function for minimizing the energy consumption of transmitting communication tasks to N user terminals by the base station based on AFSS assistance when the transmission strategy is optional, and controls the base station to adjust the transmission strategy of transmitting communication tasks to N user terminals based on the target solution obtained by solving the function. The system and its method can dynamically select different transmission strategies and change the AFSS voltage value in the transmission of communication tasks, so that the transmission efficiency of the communication tasks of the ground network can be improved while minimizing the energy consumption of the base station transmitting communication tasks to N user terminals based on AFSS assistance, and meet different spectrum requirements.

Description

Technical Field

[0001] The embodiments of the present application relate to the field of wireless communication technology, and in particular, to a wireless communication system and a communication method thereof based on an AFSS-assisted ground network. Background Art

[0002] With the explosive growth of mobile data and mobile users, communication networks have higher and higher requirements for spectrum utilization and interference suppression. Passive frequency selective surfaces (FSS) have become an important metasurface after intelligent reflective surfaces (IRS) due to their absorption, reflection and transmission characteristics within a specific frequency range, but they have the problem of adapting to dynamic network environments. Active frequency selective surfaces (AFSS) can solve the problem that traditional passive FSS cannot adapt to dynamic network environments by embedding electrical components to adjust their own frequencies.

[0003] Existing AFSS research mainly focuses on the design of AFSS structure and antenna design, but lacks research on optimization strategies in multi-user and multi-spectrum environments, and fails to fully utilize its tuning capabilities to optimize communication quality while reducing energy consumption. Especially in high-density user scenarios, the lack of intelligent adjustment mechanisms will lead to uneven distribution of spectrum resources, affecting overall communication efficiency. Summary of the invention

[0004] The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.

[0005] The main purpose of the embodiments of the present disclosure is to propose a wireless communication system and a communication method based on an AFSS-assisted ground network, which can reduce the overall energy consumption of communication tasks by adjusting the AFSS strategy selection to meet different spectrum requirements.

[0006] A first aspect of an embodiment of the present application provides a wireless communication system based on an AFSS-assisted ground network, the system comprising:

[0007] A ground network, the ground network comprising a base station and N user terminals in different frequency spectra, the base station being communicatively connected to the N user terminals, and the communication task of the base station being based on tuning-assisted transmission to the N user terminals using an active frequency selective surface AFSS; N is a positive integer greater than 1;

[0008] A controller is communicatively connected to the ground network, and includes a relationship building module, a function building module, a calculation and solution module, and an information control module, wherein:

[0009] The relationship building module is used to build an AFSS strategy set; the AFSS strategy set includes multiple transmission strategies, each of which includes a corresponding relationship between a set of AFSS voltages and AFSS transmission coefficients at multiple different resonant frequencies;

[0010] The function construction module is used to construct, according to the AFSS strategy set, an objective function for minimizing energy consumption of transmitting the communication task to the N user terminals by the base station when the transmission strategy is optional;

[0011] The calculation and solution module is used to solve the objective function to obtain the target solution;

[0012] The information control module is used to control the base station to adjust the transmission strategy of transmitting the communication task to the N user terminals according to the target solution.

[0013] The wireless communication system based on the AFSS-assisted ground network provided by the present application has at least the following beneficial effects:

[0014] For the AFSS-assisted ground network, this system provides a controller, through which an AFSS strategy set is constructed; based on the AFSS strategy set, an objective function is constructed to minimize the energy consumption of the base station transmitting the communication task to N user terminals based on the AFSS assistance when the transmission strategy is optional; according to the target solution obtained by solving the function, the base station is controlled to adjust the transmission strategy of transmitting the communication task to N user terminals. This system can dynamically select different transmission strategies and change the AFSS voltage value during the transmission process, so that the transmission efficiency of the ground network's communication tasks can be improved while minimizing the energy consumption of the base station transmitting the communication task to N user terminals based on the AFSS assistance, and meet different spectrum requirements.

[0015] A second aspect of an embodiment of the present application proposes a wireless communication method based on an AFSS-assisted ground network, which is used for a controller, wherein the controller is communicatively connected to a ground network, wherein the ground network includes a base station and N user terminals in different frequency spectra, wherein the base station is communicatively connected to the N user terminals, and the communication task of the base station is transmitted to the N user terminals after being tuned by an active frequency selective surface AFSS, where N is a positive integer greater than 1; the method comprises:

[0016] Constructing an AFSS strategy set; the AFSS strategy set includes a plurality of transmission strategies, each of which includes a set of corresponding relationships between AFSS voltages and AFSS transmission coefficients at a plurality of different resonant frequencies;

[0017] According to the AFSS strategy set, constructing an objective function for minimizing energy consumption of transmitting the communication task to the N user terminals by the base station when the transmission strategy is optional;

[0018] Solving the objective function to obtain an objective solution;

[0019] According to the target solution, the base station is controlled to adjust the transmission strategy for transmitting the communication task to the N user terminals.

[0020] A third aspect of an embodiment of the present application proposes an electronic device, comprising at least one controller and a memory for communicating with the at least one controller; the memory stores instructions that can be executed by the at least one controller, and the instructions are executed by the at least one controller to enable the at least one controller to execute the wireless communication method based on the AFSS-assisted ground network as described above.

[0021] A fourth aspect of an embodiment of the present application proposes a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the wireless communication method based on the AFSS-assisted ground network as described above.

[0022] It can be understood that the beneficial effects of the second to fourth aspects compared with the related art are the same as the beneficial effects of the first aspect compared with the related art. Please refer to the relevant description in the first aspect, and no further details will be given here. BRIEF DESCRIPTION OF THE DRAWINGS

[0023] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the embodiments or related technical descriptions will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying creative labor.

[0024] Figure 1 It is a structural block diagram of a wireless communication system based on an AFSS-assisted ground network provided by an embodiment of the present application;

[0025] Figure 2 It is a schematic diagram of the current AFSS resonant frequency and transmission coefficient provided by an embodiment of the present application;

[0026] Figure 3 is a schematic diagram of the AFSS resonant frequency and transmission coefficient provided in the experimental embodiment of the present application;

[0027] Figure 4: is a schematic diagram of energy consumption comparison between the experimental embodiment of the present application and the control method under different numbers of user terminals, wherein: Figure 4 (a) is a comparison chart of the total energy consumption of the control method under different numbers of user terminals. Figure 4 (b) shows the energy consumption of the control method under different numbers of user terminals. A comparison chart of Figure 4 (c) is the energy consumption of the control method under different numbers of user terminals. ;

[0028] Figure 5 is a schematic diagram of energy consumption comparison between the experimental embodiment of the present application and the control method under different adjustable AFSS state numbers, wherein: Figure 5 (a) is a comparison chart of the total energy consumption of the control method under different adjustable AFSS state numbers. Figure 5 (b) shows the energy consumption of the control method under different adjustable AFSS state numbers. A comparison chart of Figure 5 (c) is the energy consumption of the control method under different adjustable AFSS state numbers. ;

[0029] Figure 6 is a schematic diagram of an electronic device provided by the present application. DETAILED DESCRIPTION

[0030] In order to make the purpose, technical solution and advantages of the present application more clearly understood, the present application is further described in detail below in conjunction with the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0031] It should be noted that, although the functional modules are divided in the device schematic diagram and the logical order is shown in the flowchart, in some cases, the steps shown or described may be performed in a different order than the module division in the device or the order in the flowchart. The terms "first", "second", etc. in the specification, claims and the above drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence.

[0032] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as those commonly understood by those skilled in the art to which this application belongs. The terms used herein are only for the purpose of describing the embodiments of this application and are not intended to limit this application.

[0033] like Figure 1One embodiment of the present application provides a wireless communication system based on an AFSS-assisted ground network, including:

[0034] A ground network 1100, the ground network 1100 includes a base station 1110 and N user terminals 1120 in different frequency spectra, the base station 1110 is communicatively connected with the N user terminals 1120, and the communication task of the base station 1110 is based on the active frequency selective surface AFSS for tuning-assisted transmission to the N user terminals 1120;

[0035] A controller 1200, the controller 1200 is in communication with the ground network 1100, and the controller 1200 includes a relationship building module 1210, a function building module 1220, a calculation and solution module 1230 and an information control module 1240;

[0036] The relationship building module 1210 is used to build an AFSS strategy set; the AFSS strategy set includes multiple transmission strategies, each transmission strategy includes a set of corresponding relationships between AFSS voltages and AFSS transmission coefficients at multiple different resonant frequencies;

[0037] The function construction module 1220 is used to construct, according to the AFSS strategy set, an objective function for minimizing energy consumption of transmitting the communication task to N user terminals 1120 by the base station 1110 based on the AFSS assistance when the transmission strategy is optional;

[0038] The calculation and solution module 1230 is used to solve the objective function and obtain the target solution;

[0039] The information control module 1240 is used to control the base station 1110 to adjust the transmission strategy of transmitting communication tasks to the N user terminals 1120 according to the target solution.

[0040] Take the ground network as an example, the MISO network includes a base station and N user terminals. The MISO network uses AFSS to assist in signal tuning of the base station signal. Within the coverage of the base station, there are N user terminals that need to transmit communication tasks. In order to reduce the mutual interference of users on the same spectrum, N users are allocated to N different spectrums.

[0041] This embodiment is configured with a controller, which selects different transmission strategies for the AFSS in the process of the base station transmitting the communication task to N client terminals based on the AFSS assistance. The selection of the transmission strategy here can be defined as: the controller changes the AFSS transmission coefficient by selecting to change the AFSS voltage applied to both ends of the AFSS.

[0042] like Figure 2 Before explaining in detail, let's first introduce how to change the transmission coefficient by changing the AFSS voltage:

[0043] Here, a simple physical model is used to show the relationship between voltage and transmission coefficient, where the equivalent capacitance of the adjustable element (such as a varactor diode) in the AFSS can be expressed by the following formula:

[0044] ;

[0045] in, is the capacitance of the component, is the reference capacitance when there is no voltage, is the capacitance variation coefficient, is the voltage applied to the component.

[0046] Initial transmission coefficient of AFSS Can be with capacitor value Establish a relationship between:

[0047] ;

[0048] in, is the transmission coefficient of AFSS in the passive state, L is the inductance of the electrical component, is the capacitance of the varactor element. In summary, the relationship between voltage and AFSS transmission coefficient can be obtained:

[0049] ;

[0050] in, is the transmission coefficient when active, is the coefficient related to the capacitance change, It is the voltage applied to the adjustable element. Thus, the correlation between voltage and AFSS transmission coefficient is established. By adjusting the voltage to change the capacitance value of the adjustable element, the AFSS transmission coefficient can be adjusted.

[0051] Based on this characteristic, when there are multiple users in different spectrums in the communication environment who need to communicate, the optimal transmission strategy can be calculated to adjust the AFSS voltage to change the transmission coefficient of the AFSS, and finally improve the network communication performance.

[0052] In some embodiments, the AFSS policy set is constructed by the relationship construction module 1210 of the controller 1200. The AFSS policy set is described in detail below:

[0053] Here, it is assumed that the AFSS has S tunable AFSS voltages, and N different spectrum segments need to be considered, and these spectrum segments are all within the tunable range of the AFSS.

[0054] The set of AFSS strategies between S tunable AFSS voltages, N different resonant frequencies and AFSS transmission coefficients can be expressed as: .

[0055] Table 1 (AFSS strategy set) below shows in detail the transmission coefficient of AFSS at different AFSS voltages and different spectra:

[0056] Table 1

[0057]

[0058] In some embodiments, the target function is constructed by the function construction module 1220 of the controller 1200;

[0059] For N user terminals that need to transmit communication tasks, they are allocated to N different spectrums, and the amount of data that the N user terminals need to transmit in the communication task is set to: .

[0060] Assume that the transmission process of the communication task requires I task transmission periods to ensure that the respective data volumes of N user terminals are transmitted completely.

[0061] Assume that the vector corresponding to the transmission strategy set of N user terminals in the i-th task transmission period is expressed as: , the i-th task transmission period is one of the total I task transmission periods.

[0062] For example, according to Table 1, the resonant frequency of any user terminal is known, and N user terminals all uniformly select to Any AFSS voltage in the range and obtain the corresponding transmission coefficient of the voltage, assuming that , then the vector in the transmission strategy set =1, and to are all 0. , indicating that N user terminals use the AFSS voltage in the i-th task transmission period .

[0063] Since the task transmission rate determines the completion time of the communication task, here, according to Shannon's formula, let the nth user terminal have the transmission strategy Task transfer rate in the case of for:

[0064] ;

[0065] in . Represents the channel bandwidth allocated to the nth user terminal. represents the average transmission power of the nth user terminal communication, is the matrix of the resonant frequency of the nth user terminal. is the additive white Gaussian noise (AWGN) at the user terminal receiving point.

[0066] The set of task transmission rates of N user terminals includes: ;in Indicates The AFSS voltage of each user terminal to The total task transfer rate.

[0067] In order to further improve communication efficiency and reduce the transmission cost of communication tasks, under the condition of ensuring the amount of data required to be transmitted by the user terminal, this embodiment jointly optimizes the AFSS voltage selection and the selection of the task transmission period to minimize the energy consumption of the base station in transmitting the communication task to N user terminals.

[0068] Here the objective function is set as:

[0069] ;

[0070] Communication energy consumption of base stations Transmission energy consumption with AFSS They are as follows:

[0071] ;

[0072] ;

[0073] in, Indicates the transmission power of AFSS. is the average transmission power of the base station. is the weight value. For preset The first task in the transmission period task transfer period. For N user terminals The vector representation of the AFSS strategy set for each task transmission period, The vector representation of the AFSS strategy set corresponding to each task transmission period is: .

[0074] The constraint functions corresponding to the objective function include:

[0075] ;

[0076] ;

[0077] ;

[0078] for A vector representation of the task transfer period. is the first of N user terminals The task transmission rate of each user terminal is related to the AFSS transmission coefficient, as shown in the above Shannon solution. For the The amount of data that a user terminal needs to transmit in a communication task. For the The channel bandwidth of each user terminal. is the total channel bandwidth of N user terminals. For the The task transmission time of each user terminal. The total transmission duration of the communication task of the base station not based on AFSS-assisted tuning.

[0079] The objective function is a mixed integer optimization (MINLP) problem.

[0080] In some embodiments, the calculation solution module 1230 of the controller 1200 obtains the solution of the objective function:

[0081] This embodiment uses the deep reinforcement learning (DQN) algorithm to solve the problem.

[0082] If the DQN algorithm is not used, the greedy algorithm can also be used. However, the DQN algorithm can dynamically select the optimal AFSS voltage state according to the current communication environment, thereby optimizing multi-user and multi-spectrum communications with better results.

[0083] Here is a brief introduction to DQN:

[0084] The core idea of ​​the DQN algorithm is to approximate the Q-value function through a deep neural network. The Q-value function Q(s, a) represents the expected total reward when performing action a in state s. In traditional Q learning, the Q-value function is updated by looking up a table, while in DQN, the Q-value function is approximated by a deep neural network, and the parameters of the neural network are updated by gradient descent. The Q network inputs the current state s and outputs the Q-values ​​of all possible actions. By adjusting the neural network parameters θ, the predicted Q-value is as close to the actual Q-value as possible. Specifically, given the state s and action a, the Q-value function is expressed as Q(s, a; θ), where θ is the parameter of the neural network. DQN introduces an experience replay mechanism to store each state-action-reward-next state (s, a, r, s') quadruple experienced by the agent in the environment in a fixed-capacity memory bank D. In each update step, a small batch of samples are randomly extracted from the memory bank for training. This can break the correlation between data and improve the independence of samples. Finally, in order to stabilize the training process, DQN introduces a target network. The parameters θ⁻ of the target network are fixed and synchronized with the parameters θ of the Q network only after a certain number of steps.

[0085] According to the proposed DQN network architecture, in order to solve the solution of the objective function, the proposed state space, action space, and reward function are as follows:

[0086] The state space represents the possible state set of the environment in each time period. In the proposed algorithm, the state space consists of the remaining task amount of each user, reflecting the transmission tasks that each user still needs to complete. The state transition equation includes:

[0087] ;

[0088] in . The dimension of the state space is N.

[0089] The action space defines all possible actions that the agent can take at each time step. Specifically, the action space consists of different transmission states, each of which represents a possible transmission power configuration.

[0090] In the transmission environment proposed in this embodiment, the design of the reward function takes into account the impact of energy consumption and transmission power on the completion of the communication task. Specifically, from step i to step i+1, the agent selects the strategy that can be used in the current period from the experience pool or random sampling. The reward function is responsible for calculating the reward that can be obtained by selecting the current strategy. The reward is taken as the opposite of the energy consumption generated by the current step, so as to optimize in the direction of minimizing energy consumption. The definition of the reward function is as follows:

[0091] ;

[0092] in, Indicates the reward of the current i-th step. The communication energy consumption generated in the i-th time period Energy consumption of AFSS They are defined as:

[0093] ;

[0094] ;

[0095] In the DQN network used, the training goal of the overall network is to make all user terminals consume less energy. The transmission process of completing the communication task in fewer cases.

[0096] The wireless communication system based on the AFSS-assisted ground network provided in this embodiment has at least the following beneficial effects:

[0097] (1) For the AFSS-assisted ground network, this system provides a controller, through which an AFSS strategy set is constructed. Based on the AFSS strategy set, an objective function is constructed to minimize the energy consumption of the base station transmitting the communication task to N user terminals based on the AFSS assistance when the transmission strategy is optional. Based on the objective solution obtained by solving the function, the base station is controlled to adjust the transmission strategy of transmitting the communication task to N user terminals. This system can dynamically select different transmission strategies and change the AFSS voltage value during the communication task transmission process, so that the transmission efficiency of the communication task can be improved while minimizing the energy consumption of the base station transmitting the communication task to N user terminals based on the AFSS assistance, thereby meeting different spectrum requirements.

[0098] (2) This system introduces the deep reinforcement learning (DQN) algorithm, which can effectively solve the objective function, and then dynamically select the transmission strategy that minimizes energy consumption (i.e., the selection of AFSS voltage in different time periods), optimize multi-user and multi-band communication tasks, optimize the transmission QoS (Quality of service) of the ground system, and meet the changing spectrum requirements.

[0099] An embodiment of the present application provides a wireless communication method implemented by a wireless communication system based on an AFSS-assisted ground network, the method comprising:

[0100] Step S110, inputting the communication task to be performed into the controller;

[0101] In step S120, the controller transmits parameters such as transmission power, communication task, AFSS voltage, and resonant frequency to the DQN network.

[0102] Among them, the relevant parameters are detailed in the introduction of the above embodiment and will not be repeated here.

[0103] Step S120, the DQN network calculates the transmission strategy selected after the communication task is transmitted. Please refer to the above embodiment for the calculation process.

[0104] Step S140: The task starts to be transmitted.

[0105] Step S150, if the task changes during the transmission process (such as the channel state, the total number of user terminals changes), continue the operation of step S120, recalculate the relevant parameters, calculate the transmission strategy, and transmit according to the transmission strategy until the task transmission is completed.

[0106] An embodiment of the present application also provides an experimental embodiment.

[0107] When the number of user terminals is set to 100, 125, 150, 175, and 200, an AFSS with six tunable states is constructed to compare the performances of three methods (i.e., the method shown in the above embodiment, the GA method, and the Greedy method).

[0108] Different communication task data volumes and spectrums are allocated to each user terminal, and a certain amount of data is randomly allocated. This embodiment does not consider the noise differences caused by the geographical locations of the user terminals, and uses a random Gaussian white noise to represent the noise of all user terminals.

[0109] like Figures 3 to 5 , the experimental conclusions are as follows:

[0110] (1) Performance analysis under different numbers of user terminals;

[0111] In the first set of simulation experiments, the energy consumption under various transmission strategy selections was studied. Analysis. Six AFSS tuning states are selected. It should be noted that Figure 3 From left to right, they are the 1st state (i.e. the tuning state of AFSS) to the 6th state. Figure 4 and Figure 5 In the present invention, AFSS is used to refer to the above-mentioned embodiment method.

[0112] When the number of user terminals is small, the method shown in the above embodiment can well determine the best transmission strategy selection. When the number of user terminals increases, the method shown in the above embodiment shows a continuous advantage over other methods. When the number of user terminals N=200, the joint power obtained by the method shown in the above embodiment is 11.40% lower than the best performing Greedy method. By fitting the method, compared with the instability generated by using the heuristic method, the method shown in the above embodiment has a more stable strategy selection. This shows that as the scale of user terminals continues to expand, the method shown in the above embodiment has the ability to continuously and stably calculate the optimal strategy.

[0113] Without considering the impact of AFSS energy consumption, the advantages and disadvantages of various methods are compared only from the perspective of shortening communication time. Compared with several heuristic methods, the method shown in the above embodiment can still calculate a better transmission strategy. From the perspective of only considering AFSS energy consumption, when the scale of user terminals is expanded, compared with other methods, the method shown in the above embodiment always has certain advantages. It can be foreseen that the method shown in the above embodiment can effectively solve the communication problem of user terminals at different frequencies, thereby significantly improving the communication quality.

[0114] (2) Performance analysis under different numbers of adjustable AFSS states;

[0115] In addition to the user terminal scale, the number of AFSS tuning states is also an important factor affecting communication QoS. The number of AFSS states available for the experiment is set to 2, 3, 4, 5, and 6, and some states are randomly selected from the total selectable states as experimental settings. The same task volume is set in different states to eliminate the impact of task volume changes on the experimental results.

[0116] As the number of adjustable states of AFSS increases, the energy consumption required for communication with the same amount of tasks Although the results of Greedy and GA methods also show a downward trend, their effects are far less than those of the methods shown in the above embodiments. On the other hand, the results of GA show greater instability, and the computing power is poor when there are more adjustable AFSS voltages. In terms of single time and single power, the methods shown in the above embodiments can also significantly obtain better transmission strategies to meet network requirements.

[0117] When only the time factor is considered, when the number of user terminals is small, the performance of the method shown in the above embodiment can be improved by up to 16.7% compared with the GA method.

[0118] In summary, the method shown in the above embodiment can better find the optimal transmission strategy among multiple methods to meet the communication needs when the user terminals are distributed in multiple different bands. At the same time, for the situation where the number of user terminals is large, the method shown in the above embodiment can well cope with the changes in the number of user terminals and large-scale scenarios.

[0119] In some embodiments of the present application, a wireless communication method based on an AFSS-assisted ground network is also provided, which is used for a controller, the controller is communicatively connected to the ground network, the ground network includes a base station and N user terminals in different frequency spectra, the base station is communicatively connected to the N user terminals, and the communication task of the base station is transmitted to the N user terminals after being tuned by an active frequency selective surface AFSS, where N is a positive integer greater than 1; the method includes:

[0120] Step S210, constructing an AFSS strategy set; the AFSS strategy set includes multiple transmission strategies, each transmission strategy includes a set of corresponding relationships between AFSS voltages and AFSS transmission coefficients at multiple different resonant frequencies;

[0121] Step S220, constructing an objective function for minimizing energy consumption of transmitting communication tasks to N user terminals by the base station based on the AFSS assistance when the transmission strategy is optional according to the AFSS strategy set;

[0122] Step S230, solving the objective function to obtain the objective solution;

[0123] Step S240: According to the target solution, the base station is controlled to adjust the transmission strategy of transmitting the communication task to the N user terminals.

[0124] It should be noted that this example and the above-mentioned system embodiment are based on the same inventive concept and will not be repeated here.

[0125] In some embodiments, the objective function of minimizing transmission energy consumption includes:

[0126] ;

[0127] ;

[0128] ;

[0129] The constraints are:

[0130] ;

[0131] ;

[0132] ;

[0133] in, is the energy consumption of the base station transmitting the communication task to N user terminals, is the weight value; is the average transmission power of the base station, For preset The first task in the transmission period Task transfer period; is the average transmission power of AFSS, For N user terminals The vector representation of the AFSS strategy set for the task transmission period, where The vector representation of the AFSS strategy set corresponding to each task transmission period is: , is the total number of AFSS voltages in the AFSS strategy set, Respectively The vector representation of the transmission strategy corresponding to each AFSS voltage, for A vector representation of the task transfer period; is the first of N user terminals The task transmission rate of each user terminal is related to the AFSS transmission coefficient. For the The amount of data that a user terminal needs to transmit in a communication task; For the The channel bandwidth of each user terminal is is the total channel bandwidth of N user terminals, For the The task transmission time of each user terminal is The total transmission duration of the communication task of the base station not based on AFSS-assisted tuning.

[0134] In some embodiments, deep reinforcement learning DQN is used to solve the objective function to obtain a target solution.

[0135] In some embodiments, the reward function in the deep reinforcement learning DQN includes:

[0136] ;

[0137] ;

[0138] ;

[0139] in, For the Step reward.

[0140] For details, please refer to the relevant introduction of the above system embodiment.

[0141] like Figure 6 The embodiment of the present application further provides an electronic device, the electronic device comprising:

[0142] at least one memory;

[0143] at least one processor;

[0144] at least one program;

[0145] The programs are stored in the memory, and the processor executes at least one program to implement the wireless communication method based on the AFSS-assisted ground network described above in the present disclosure.

[0146] The electronic device may be any intelligent terminal including a mobile phone, a tablet computer, a personal digital assistant (PDA), a vehicle-mounted computer, etc.

[0147] The electronic device according to the embodiment of the present application is described in detail below.

[0148] The processor 1600 may be implemented by a general-purpose central processing unit (CPU), a microprocessor, an application-specific integrated circuit (ASIC), or one or more integrated circuits, and is used to execute relevant programs to implement the technical solutions provided in the embodiments of the present invention.

[0149] The memory 1700 may be implemented in the form of a read-only memory (ROM), a static storage device, a dynamic storage device, or a random access memory (RAM). The memory 1700 may store an operating system and other application programs. When the technical solution provided in the embodiment of this specification is implemented by software or firmware, the relevant program code is stored in the memory 1700, and the processor 1600 calls and executes the wireless communication method based on the AFSS-assisted ground network in the embodiment of the present invention.

[0150] Input / output interface 1800, used to implement information input and output;

[0151] Communication interface 1900, used to realize communication interaction between the device and other devices, which can be realized through wired mode (such as USB, network cable, etc.) or wireless mode (such as mobile network, WIFI, Bluetooth, etc.);

[0152] Bus 2000 , which transmits information between various components of the device (e.g., processor 1600 , memory 1700 , input / output interface 1800 , and communication interface 1900 );

[0153] The processor 1600 , the memory 1700 , the input / output interface 1800 , and the communication interface 1900 are connected to each other in communication within the device via the bus 2000 .

[0154] An embodiment of the present invention further provides a storage medium, which is a computer-readable storage medium. The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned wireless communication method based on the AFSS-assisted ground network.

[0155] The memory, as a non-transient computer-readable storage medium, can be used to store non-transient software programs and non-transient computer executable programs. In addition, the memory may include a high-speed random access memory, and may also include a non-transient memory, such as at least one disk storage device, a flash memory device, or other non-transient solid-state storage device. In some embodiments, the memory may optionally include a memory remotely disposed relative to the processor, and these remote memories may be connected to the processor via a network. Examples of the above-mentioned network include, but are not limited to, the Internet, an intranet, a local area network, a mobile communication network, and combinations thereof.

[0156] The embodiments described in the present invention are intended to more clearly illustrate the technical solutions of the embodiments of the present invention and do not constitute a limitation on the technical solutions provided by the embodiments of the present invention. Those skilled in the art will appreciate that with the evolution of technology and the emergence of new application scenarios, the technical solutions provided by the embodiments of the present invention are also applicable to similar technical problems.

[0157] Those skilled in the art will appreciate that the technical solutions shown in the figures do not limit the embodiments of the present invention and may include more or fewer steps than shown in the figures, or a combination of certain steps, or different steps.

[0158] The device embodiments described above are merely illustrative, and the units described as separate components may or may not be physically separated, that is, they may be located in one place or distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0159] Those skilled in the art will appreciate that all or some of the steps in the methods disclosed above, and the functional modules / units in the systems and devices may be implemented as software, firmware, hardware, or a suitable combination thereof.

[0160] The terms "first", "second", "third", "fourth", etc. (if any) in the specification of the present application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments of the present application described herein can be implemented in an order other than those illustrated or described herein. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device comprising a series of steps or units is not necessarily limited to those steps or units clearly listed, but may include other steps or units that are not clearly listed or inherent to these processes, methods, products or devices.

[0161] In the several embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of units is only a logical function division. There may be other division methods in actual implementation, such as multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or units, which can be electrical, mechanical or other forms.

[0162] The units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place or distributed on multiple network units. Some or all of the units may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0163] In addition, each functional unit in each embodiment of the present application may be integrated into one processing unit, or each unit may exist physically separately, or two or more units may be integrated into one unit. The above-mentioned integrated unit may be implemented in the form of hardware or in the form of software functional units.

[0164] If the integrated unit is implemented in the form of a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application is essentially or the part that contributes to the prior art or all or part of the technical solution can be embodied in the form of a software product, and the computer software product is stored in a storage medium, including multiple instructions to enable an electronic device (which can be a personal computer, server, or network device, etc.) to perform all or part of the steps of each embodiment method of the present application. The aforementioned storage medium includes: U disk, mobile hard disk, read-only memory (Read-Only Memory, ROM), random access memory (Random Access Memory, RAM), disk or optical disk and other media that can store programs.

[0165] The above is a specific description of the preferred implementation of the embodiments of the present application, but the embodiments of the present application are not limited to the above-mentioned implementation methods. Technical personnel familiar with the field can also make various equivalent modifications or substitutions without violating the spirit of the embodiments of the present application. These equivalent modifications or substitutions are all included in the scope defined by the claims of the embodiments of the present application.

Claims

1. A wireless communication system based on AFSS-assisted ground network, characterized in that: The system comprises: A ground network, the ground network comprising a base station and N user terminals in different frequency spectra, the base station being communicatively connected to the N user terminals, and the communication task of the base station being based on tuning-assisted transmission to the N user terminals using an active frequency selective surface AFSS; N is a positive integer greater than 1; A controller is communicatively connected to the ground network, and includes a relationship building module, a function building module, a calculation and solution module, and an information control module, wherein: The relationship building module is used to build an AFSS strategy set; the AFSS strategy set includes multiple transmission strategies, each of which includes a corresponding relationship between a set of AFSS voltages and AFSS transmission coefficients at multiple different resonant frequencies; The function construction module is used to construct, according to the AFSS strategy set, an objective function for minimizing energy consumption when the base station transmits the communication task to the N user terminals when the transmission strategy is optional; the objective function for minimizing energy consumption includes: ； ； ； The constraints are: ； ； ； in, is the energy consumption of the base station transmitting the communication task to N user terminals, is the weight value; is the average transmission power of the base station, For preset The first task in the transmission period Task transfer period; is the average transmission power of AFSS, For N user terminals The vector representation of the AFSS strategy set for the task transmission period, where The vector representation of the AFSS strategy set corresponding to each task transmission period is: , is the total number of AFSS voltages in the AFSS strategy set, Respectively The vector representation of the transmission strategy corresponding to each AFSS voltage, for A vector representation of the task transfer period; is the first of N user terminals The task transmission rate of each user terminal is related to the AFSS transmission coefficient. For the The amount of data that a user terminal needs to transmit in a communication task; For the The channel bandwidth of each user terminal is is the total channel bandwidth of N user terminals, For the The task transmission time of each user terminal is The total transmission duration of the communication task of the base station not based on AFSS-assisted tuning; The calculation and solution module is used to solve the objective function to obtain the target solution; The information control module is used to control the base station to adjust the transmission strategy of transmitting the communication task to the N user terminals according to the target solution.

2. The wireless communication system based on the AFSS-assisted ground network according to claim 1, characterized in that: The calculation and solution module is specifically used to solve the objective function using deep reinforcement learning DQN to obtain a target solution.

3. The wireless communication system based on the AFSS-assisted ground network according to claim 2, characterized in that: The reward function in the deep reinforcement learning DQN includes: ； ； ； in, For the Step reward.

4. A wireless communication method based on AFSS-assisted ground network, characterized in that: Used in a controller, the controller is communicatively connected to a ground network, the ground network includes a base station and N user terminals in different frequency spectra, the base station is communicatively connected to the N user terminals, and the communication tasks of the base station are transmitted to the N user terminals after being tuned by an active frequency selective surface AFSS, where N is a positive integer greater than 1; the method includes: Constructing an AFSS strategy set; the AFSS strategy set includes a plurality of transmission strategies, each of which includes a set of corresponding relationships between AFSS voltages and AFSS transmission coefficients at a plurality of different resonant frequencies; According to the AFSS strategy set, an objective function of minimizing energy consumption by the base station in transmitting the communication task to the N user terminals is constructed when the transmission strategy is optional; the objective function of minimizing energy consumption includes: ； ； ； The constraints are: ； ； ； in, is the energy consumption of the base station transmitting the communication task to N user terminals, is the weight value; is the average transmission power of the base station, For preset The first task in the transmission period Task transfer period; is the average transmission power of AFSS, For N user terminals The vector representation of the AFSS strategy set for the task transmission period, where The vector representation of the AFSS strategy set corresponding to each task transmission period is: , is the total number of AFSS voltages in the AFSS strategy set, Respectively The vector representation of the transmission strategy corresponding to each AFSS voltage, for A vector representation of the task transfer period; is the first of N user terminals The task transmission rate of each user terminal is related to the AFSS transmission coefficient. For the The amount of data that a user terminal needs to transmit in a communication task; For the The channel bandwidth of each user terminal is is the total channel bandwidth of N user terminals, For the The task transmission time of each user terminal is The total transmission duration of the communication task of the base station not based on AFSS-assisted tuning; Solving the objective function to obtain an objective solution; According to the target solution, the base station is controlled to adjust the transmission strategy for transmitting the communication task to the N user terminals.

5. The wireless communication method based on the AFSS-assisted ground network according to claim 4, characterized in that: The objective function is solved by using deep reinforcement learning DQN to obtain the objective solution.

6. The wireless communication method based on the AFSS-assisted ground network according to claim 5, characterized in that: The reward function in the deep reinforcement learning DQN includes: ； ； ； in, For the Step reward.

7. An electronic device, characterized in that: It includes at least one controller and a memory for communicating with the at least one controller; the memory stores instructions that can be executed by the at least one controller, and the instructions are executed by the at least one controller to enable the at least one controller to execute the wireless communication method based on the AFSS-assisted ground network as described in any one of claims 4 to 6.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the wireless communication method based on the AFSS-assisted ground network as described in any one of claims 4 to 6.

Images