Signal transmission method based on rate division multiple access of construction interference and related equipment

Abstract

The invention provides a rate division multiple access signal transmission method based on construction interference and related equipment, which considers existence of an eavesdropping end, considers physical layer security, processes through a constructive interference algorithm, determines constructive interference construction conditions, processes in combination with an interference control algorithm, and determines eavesdropping constraint conditions. According to the method, the receiving signal of the eavesdropping end is controlled in the non-construction area, so that the eavesdropping end cannot receive important private signal data of each target user end in the construction area, and further the eavesdropping end cannot perform normal decoding, thereby ensuring the data security, avoiding the problem of data leakage, performing processing based on a power distribution algorithm of a genetic algorithm, and improving the processing efficiency. And the reduced transmission power which simultaneously meets the minimum rate requirement and the service quality requirement of the user is solved, so that the base station and the plurality of user sides are controlled to execute the signal transmission process according to the target power distribution strategy, and the problem of high energy consumption can be avoided.

Description

Technical Field

[0001] The present application relates to the field of communication technology, and in particular to a signal transmission method and related equipment of rate division multiple access based on structured interference. Background Art

[0002] The arrival of the Sixth Generation of Mobile Wireless Communications (6G) has made the Internet of Everything a reality. Wireless networks are facing unprecedented challenges, including achieving higher data throughput, ensuring more reliable connections, adapting to large-scale device connections, and coping with the heterogeneity of Quality of Service (QoS) requirements, which has led to more significant problems of data leakage and high energy consumption. Therefore, how to avoid data leakage and excessive energy consumption has become a problem that needs to be solved urgently. Summary of the invention

[0003] In view of this, the purpose of the present application is to propose a signal transmission method and related equipment of rate division multiple access based on structured interference to solve the above technical problems.

[0004] Based on the above purpose, the first aspect of the present application provides a signal transmission method based on rate division multiple access with constructed interference, which is applied to a signal transmission system, wherein the system includes a controller, a base station, an eavesdropping terminal and multiple user terminals, and the method includes:

[0005] The base station acquires user data and pre-coded data corresponding to the user data, and processes the user data and the pre-coded data through a transmission signal determination algorithm to obtain a transmission signal of the base station;

[0006] Each of the multiple user terminals is used as a target user terminal, and the target user terminal processes the transmission signal of the base station through the user terminal reception signal determination algorithm to obtain a reception signal of the target user terminal;

[0007] The target user terminal processes the received signal of the target user terminal through a signal-to-noise ratio determination algorithm of the user terminal decoding public information to obtain a signal-to-noise ratio of the public information decoded by the target user terminal, and the target user terminal processes the received signal of the target user terminal through a user terminal private data stream realization rate determination algorithm to obtain a realization rate of the private data stream of the target user terminal;

[0008] The eavesdropping end processes the transmission signal of the base station through the reception signal determination algorithm of the eavesdropping end to obtain the reception signal of the eavesdropping end;

[0009] The eavesdropping end processes the received signal of the eavesdropping end through a signal-to-noise ratio determination algorithm for decoding public information by the eavesdropping end to obtain a signal-to-noise ratio of the public information decoded by the eavesdropping end;

[0010] The target user end processes the received signal of the target user end through a constructive interference algorithm to determine a constructive interference construction condition;

[0011] The eavesdropping end processes the received signal of the eavesdropping end through an interference control algorithm to determine the eavesdropping constraint condition;

[0012] The controller constructs an objective function based on the transmitted signal of the base station, constructs a signal-to-noise ratio constraint condition based on the signal-to-noise ratio of the public information decoded by each user terminal, and constructs a rate constraint condition using the implementation rate of the private data stream of each user terminal. Based on the signal-to-noise ratio constraint condition, the rate constraint condition, the constructive interference construction condition and the eavesdropping constraint condition, the objective function is processed by a power allocation algorithm of a genetic algorithm to determine a target power allocation strategy when the value of the objective function is minimized, and the base station and the multiple user terminals are controlled to perform a signal transmission process according to the target power allocation strategy.

[0013] Based on the same inventive concept, the second aspect of the present application provides an electronic device, comprising a memory, a processor, and a computer program stored on the memory and executable by the processor, wherein the processor implements the method described in the first aspect above when executing the computer program.

[0014] From the above, it can be seen that the signal transmission method and related equipment of rate division multiple access based on constructed interference provided by the present application take into account the existence of the eavesdropping end. From the perspective of physical layer security, the constructive interference algorithm is used for processing to determine the constructive interference construction conditions, and the interference control algorithm is used for processing to determine the eavesdropping constraint conditions. The eavesdropping end receives the signal within the non-constructed area, so that the eavesdropping end cannot receive the important private signal data of each target user end in the constructed area, and thus the eavesdropping end cannot decode normally, thereby ensuring the security of the data and avoiding the problem of data leakage. The power allocation algorithm based on the genetic algorithm is used for processing to obtain the transmission power that satisfies the user's minimum rate requirements, service quality requirements and reduction at the same time, and then the base station and multiple user ends are controlled to execute the signal transmission process according to such a target power allocation strategy, which can avoid the problem of high energy consumption. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] In order to more clearly illustrate the technical solutions in the present application or related technologies, the drawings required for use in the embodiments or related technical descriptions are briefly introduced below. Obviously, the drawings described below are only embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0016] Figure 1 A flowchart of a signal transmission method of rate division multiple access based on structured interference according to an embodiment of the present application;

[0017] Figure 2A A schematic diagram of the architecture of a signal transmission system according to an embodiment of the present application;

[0018] Figure 2B A schematic diagram of the relationship between the total transmission power, the public information transmission power, the private information transmission power, the distance between the base station and the user, and the user signal-to-noise ratio threshold in an embodiment of the present application;

[0019] Figure 2C A schematic diagram of the proportion of the achievable public rate and private rate in the total system rate under a fixed total transmission rate in an embodiment of the present application;

[0020] Figure 2D A schematic diagram of the relationship between the average total transmit power, public transmit power, private transmit power and distance of different schemes under the condition of SNR=5dB in an embodiment of the present application;

[0021] Figure 2E A schematic diagram of the relationship between the transmit power and the signal-to-noise ratio values ​​of different users in simulations of different schemes according to an embodiment of the present application;

[0022] Figure 2F A schematic diagram of the impact of the CRSMA scheme of an embodiment of the present application on the allocation of private transmission power between single users;

[0023] Figure 2G-1 A first schematic diagram of receiving signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0024] Figure 2G-2 A second schematic diagram of receiving signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0025] Figure 2G-3 A third schematic diagram of receiving signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0026] Figure 2H-1 A fourth schematic diagram of receiving signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0027] Figure 2H-2 A fifth schematic diagram of receiving signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0028] Figure 2H-3 A sixth schematic diagram of received signal points of user 1 and an eavesdropper under different conditions in an embodiment of the present application;

[0029] Figure 3 A structural block diagram of a signal transmission loading method of rate division multiple access based on structured interference according to an embodiment of the present application;

[0030] Figure 4 A schematic diagram of an electronic device according to an embodiment of the present application. DETAILED DESCRIPTION

[0031] In order to make the objectives, technical solutions and advantages of the present application more clearly understood, the present application is further described in detail below in combination with specific embodiments and with reference to the accompanying drawings.

[0032] It should be noted that, unless otherwise defined, the technical terms or scientific terms used in the embodiments of the present application should be the usual meanings understood by people with ordinary skills in the field to which the present application belongs. The "first", "second" and similar words used in the embodiments of the present application do not represent any order, quantity or importance, but are only used to distinguish different components. "Including" or "comprising" and similar words mean that the elements or objects appearing in front of the word cover the elements or objects listed after the word and their equivalents, without excluding other elements or objects. "Connect" or "connected" and similar words are not limited to physical or mechanical connections, but can include electrical connections, whether direct or indirect. "Up", "down", "left", "right" and the like are only used to indicate relative positional relationships. When the absolute position of the described object changes, the relative positional relationship may also change accordingly.

[0033] It is understandable that before using the technical solutions of each embodiment of the present application, the type, scope of use, usage scenarios, etc. of the personal information involved will be informed to the user in an appropriate manner, and the user's authorization will be obtained.

[0034] For example, in response to receiving an active request from a user, a prompt message is sent to the user to clearly remind the user that the operation requested to be performed will require obtaining and using the user's personal information. Thus, the user can independently choose whether to provide personal information to the electronic device, application, server, storage medium or other software or hardware that performs the operation of the technical solution of the present application according to the prompt message.

[0035] As an optional but non-limiting implementation, in response to receiving the user's active request, the prompt information may be sent to the user in the form of a pop-up window, in which the prompt information may be presented in text form. In addition, the pop-up window may also carry a selection control for the user to choose "agree" or "disagree" to provide personal information to the electronic device.

[0036] It is understandable that the above notification and the process of obtaining user authorization are merely illustrative and do not constitute a limitation on the implementation method of this application. Other methods that meet relevant laws and regulations may also be applied to the implementation method of this application.

[0037] The arrival of the Sixth Generation of Mobile Wireless Communications (6G) has made the Internet of Everything a reality. Wireless networks are facing unprecedented challenges, including achieving higher data throughput, ensuring more reliable connections, adapting to large-scale device connections, and coping with the heterogeneity of Quality of Service (QoS) requirements, which has led to more significant problems of data leakage and high energy consumption. Physical layer security (PLS) is different from traditional encryption methods. It uses the inherent randomness of wireless channels and has performance advantages in terms of computational complexity and adaptability to heterogeneous environments.

[0038] Multiple access (MA) technology is the core of wireless communication. Traditionally, multiple access schemes are divided into two types: orthogonal and non-orthogonal. However, this classification cannot fully reflect the complexity of modern communication design. RSMA is an innovative multi-user information transmission method that overcomes the limitations of spatial division multiple access (SDMA) and non-orthogonal multiple access (NOMA). The information is divided into public streams and private streams at the transmitter. The information carried by the public stream is decoded by all users, and the private stream is for specific users. In recent years, the research on RSMA in related technologies is as follows:

[0039] The problem of maximizing the total confidentiality spectrum efficiency (SE) of two types of users in the RSMA system is considered: one type of users' private information flows require information security protection, while the other type of users do not; or, the research focuses on RSMA-based communication systems under transmission power constraints, aiming to maximize the minimum security rate (MSR) of legitimate users; or, artificial noise (AN) is introduced into RSMA, and the problem of maximizing the minimum user rate under security constraints is solved; or, RSMA is combined with smart reflection surface (RIS) to propose an energy efficiency optimization algorithm for 6G multi-cellular communication systems. Current research shows that RSMA exceeds SDMA and NOMA in terms of degrees of freedom (DoF), efficiency, versatility, flexibility, robustness and low latency; or, constructive interference (CI) precoding is an innovative symbol-level precoding scheme, which is different from traditional linear precoding methods such as minimum mean square error (MMSE), maximum ratio transmission (MRT) and zero forcing (ZF). CI uses channel state information (CSI) and inherent data symbol information to locate the interfering signal within the constructive interference region of the relevant symbol, thereby converting multi-user interference (MUI) into useful received power. CI significantly improves the symbol error rate (SER) performance and reduces the transmission power by exploiting the spatial and symbol-level degrees of freedom (DoF). Closed-form expressions of CI for strict and non-strict phase rotation are proposed for various modulation schemes such as phase-shift keying (PSK) and quadrature amplitude modulation (QAM), respectively; or, a secure precoding algorithm based on constructive-destructive (CD) interference is applicable to the case involving a single eavesdropper, achieving energy-efficient secure information transmission and secure wireless power transmission (SWIPT); or, the existing CD-based precoding scheme is modified to fully utilize the entire destructive interference (DI) region to better deal with smart eavesdroppers; or, symbol-level precoding technology is used to enhance the security of multi-user multiple-input multiple-output (MU-MIMO) communication systems when the eavesdropper's CSI is unknown. Currently, CI precoding has been combined with a variety of wireless systems, including massive MIMO systems, smart metasurface (RIS)-assisted systems, and non-orthogonal multiple access technology (NOMA), and has shown significant potential in enhancing physical layer security, reducing transmission power, and improving sum performance. However, the application of CI in RSMA networks has not been widely studied; alternatively, serial communication (RS) in a multi-user multi-antenna environment is explored and a method to utilize CI is proposed, using the existing strict phase rotation derived closed-form CI coding to process private information and calculate the traversal and rate of RS, but the presence of eavesdroppers is not considered.

[0040] The above prior art has the following problems:

[0041] (1) The existing RSMA scheme ignores the interference of multiple users, which affects the accuracy of users' decoding of private information. The present application adopts CI precoding for private information in the RSMA system, allowing each user to convert interference into useful information during decoding, thereby enhancing its decoding ability. (2) The energy consumption of existing RSMA technology is too high, and there is little research on its encoding method. The present application proposes a CI-assisted RSMA scheme that reduces power consumption while meeting the same performance, and at the same time solves the far-near effect of traditional multiple access technology. (3) The existing RSMA does not provide sufficient protection for data privacy. The present application takes into account the existence of eavesdroppers and, from the perspective of physical layer security, controls the eavesdropper's receiving signal within a non-constructed area to ensure that the eavesdropper cannot decode normally, thereby ensuring the security of the data.

[0042] Based on the above background, this application proposes a multi-user multiple input single output (MU-MISO) based on CI technology assisted RSMA system (CRSMA) solution, and proposes a downlink CRSMA system model including eavesdroppers to supplement the traditional RSMA multi-user interference and data leakage problems. In addition, it also proposes a problem statement of minimizing the base station transmission power in the CRSMA scheme with CSI, determines the beamforming vector that meets the user's minimum service quality requirements and security performance, and minimizes the weighted sum of transmission power to achieve green and safe RSMA.

[0043] In response to the multi-user interference problem in wireless communication scenarios, this application uses constructive interference (CI) precoding for private information in the Rate-Splitting Multiple Access (RSMA) system, allowing users to convert interference into useful information when decoding private information, thereby enhancing decoding capabilities and improving the accuracy of decoding private information. In response to the problem that there are few studies on encoding methods in RSMA systems and the excessive energy consumption of RSMA, this application proposes a problem statement of minimizing the base station transmission power, reducing power consumption while meeting the same performance. In response to the problem of insufficient data privacy protection in RSMA scenarios, this application takes into account the existence of eavesdroppers and, from the perspective of physical layer security, controls the eavesdropper's receiving signal within a non-constructed area to ensure that the eavesdropper cannot decode normally, thereby ensuring data security.

[0044] Among them, (1) Rate Division Multiple Access: Rate Division Multiple Access is a multi-user information transmission method that divides user data into two parts: a public part and a private part. The public part contains information that all users need to decode, while the private part contains information that is only for a specific user. At the transmitter, the public part and the private part are encoded separately and transmitted in different ways. At the receiver, the user first decodes the public part and then uses interference cancellation technology to decode the private part. (2) Constructive interference: Constructive interference is a technology that uses channel state information and data symbol information to place the interference signal within the constructed interference area of ​​the symbol of interest, thereby converting multi-user interference into useful received power. (3) Physical layer security: Security technology based on physical channels aims to utilize the randomness and uniqueness of the physical medium of wireless communication (such as wireless fading channels, received signal strength, hardware fingerprints, etc.) to provide lightweight and high-security security for networks and users. Physical layer security technology makes full use of the channel resources of wireless transmission and achieves high-intensity unconditional secure transmission without the need to assume that the attacker has limited computing power. (4) MU-MISO: MU-MISO is a wireless communication system that efficiently utilizes wireless resources. It implements spatial diversity and spatial multiplexing by equipping the transmitting end (called a base station or access point) with multiple antennas, thereby improving communication performance and spectrum efficiency. The system can simultaneously serve multiple single-antenna user terminals (called user equipment) in the same frequency band at the same time, thereby significantly improving the performance of wireless communications.

[0045] The embodiment of the present application provides a signal transmission method of rate division multiple access based on constructed interference, which is applied to a signal transmission system. The system includes a controller, a base station, an eavesdropping terminal and multiple user terminals. Taking the existence of the eavesdropping terminal into consideration, from the perspective of physical layer security, a constructive interference algorithm is used for processing to determine the constructive interference construction conditions, and an interference control algorithm is used for processing to determine the eavesdropping constraint conditions. The eavesdropping terminal receives the signal within a non-constructed area, so that the eavesdropping terminal cannot receive important private signal data of each target user terminal within the constructed area, thereby making it impossible for the eavesdropping terminal to decode normally, thereby ensuring data security and avoiding data leakage problems. A power allocation algorithm based on a genetic algorithm is used for processing to obtain a transmission power that simultaneously meets the user's minimum rate requirements, service quality requirements and reduced transmission power, and then the base station and multiple user terminals are controlled to execute the signal transmission process according to such a target power allocation strategy, thereby avoiding the problem of high energy consumption.

[0046] like Figure 1 As shown, the method includes:

[0047] Step 101: The base station obtains user data and pre-coded data corresponding to the user data, and processes the user data and the pre-coded data through a transmission signal determination algorithm to obtain a transmission signal of the base station.

[0048] In this step, the base station, as a key node in the wireless communication network, is responsible for communicating with the user terminal (such as mobile phones, laptops, etc.). In this process, the base station first needs to obtain data from the user device. This data can include various types of information such as voice call content, text information, video streams, etc., which are generated by the user terminal and need to be sent to other devices or network nodes through the wireless communication network.

[0049] In addition to the user data, the base station also needs to obtain the pre-coded data corresponding to the user data. The pre-coded data is usually the result of a series of pre-processing operations on the original user data before the data is sent in order to improve the efficiency and reliability of data transmission. These pre-processing operations may include data compression, encryption, modulation, encoding, etc. The pre-coded data contains the necessary information on how to correctly decode and restore the original user data.

[0050] After the base station obtains the user data and pre-coded data, it will process them through the transmission signal determination algorithm, with the purpose of determining the best transmission signal based on the current communication environment (such as signal interference, noise level, channel conditions, etc.) and system requirements (such as data transmission rate, bit error rate, etc.). This process may involve signal optimization, resource allocation, power control and other aspects to ensure that the data can be transmitted to the target user equipment in an efficient and reliable manner.

[0051] After being processed by the transmit signal determination algorithm, the base station will eventually obtain one or more transmit signals. These transmit signals are obtained after the original user data and pre-coded data are encoded, modulated, etc., and they are designed to adapt to the current communication environment and system requirements. The base station then sends these transmit signals to the wireless channel through the antenna so that the user terminal can receive and decode the original user data.

[0052] Step 102: each of the multiple user terminals is used as a target user terminal. The target user terminal is processed by a user terminal receiving signal determination algorithm based on the transmission signal of the base station to obtain a receiving signal of the target user terminal.

[0053] In this step, the base station sends signals to all user terminals, and these signals contain data to be transmitted to each user terminal. In actual situations, due to the characteristics of the wireless channel, these signals may be affected by factors such as attenuation, multipath effect, and interference during transmission.

[0054] Each target user terminal uses the user terminal's received signal determination algorithm to process the signal it receives. The goal is to extract useful information (i.e., data sent to the user terminal) from the received signal while minimizing the effects of noise and interference. This algorithm may include steps such as channel estimation, signal detection, and decoding.

[0055] After the above processing, the target user end can successfully obtain the data signal sent to it. This process ensures that the user end can reliably receive the data even in the presence of noise and interference.

[0056] Step 103: The target user terminal processes the received signal of the target user terminal through a signal-to-noise ratio determination algorithm for user terminal decoding public information to obtain a signal-to-noise ratio of the public information decoded by the target user terminal, and the target user terminal processes the received signal of the target user terminal through a user terminal private data stream realization rate determination algorithm to obtain a realization rate of the private data stream of the target user terminal.

[0057] In this step, in a multi-user wireless communication system, public information refers to information that can be received and used by all user terminals, such as control information broadcast by the system, synchronization signals, etc. Such information is crucial for the normal operation of the system.

[0058] The signal-to-noise ratio refers to the ratio of signal power to noise power and is an important indicator for measuring the performance of a communication system. A high signal-to-noise ratio means better signal quality and a lower decoding error rate.

[0059] The target user end first receives signals from the base station or other transmitting source. Then, it processes these signals using the signal-to-noise ratio determination algorithm for decoding public information at the user end to calculate the signal-to-noise ratio when decoding public information. This algorithm may involve multiple steps such as signal demodulation, decoding, and noise estimation.

[0060] In a multi-user wireless communication system, a private data stream refers to a data stream that is specifically sent to a specific user end and is kept confidential from other users. Private data streams are usually used to transmit user-specific data, such as voice calls, video streams, or Internet data.

[0061] The achieved rate refers to the data rate at which a private data stream can be continuously transmitted during actual communication. This rate is affected by many factors, including signal quality, system resource allocation, interference, etc.

[0062] The target user end also calculates the realization rate of the private data stream based on the received signal using the realization rate determination algorithm of the user end private data stream. This algorithm may involve multiple aspects such as the evaluation of signal quality, the understanding of system resource allocation, and possible interference analysis.

[0063] Step 104: the eavesdropping end processes the signal sent by the base station through a received signal determination algorithm of the eavesdropping end to obtain a received signal of the eavesdropping end.

[0064] In this step, the eavesdropping end refers to an unauthorized entity that attempts to intercept or monitor the communication between the base station and the user end. This eavesdropping end may be an attacking user device or entity, or it may be some form of monitoring system.

[0065] In order to extract useful information from the signal sent by the base station, the eavesdropper uses the received signal determination algorithm of the eavesdropper to process the received signal. This algorithm is usually designed to separate the useful signal from the noise and interference and restore the original sent information as accurately as possible.

[0066] After the above algorithm processing, the signal finally obtained by the eavesdropping end is its received signal. This signal contains the information from the base station that the eavesdropping end successfully intercepted.

[0067] Step 105 , the eavesdropping end processes the received signal of the eavesdropping end through a signal-to-noise ratio determination algorithm for decoding public information of the eavesdropping end to obtain a signal-to-noise ratio of the public information decoded by the eavesdropping end.

[0068] In this step, the eavesdropping end processes the received signal of the eavesdropping end through the signal-to-noise ratio determination algorithm for decoding public information by the eavesdropping end, which is used to evaluate the ratio between the signal and the noise (i.e., signal-to-noise ratio, SNR) when the eavesdropping end attempts to decode public information. The signal-to-noise ratio is an important indicator for measuring signal quality. A high signal-to-noise ratio means a clearer signal and less noise, making it easier to be correctly decoded.

[0069] By applying the above algorithm, the eavesdropper can calculate the signal-to-noise ratio when trying to decode the public information. This value is important to the eavesdropper because it can indicate the probability of successful eavesdropping. If the signal-to-noise ratio is high, the eavesdropper may be more likely to successfully decode the information; if the signal-to-noise ratio is low, the decoding may fail or produce errors.

[0070] Step 106: The target user end processes the received signal of the target user end through a constructive interference algorithm to determine a constructive interference construction condition.

[0071] In this step, the signal received by the target user end from the external environment may contain useful information (such as voice, data, etc.) or interference signals (such as noise, other communication signals, etc.). The quality of the received signal is crucial to the function and performance of the target user end.

[0072] Constructive interference algorithms are used to process interference components in received signals. Constructive interference algorithms attempt to use these interference signals to have a positive impact on the received useful signals through specific processing methods, which is called "constructive interference". The purpose of this algorithm is to improve the quality of signal reception, which may be achieved by enhancing signal strength, improving signal-to-noise ratio, etc.

[0073] By running a constructive interference algorithm, the target user end analyzes the received signal and determines how to construct constructive interference under specific conditions. These conditions may include parameters such as the frequency, phase, and strength of the signal, and how to make adjustments on these parameters to maximize the effect of constructive interference. Once these conditions are determined, the target user end can use this information to optimize its signal processing process, thereby improving the quality of the received signal.

[0074] Step 107: The eavesdropping end processes the received signal of the eavesdropping end through an interference control algorithm to determine the eavesdropping constraint condition.

[0075] In this step, the interference control algorithm is used to intentionally interfere with the eavesdropping end by the legitimate communicating parties (to enhance the security of communication).

[0076] By applying interference control algorithms, the ability of the eavesdropper to successfully steal information is limited, making it impossible for the eavesdropper to steal private information and then use it for decryption, thus ensuring communication security.

[0077] Step 108, the controller constructs an objective function based on the transmitted signal of the base station, constructs a signal-to-noise ratio constraint based on the signal-to-noise ratio of the public information decoded by each user terminal, and constructs a rate constraint using the implementation rate of the private data stream of each user terminal, processes the objective function through a power allocation algorithm of a genetic algorithm based on the signal-to-noise ratio constraint, the rate constraint, the constructive interference construction condition, and the eavesdropping constraint, determines a target power allocation strategy when the value of the objective function is minimized, and controls the base station and the multiple user terminals to perform a signal transmission process according to the target power allocation strategy.

[0078] In this step, the controller is responsible for determining the power allocation strategy.

[0079] Genetic algorithm is an optimization algorithm that simulates natural selection and genetic mechanism. In this scenario, it is used to find the optimal power allocation strategy, that is, how to allocate the transmission power of the base station to achieve the best system performance while satisfying all the above conditions (including signal-to-noise ratio, private data flow rate, constructive interference construction and eavesdropping constraints).

[0080] By running a power allocation algorithm based on a genetic algorithm, the controller can determine an optimal power allocation strategy, that is, how to allocate power to different user terminals and different information flows.

[0081] Once the target power allocation strategy is determined, the controller will control the signal transmission process between the base station and the user end according to this strategy to ensure the effective and safe operation of the system.

[0082] Through the above scheme, the existence of the eavesdropping end is taken into account. From the perspective of physical layer security, the constructive interference algorithm is used for processing to determine the constructive interference construction conditions. The interference control algorithm is combined for processing to determine the eavesdropping constraint conditions, and the eavesdropping end receiving signal is controlled within the non-construction area, so that the eavesdropping end cannot receive the important private signal data of each target user end in the construction area, and thus the eavesdropping end cannot decode normally, thereby ensuring data security and avoiding data leakage problems. The power allocation algorithm based on the genetic algorithm is used for processing to obtain the transmission power that meets the user's minimum rate requirements, service quality requirements and reduced transmission power at the same time, and then the base station and multiple user ends are controlled to execute the signal transmission process according to such a target power allocation strategy, which can avoid the problem of high energy consumption.

[0083] In some embodiments, in step 101, the processing based on the user data and the pre-coded data by a transmission signal determination algorithm to obtain the transmission signal of the base station includes:

[0084] The base station determines the transmission signal of the base station based on the user data and the pre-coded data by the following formula:

[0085]

[0086] Where x represents the signal sent by the base station, s represents user data, and s = [s c ,s 1 ,s 2 , ..., s K ] T , P represents the pre-coded data, P = [p c , p 1 , p 2 , ..., p K ], p c ∈C N×1 It is the public data stream s in the user data c The pre-encoder data, p k ∈C N×1 is the private data stream s in the kth user data k The pre-encoder data, is the user-side index,

[0087] In the above scheme, the CRSMA downlink system (i.e., signal transmission system) of the multi-user multiple input single output (MU-MISO) of the present application is as follows: Figure 2A As shown, the system includes an N-antenna base station (BS) that provides services to K single-antenna users (i.e., user terminals) at the same time, indexed as In this system, the channel is assumed to be an independent and identically distributed (iid) Rayleigh fading channel. The BS uses the same time-frequency resources to send K independent confidential information W to K users respectively. 1 , ..., W K In RSMA, the information W k Divide into public part W c，k and the private part W p，k . Common part W c，1 , ..., W c，K Merge into public information W c , and uses the codebook shared by all users to encode into a common stream s c Therefore, s c Must be decoded by all users. Then, the K private streams are mapped to the BS antenna array through the CI pre-encoder, and the public part is pre-encoded in a multicast manner, so the transmission signal at the BS (i.e., the base station's transmission signal) is expressed as:

[0088]

[0089] Where s = [s c ,s 1 ,s 2 , ..., s K ] T , (i.e. user data), s k The unit standard M phase shift keying (PSK) modulation is adopted. Therefore, E(ss H )=I, and its corresponding constellation point satisfies where φ k is the phase, j represents the imaginary unit, P = [p c , p 1 , p 2 , ..., p K ] is the pre-encoder matrix (i.e., pre-encoded data). c ∈C N×1 Yes c The pre-encoder, p c ∈C N×1 is the kth dedicated stream s k (i.e. private data stream) pre-encoder.

[0090] The signal transmission determination algorithm can make the determined base station's signal transmission adapt to the current communication environment and system requirements, so as to ensure that data can be transmitted to the target user equipment in an efficient and reliable manner.

[0091] In some embodiments, in step 102, the target user terminal processes the signal sent by the base station through a received signal determination algorithm of the user terminal to obtain a received signal of the target user terminal, including:

[0092] The target user terminal determines the received signal of the target user terminal based on the transmitted signal of the base station by using the following formula:

[0093]

[0094] Among them, y k represents the received signal of the target user end k, h k ∈C N×1 is the channel between the base station and the target user terminal k, X represents the sending signal of the base station, is the additive Gaussian white noise at the target user end k, p c ∈C N×1 It is the public data stream s in the user data c The pre-encoder data, p i is the private data stream S in the i-th user data i The pre-encoder data, is the user-side index,

[0095] In the above scheme, if Figure 2A As shown, the signal received by user terminal k (i.e., the received signal of the standard user terminal) can be written as:

[0096]

[0097] Among them, h k ∈C N×1 is the channel between the BS and the target user end k, considering the Rayleigh block fading channel, and assuming that the channel state information (CSI) of the target user end and the eavesdropping end is completely known at the BS; is the additive white Gaussian noise (AWGN) at the target user end k.

[0098] The received signal determination algorithm at the user end enables the target user end to successfully obtain the data signal sent to it. This process ensures that the user end can reliably receive data even in the presence of noise and interference.

[0099] In some embodiments, in step 103, the target user terminal processes the received signal of the target user terminal through a signal-to-noise ratio determination algorithm of the user terminal decoding public information to obtain the signal-to-noise ratio of the target user terminal decoding public information, including:

[0100] Step A1: the target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal. k , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k

[0101] Step A2: the target user terminal is based on the channel h between the base station and the target user terminal k. k , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The signal-to-noise ratio of the public information decoded by the target user terminal is determined by the following formula:

[0102]

[0103] Among them, γ c，k represents the signal-to-noise ratio of the public information decoded by the target user terminal, is the user-side index, i represents the order of the index of the client.

[0104] In the above scheme, if Figure 2A As shown in Figure 1, at the receiving end (RSMAReceiver), each user end first treats all private information streams as noise, decodes the public information stream, and then uses continuous interference cancellation (SIC) to remove the public information under the assumption of error-free decoding, and then decodes its own private information. Since CI precoding is used for private information, the other K-1 private information streams decode the target user end k s k Therefore, the target user terminal k decodes s c The signal-to-noise ratio (SNR) can be expressed as follows:

[0105]

[0106] The signal-to-noise ratio when decoding public information can be determined quickly and accurately by the signal-to-noise ratio determination algorithm for decoding public information at the user end.

[0107] Therefore, the public data flow R of the target user k is c，k The achievable rate is:

[0108] R c，k =log 2 (1+γ c，k ) The achievable rate of public information is To ensure that all users can successfully decode public information. c Shared by all users, each user is assigned R c Zhong and W c，k The rate corresponding to c k The data rate allocation matrix for each target user terminal k to receive public information is c = [c 1 , c 2 , ..., c K ], the constraints are satisfied

[0109] In some embodiments, in step 103, the target user terminal processes the received signal of the target user terminal through the user terminal private data stream realization rate determination algorithm to obtain the realization rate of the target user terminal private data stream, including:

[0110] Step B1: the target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal. k , and the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k

[0111] Step B2: the target user terminal is based on the channel h between the base station and the target user terminal k. k , and the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The signal-to-noise ratio of the private information decoded by the target user terminal is determined by the following formula:

[0112]

[0113] Among them, γ p，k represents the signal-to-noise ratio of the target user end decoding private information, is the user-side index, i represents the order of the index of the client.

[0114] Step B3, the target user terminal determines the realization rate of the private data stream of the target user terminal by the following formula based on the signal-to-noise ratio of the private information decoded by the target user terminal:

[0115] R p，k =log 2 (1+γ p，k )

[0116] Among them, R p，k represents the realization rate of the private data flow of the target user end, γ p，k Indicates the signal-to-noise ratio of the target user end decoding private information.

[0117] In the above scheme, if Figure 2A As shown in Figure 1, at the receiving end (RSMA Receiver), each user end first treats all private information streams as noise, decodes the public information stream, and then uses continuous interference cancellation (SIC) to remove the public information under the assumption of error-free decoding, and then decodes its own private information. Since CI precoding is used for private information, the other K-1 private information streams decode the target user end k s k Therefore, the target user terminal k decodes s k The signal-to-noise ratio (SNR) can be expressed as follows:

[0118]

[0119] Therefore, the private data stream R of target user k is p，k The achievable rate is:

[0120] R p，k =log 2 (1+γ p，k )

[0121] The above method can quickly and accurately determine the signal-to-noise ratio when decoding public information, thereby determining the private data stream R of the target user terminal k. p，k The achievable rate is more accurate.

[0122] In some embodiments, step 104 includes:

[0123] The eavesdropping end determines the received signal of the eavesdropping end based on the transmitted signal of the base station by using the following formula:

[0124]

[0125] Among them, y erepresents the received signal of the eavesdropping end, h e ∈C N×1 is the channel between the base station and the eavesdropping end e, X represents the sending signal of the base station, is the additive white Gaussian noise at the eavesdropping end e, p c ∈C N×1 It is the public data stream s in the user data c The pre-encoder data, p k ∈C N×1 is the private data stream s in the kth user data k The pre-encoder data, is the user-side index,

[0126] In the above scheme, if Figure 2A As shown, the received signal of the eavesdropping end can be expressed as follows:

[0127]

[0128] Among them, h e ∈C N×1 is the channel between BS and the eavesdropping end, is the additive white Gaussian noise (AWGN) at the eavesdropping end.

[0129] The received signal of the eavesdropping end can be determined quickly and accurately through the received signal determination algorithm of the eavesdropping end.

[0130] In some embodiments, step 105 includes:

[0131] Step C1, the eavesdropping end decodes the received signal of the eavesdropping end, and determines the channel h between the base station and the eavesdropping end e from the received signal of the eavesdropping end e , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the eavesdropping end e

[0132] Step C2: the eavesdropping end decodes the received signal of the eavesdropping end and determines the channel h between the base station and the eavesdropping end e from the received signal of the eavesdropping end. e , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the eavesdropping end e The signal-to-noise ratio of the public information decoded by the eavesdropping end is determined by the following formula:

[0133]

[0134] in, represents the signal-to-noise ratio of the public information decoded by the eavesdropping end, is the user-side index, i represents the order of the index of the client.

[0135] In the above scheme, the decoding process of the eavesdropper is similar to that of each target user end, but the eavesdropper cannot successfully decode the public stream, nor can it use SIC to subtract the shared data from it. When the eavesdropper decodes the private data stream, the public data stream will act as interference, so the eavesdropper decodes s c and k The signal-to-noise ratio (SNR) is:

[0136]

[0137] Public stream of the eavesdropping end and private streams The achievable rates are:

[0138]

[0139] The signal-to-noise ratio of the public information decoded by the eavesdropping end can be determined quickly and accurately in the above manner.

[0140] In some embodiments, step 106 includes:

[0141] Step D1, the target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal k , the private data stream S in the i-th user data i The pre-encoder data p i , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane Additive Gaussian white noise at the target user end k The signal-to-noise ratio requirement of the target user terminal k is Γ k .

[0142] Step D2: the target user terminal is based on the channel h between the base station and the target user terminal k. k , the private data stream S in the i-th user data i The pre-encoder data p i, the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane Additive Gaussian white noise at the target user end k The signal-to-noise ratio requirement of the target user terminal k is Γ k , the constructive interference construction condition is determined by the following formula:

[0143]

[0144] Where k represents the order of the user end, is the user-side index,

[0145] In the above scheme, if Figure 2A As shown, for private information, CI encoding is used as follows Figure 2A The receiver complex plane (a) is shown in the form of QPSK as an example (M = 4). k is the symbol that the target user k is interested in, and its complex plane coordinates are For QPSK modulation, s k The decision boundaries of are the R axis and the I axis. In order to quantify the QoS requirements, let Γ k is the signal-to-noise ratio requirement of the target user terminal k. When the private information of other users is ignored and only a single user terminal is considered, point A is the minimum point that meets the signal-to-noise ratio threshold of the target user terminal k, that is:

[0146]

[0147] The noise-free private information actually received by the target user end k is represented by point B on the complex plane:

[0148]

[0149] P needs to be designed to ensure that point B is located in the constructive (green) area (i.e., the constructed area) and away from the corresponding decision boundary, so as to constructively utilize the interference and correctly decode s while ensuring the signal-to-noise ratio threshold. k Point C is point B at The projection in the direction. Figure 2A In the modulation constellation diagram part, the signal received by the target user end k needs to meet the following requirements:

[0150]

[0151] Figure 2A The complex plane of the receiver (b) is obtained by rotating (a) clockwise by φ kAfter that, the construction conditions (i.e. constructive interference construction conditions) can be obtained according to the geometric relationship:

[0152]

[0153] It can be further expressed as:

[0154]

[0155] In some embodiments, step 107 includes:

[0156] Step E1: the eavesdropping end receives a signal y from the eavesdropping end. e Decode the received signal y from the eavesdropping end e Determine the additive white Gaussian noise n at the eavesdropping end e e , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane The square root of the additive white Gaussian noise at the eavesdropping end e is σ e , the signal-to-noise ratio requirement of the eavesdropping end e is Γ e .

[0157] Step E2: the eavesdropping end receives a signal y from the eavesdropping end. e Decode the received signal y from the eavesdropping end e Determine the additive white Gaussian noise n at the eavesdropping end e e , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane The square root of the additive white Gaussian noise at the eavesdropping end e is σ e , the signal-to-noise ratio requirement of the eavesdropping end e is Γ e , the eavesdropping constraint condition is determined by the following formula:

[0158]

[0159] In the above scheme, if Figure 2A As shown, at the eavesdropping end, the noise-free received signal is point D, which should be controlled within the interference (red) area (i.e., outside the construction area). In order to make full use of the entire destruction area, the constraints (i.e., eavesdropping constraints) are:

[0160]

[0161] Among them, Γ e is the signal-to-noise ratio requirement of the eavesdropping end, It is the noise-free information actually received by the eavesdropping end.

[0162] Through the eavesdropping constraint conditions, the eavesdropping end can only receive information from the interference (red) area of ​​the user end, and the user end stores the received private information in the green area through constructive interference construction conditions. Therefore, the eavesdropping end cannot steal private information from the user end, thereby ensuring communication security.

[0163] In some embodiments, the controller of the present application processes the target power allocation strategy through a power allocation algorithm based on a genetic algorithm based on the signal-to-noise ratio of each user terminal decoding public information, the realization rate of the private data stream of each user terminal, and the eavesdropping constraint condition of the constructive interference construction condition based on the base station's transmission signal, and the process is as follows:

[0164] Based on the above description of the user's QoS constraints and the eavesdropper's security constraints, the power minimization problem can be expressed as:

[0165] PP

[0166] st c，k ≥Γ k

[0167]

[0168] c≥0

[0169] Among them, R k is the minimum rate requirement of target user k, Γ k and Γ e are the SINR thresholds of the target user terminal k and the eavesdropping terminal respectively.

[0170] Constraints: γ c，k ≥Γ k Represents the QoS requirements of each user end and ensures the reliability of communication.

[0171] Constraints: Ensure that public information cannot be deciphered by eavesdroppers.

[0172] Constraints: Indicates the minimum rate constraint for all users.

[0173] Constraints:

[0174]

[0175] This constraint ensures that any private information received by a user remains within the region in which it was formed (the constructed region).

[0176] The constraints are:

[0177]

[0178] This constraint keeps the noise-free information received by the eavesdropping end outside its decoding region (outside the constructed region), preventing the information from being accurately decoded.

[0179] Constraint: c ≥ 0 ensures that the public information rate of each user terminal is non-negative.

[0180] CRSMA precoding problem optimization:

[0181] Before solving problem P1, we first simplify the optimization objectives and constraints. The information S is encoded as a unit positive vector, so the optimization objective of minimizing the transmit power can be written as:

[0182]

[0183] For convenience, assume that σ k =σ e =σ. Constraints:

[0184]

[0185] The received signal is expressed in polar coordinates. After triangular transformation, the constraint is equivalent to the following two constraints:

[0186]

[0187] Wherein, α represents the difference between the phase of the noise-free signal actually received by the user end and the phase of the ideal received signal.

[0188] Similarly, for the eavesdropping end, the constraints are:

[0189]

[0190] This constraint is equivalent to the following two constraints:

[0191] or,

[0192]

[0193] Among them, α e It represents the difference between the phase of the noise-free signal actually received from the eavesdropping end and the phase of the ideal received signal.

[0194] The optimization problem P1 can be transformed into:

[0195] P2

[0196]

[0197] or,

[0198]

[0199] The optimization objective of problem P2 is convex in nature, but the existence of constraints makes the entire problem a non-convex optimization problem. In addition, the intricate coupling relationship between multiple optimization variables also increases the complexity of finding a solution. In order to solve this type of coupled variable problem, the usual practice is to use the alternating optimization (AO) algorithm. In this case, if we first fix the variable c and then solve p k and p c , and then the obtained p k and p c Substitute into problem P2. ||P|| 2 It depends entirely on the variable p k and p c Therefore, p k and p c Substituting into problem P2 again, we can find that the value objective function has been fixed and cannot be further optimized.

[0200] Only based on constraints:

[0201]

[0202] or,

[0203]

[0204] Get each c k The allowed range is c k，mi n≤c k ≤c k，max , but it is impossible to determine c k To circumvent this problem, it is necessary to eliminate the optimization variable c from the optimization problem P2. By studying the constraints:

[0205] or,

[0206]

[0207] It can be determined that k The lower limit is:

[0208]

[0209] The c k The equation for the lower limit of c is the same as the following constraint k Upper limit expressions are merged:

[0210]

[0211] Combined to get:

[0212]

[0213] The optimization problem P2 can be transformed into problem P3:

[0214] P3

[0215] The constraints st are as follows:

[0216]

[0217] Given the non-convexity of problem P3, traditional optimization algorithms, especially those that rely on gradient information for local search, may converge to a local optimum, which makes it very difficult to find the global optimum in the entire solution space. To meet this challenge, this application uses a genetic algorithm (GA). Inspired by natural selection, the genetic algorithm provides a global search heuristic suitable for complex solution spaces. The execution process of the power allocation algorithm based on the genetic algorithm is as follows:

[0218] Initialization: Population size P size , the number of elites E count , the maximum number of generations G max , fitness tolerance T fun . Transmission symbol s k , iteration number i=1, GA iteration number j=1.

[0219] Simulation parameters: number of cycles N max , signal-to-noise ratio threshold Γ, Γ e , Gaussian white noise σ, σ e .

[0220] step:

[0221] (1) When i≤N max (2) Randomly generate channel h k and h e ; (3) Initialize the population; (4) Repeat; (5) Define the fitness function fitness(P) according to the constraints of the objective function; (6) Select the first E count Individuals are selected as elite individuals; (7) Select the parent P′ with high fitness j , use single-point crossover to generate offspring P″ j ; (8) Use Gaussian mutation on the offspring to obtain P″′ j ; (9) Formation of a new population P j =P″′ j∪elite; (10) j = j + 1; (11) until j ≥ G max or fitness(P)≥T fun , select the individual with the highest fitness function value as the optimal solution P for problem P3 i ; (12) i = i + 1; (13) complete the current operation (endwhile); (14) take the average value

[0222] In some embodiments, the present application conducts a large number of simulation experiments on the MU-MISO system with an eavesdropper to evaluate the performance of the proposed CRSMA scheme. Specifically, the BS is equipped with 3 antennas and there are 2 single-antenna legitimate users. The channels between the BS and the user and between the BS and the eavesdropper are simulated as independent and identically distributed (iid) path loss models combined with Rayleigh fading channels, with large-scale fading exponent α=2 and fading coefficient β=10 -3 . The distance between the BS and the user is set to vary from 25m to 300m, and the distance between the BS and the eavesdropper is fixed at 250m. For simplicity, the noise power of all users and eavesdroppers is set to σ = -110dBm. In terms of transmission signals, quadrature phase shift keying (QPSK) modulation with a modulation order of M = 4 is used, and the user's transmission symbols are independently selected from the constellation diagram. Different scenarios are simulated by adjusting factors such as user distance and the signal-to-noise ratio threshold of users and eavesdroppers. All simulation results are based on the average of 1000 independent channel measurements.

[0223] like Figure 2B As shown, the relationship between the total transmission power, the public information transmission power and the private information transmission power and the distance between the base station and the user and the user signal-to-noise ratio threshold is demonstrated. Figure 2B The x, y, and z axes represent the distance d between the base station and the user, respectively. k , user signal-to-noise ratio threshold Γ k and transmission power, the eavesdropper's signal-to-noise ratio threshold Γ e Set to 3dB. Figure 2B It can be seen that as d k and Γ k With the increase of , the three transmission powers all show a steady upward trend. It is worth noting that the private transmission power is always lower than the public transmission power, because users must meet the signal-to-noise ratio constraint to successfully decode the public information.

[0224] Figure 2C It shows that in R k=The ratio of the public rate and private rate to the total system rate at a fixed total transmission rate of 3 bits / s. As the signal-to-noise ratio increases from 3dB to 8dB, the public information rate ratio gradually increases, while the private information rate ratio gradually decreases. This is consistent with Figure 2B The results in Figure 2 are consistent with those in Figure 2, namely that the power allocation to public information increases with increasing SNR, leading to a corresponding increase in the public information rate. The proportion of the public information rate increases with increasing SNR, indicating that higher SNR levels can more effectively support the transmission of public data, which is essential for applications such as broadcast information or collaborative communications. In contrast, the decrease in the proportion of the private information transmission rate indicates that as the SNR increases, the proportion of single user data transmission in the entire communication becomes smaller and smaller. This trend highlights the potential of the CRSMA scheme to more efficiently utilize spectrum and its ability to dynamically adapt to different SNR conditions.

[0225] To further evaluate the performance of the proposed CRSMA scheme, a comparative analysis is performed with a baseline scheme that does not use CI encoding. Figure 2D The figure shows the relationship between the average total transmit power, public transmit power, and private transmit power of the two schemes and the distance under the condition of SNR = 5dB. It can be seen that the transmit power of the precoding scheme increases with d k Under QoS constraints, the total transmit power of the benchmark scheme is always higher than that of the CRSMA scheme.

[0226] In order to compare the power consumption more comprehensively, the transmit power of the two schemes with different Γ k For simplicity, we set all users Γ k =Γ. Figure 2E As shown in Figure 2, the transmit power of the CRSMA scheme is always lower than that of the benchmark scheme. When the SNR value is 3dB and 4dB, the total transmit power of the two schemes is very close. As Γ gradually increases, the increase rate of the transmit power of the benchmark scheme is significantly faster than that of the CRSMA scheme.

[0227] To further illustrate the effectiveness of the CRSMA scheme, the impact of the CRSMA scheme on the private transmission power allocation between individual users is analyzed, such as Figure 2F This study includes two simulation sets, each of which contains a system consisting of three groups of users. In the first case, the distance between the user and the base station is set to 20m, 100m, and 200m respectively; in the second case, the distance is increased to 50m, 150m, and 250m respectively. Figure 2FAs can be seen in , the increase in total distance in the latter case requires more private power to be allocated to each user compared to the former case. For a single simulation, the CRSMA scheme shows a clear balance in power allocation among the three users, almost independent of distance, which is in sharp contrast to the traditional NOMA system. By designing the CI vector precoding of the private symbols, the scheme enables each user to transform interference from other users into beneficial signals, thereby enhancing their received information. Therefore, users with weaker channels do not have to increase their transmission power to overcome channel degradation as in the traditional NOMA system.

[0228] exist Figure 2G-1 , Figure 2G-2 , Figure 2G-3 and Figure 2H-1 , Figure 2H-2 , Figure 2H-3 In the figure, the interaction between user 1 and the eavesdropper in three different Γ and Γ is described. e The received signal points under the following conditions. Specifically, 1) Γ=0dB, Γ=4dB and Γ=8dB; 2) Γ e =-4dB, Γ e = 0dB and Γ e =4dB. Blue and red represent the received signals of user 1 and the eavesdropper, respectively. It is observed that the signals received by the user are always within the constructed area and are mostly concentrated near the boundary of the constructed area, which is consistent with the optimization goal of this application, which is to minimize the transmission power to save energy. The signal received by the eavesdropper is located in the non-constructed area. Since the present application makes full use of the entire non-constructed area, the received signal points are scattered near the origin and are evenly distributed in the four quadrants, showing no special patterns that can be exploited by eavesdroppers. Therefore, even if the eavesdropper uses a complex blind detector or classifier, it is difficult to effectively classify the symbols, which greatly improves the security of the communication. Compare Figure 2G-1 , Figure 2G-2 , Figure 2G-3 and Figure 2H-1 , Figure 2H-2 , Figure 2H-3 ,As the user’s SNR threshold increases, the points received by the eavesdropper become more scattered and farther from the boundary of the built area; ,As the eavesdropper’s SNR threshold increases, the receiving points also become more scattered, but closer to the boundary of the user’s built area, which may increase the risk of the eavesdropper correctly decoding the private information.

[0229] It should be noted that the method of the embodiment of the present application can be performed by a single device, such as a computer or server. The method of this embodiment can also be applied to a distributed scenario and completed by multiple devices cooperating with each other. In the case of such a distributed scenario, one of the multiple devices can only perform one or more steps in the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the described method.

[0230] It should be noted that the above describes some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recorded in the claims can be performed in an order different from that in the above embodiments and still achieve the desired results. In addition, the processes depicted in the accompanying drawings do not necessarily require the specific order or continuous order shown to achieve the desired results. In some embodiments, multitasking and parallel processing are also possible or may be advantageous.

[0231] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides a signal transmission device of rate division multiple access based on constructed interference.

[0232] refer to Figure 3 The signal transmission device of rate division multiple access based on structured interference is arranged in a signal transmission system, the system includes a controller, a base station, an eavesdropping terminal and a plurality of user terminals, and the device includes:

[0233] The base station 301 is configured to obtain user data and pre-coded data corresponding to the user data, and process the user data and the pre-coded data through a transmission signal determination algorithm to obtain a transmission signal of the base station;

[0234] The user terminal 302 is configured to use each of the multiple user terminals as a target user terminal, the target user terminal is processed by a user terminal receiving signal determination algorithm based on the transmission signal of the base station to obtain a received signal of the target user terminal; based on the received signal of the target user terminal, the signal-to-noise ratio of the public information decoded by the user terminal is processed by a user terminal decoding signal-to-noise ratio determination algorithm to obtain the signal-to-noise ratio of the public information decoded by the target user terminal, and the target user terminal is processed by a user terminal private data stream realization rate determination algorithm based on the received signal of the target user terminal to obtain the realization rate of the private data stream of the target user terminal; based on the received signal of the target user terminal, the constructive interference construction condition is determined by processing the constructive interference algorithm;

[0235] The eavesdropping end 303 is configured to process the base station's transmitted signal through the eavesdropping end's received signal determination algorithm to obtain the eavesdropping end's received signal; process the eavesdropping end's received signal through the eavesdropping end's decoded public information's signal-to-noise ratio determination algorithm to obtain the eavesdropping end's decoded public information's signal-to-noise ratio; and determine the eavesdropping constraint condition based on the eavesdropping end's received signal through the interference control algorithm;

[0236] The controller 304 is configured to construct an objective function based on the transmitted signal of the base station, construct a signal-to-noise ratio constraint condition based on the signal-to-noise ratio of the public information decoded by each user terminal, and construct a rate constraint condition using the implementation rate of the private data stream of each user terminal. Based on the signal-to-noise ratio constraint condition, the rate constraint condition, the constructive interference construction condition and the eavesdropping constraint condition, the objective function is processed by a power allocation algorithm of a genetic algorithm to determine a target power allocation strategy when the value of the objective function is minimized, and the base station and the multiple user terminals are controlled to perform a signal transmission process according to the target power allocation strategy.

[0237] For the convenience of description, the above device is described in terms of functions divided into various modules. Of course, when implementing the present application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0238] The device of the above embodiment is used to implement the corresponding rate division multiple access signal transmission method based on constructed interference in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0239] Based on the same inventive concept, corresponding to any of the above-mentioned embodiments and methods, the present application also provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the signal transmission method of rate division multiple access based on constructed interference described in any of the above embodiments is implemented.

[0240] Figure 4 A more specific schematic diagram of the hardware structure of an electronic device provided in this embodiment is shown, and the device may include: a processor 401, a memory 402, an input / output interface 403, a communication interface 404, and a bus 405. The processor 401, the memory 402, the input / output interface 403, and the communication interface 404 are connected to each other in communication within the device through the bus 405.

[0241] The processor 401 can be implemented by a general-purpose CPU (Central Processing Unit), 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 this specification.

[0242] The memory 402 can be implemented in the form of ROM (Read Only Memory), RAM (Random Access Memory), static storage device, dynamic storage device, etc. The memory 402 can store an operating system and other application programs. When the technical solutions provided in the embodiments of this specification are implemented by software or firmware, the relevant program codes are stored in the memory 402 and called and executed by the processor 401.

[0243] The input / output interface 403 is used to connect the input / output module to realize information input and output. The input / output module can be configured in the device as a component (not shown in the figure), or it can be externally connected to the device to provide corresponding functions. The input device may include a keyboard, a mouse, a touch screen, a microphone, various sensors, etc., and the output device may include a display, a speaker, a vibrator, an indicator light, etc.

[0244] The communication interface 404 is used to connect a communication module (not shown) to realize communication interaction between the device and other devices. The communication module can realize communication through a wired mode (such as USB, network cable, etc.) or a wireless mode (such as mobile network, WIFI, Bluetooth, etc.).

[0245] The bus 405 comprises a pathway for transmitting information between the various components of the device (eg, the processor 401 , the memory 402 , the input / output interface 403 , and the communication interface 404 ).

[0246] It should be noted that, although the above device only shows the processor 401, the memory 402, the input / output interface 403, the communication interface 404 and the bus 405, in the specific implementation process, the device may also include other components necessary for normal operation. In addition, it can be understood by those skilled in the art that the above device may also only include the components necessary for implementing the embodiments of the present specification, and does not necessarily include all the components shown in the figure.

[0247] The electronic device of the above embodiment is used to implement the corresponding rate division multiple access signal transmission method based on constructed interference in any of the above embodiments, and has the beneficial effects of the corresponding method embodiment, which will not be repeated here.

[0248] Based on the same inventive concept, corresponding to any of the above-mentioned embodiment methods, the present application also provides a non-transitory computer-readable storage medium, wherein the non-transitory computer-readable storage medium stores computer instructions, and the computer instructions are used to enable the computer to execute the signal transmission method of rate division multiple access based on constructed interference as described in any of the above embodiments.

[0249] The computer-readable medium of this embodiment includes permanent and non-permanent, removable and non-removable media, and information storage can be implemented by any method or technology. Information can be computer-readable instructions, data structures, modules of programs, or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, read-only compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device.

[0250] The computer instructions stored in the storage medium of the above embodiment are used to enable the computer to execute the signal transmission method of rate division multiple access based on constructed interference as described in any of the above embodiments, and have the beneficial effects of the corresponding method embodiments, which will not be repeated here.

[0251] A person skilled in the art should understand that the discussion of any of the above embodiments is merely illustrative and is not intended to imply that the scope of the present application is limited to these examples. In line with the concept of the present application, the technical features in the above embodiments or different embodiments may be combined, the steps may be implemented in any order, and there are many other variations of the different aspects of the embodiments of the present application as described above, which are not provided in detail for the sake of simplicity.

[0252] In addition, to simplify the description and discussion, and in order not to make the embodiments of the present application difficult to understand, the known power supply / ground connection with the integrated circuit (IC) chip and other components may or may not be shown in the provided drawings. In addition, the device can be shown in the form of a block diagram to avoid making the embodiments of the present application difficult to understand, and this also takes into account the fact that the details of the implementation of these block diagram devices are highly dependent on the platform to be implemented in the embodiments of the present application (that is, these details should be fully within the scope of understanding of those skilled in the art). In the case of elaborating specific details (e.g., circuits) to describe exemplary embodiments of the present application, it is obvious to those skilled in the art that the embodiments of the present application can be implemented without these specific details or when these specific details are changed. Therefore, these descriptions should be considered to be illustrative rather than restrictive.

[0253] Although the present application has been described in conjunction with specific embodiments of the present application, many replacements, modifications and variations of these embodiments will be apparent to those skilled in the art from the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may use the embodiments discussed.

[0254] The embodiments of the present application are intended to cover all such substitutions, modifications and variations that fall within the broad scope of the present application. Therefore, any omissions, modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the embodiments of the present application should be included in the protection scope of the present application.

Claims

1. A signal transmission method of rate division multiple access based on structured interference, characterized in that: Applied to a signal transmission system, the system includes a controller, a base station, an eavesdropping terminal and multiple user terminals, and the method includes: The base station acquires user data and pre-coded data corresponding to the user data, and processes the user data and the pre-coded data through a transmission signal determination algorithm to obtain a transmission signal of the base station; Each of the multiple user terminals is used as a target user terminal, and the target user terminal processes the received signal of the target user terminal based on the sent signal of the base station through the user terminal receiving signal determination algorithm to obtain a received signal of the target user terminal; The target user terminal processes the received signal of the target user terminal through a signal-to-noise ratio determination algorithm of the user terminal decoding public information to obtain a signal-to-noise ratio of the public information decoded by the target user terminal, and the target user terminal processes the received signal of the target user terminal through a user terminal private data stream realization rate determination algorithm to obtain a realization rate of the private data stream of the target user terminal; The eavesdropping end processes the transmission signal of the base station through the reception signal determination algorithm of the eavesdropping end to obtain the reception signal of the eavesdropping end; The eavesdropping end processes the received signal of the eavesdropping end through a signal-to-noise ratio determination algorithm for decoding public information by the eavesdropping end to obtain a signal-to-noise ratio of the public information decoded by the eavesdropping end; The target user end processes the received signal of the target user end through a constructive interference algorithm to determine a constructive interference construction condition; The eavesdropping end processes the received signal of the eavesdropping end through an interference control algorithm to determine the eavesdropping constraint condition; The controller constructs an objective function based on the transmitted signal of the base station, constructs a signal-to-noise ratio constraint condition based on the signal-to-noise ratio of the public information decoded by each user terminal, and constructs a rate constraint condition using the implementation rate of the private data stream of each user terminal. Based on the signal-to-noise ratio constraint condition, the rate constraint condition, the constructive interference construction condition and the eavesdropping constraint condition, the objective function is processed by a power allocation algorithm of a genetic algorithm to determine a target power allocation strategy when the value of the objective function is minimized, and the base station and the multiple user terminals are controlled to perform a signal transmission process according to the target power allocation strategy.

2. The method according to claim 1, characterized in that The processing based on the user data and the pre-coded data by a transmission signal determination algorithm to obtain the transmission signal of the base station includes: The base station determines the transmission signal of the base station based on the user data and the pre-coded data by the following formula: Where X represents the signal sent by the base station, s represents user data, S = [s c , s1, s2, ..., s K ] T , P represents the pre-coded data, P = [p c , p1, p2, ..., p K ], p c ∈C N×1 It is the public data stream s in the user data c The pre-encoder data, p k ∈C N×1 is the private data stream s in the kth user data k The pre-encoder data of , k is the index of the user end, 3. The method according to claim 1, characterized in that The target user terminal processes the transmitted signal of the base station through a received signal determination algorithm of the user terminal to obtain a received signal of the target user terminal, including: The target user terminal determines the received signal of the target user terminal based on the transmitted signal of the base station by using the following formula: Among them, y k represents the received signal of the target user end k, h k ∈C N×1 is the channel between the base station and the target user terminal k, X represents the sending signal of the base station, is the additive Gaussian white noise at the target user end k, p c ∈C N×1 It is the public data stream s in the user data c The pre-encoder data, p i is the private data stream S in the i-th user data i The pre-encoder data, is the user-side index, 4. The method according to claim 1, characterized in that: The target user terminal processes the received signal of the target user terminal by using a signal-to-noise ratio determination algorithm of the public information decoded by the user terminal to obtain a signal-to-noise ratio of the public information decoded by the target user terminal, including: The target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal. k , and the public data stream S in the user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The target user terminal is based on the channel h between the base station and the target user terminal k k , and public data streams in user data c The pre-encoder data p c , the private data stream s in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The signal-to-noise ratio of the public information decoded by the target user terminal is determined by the following formula: Among them, γ c，k represents the signal-to-noise ratio of the public information decoded by the target user terminal, is the user-side index, i represents the order of the index of the client.

5. The method according to claim 1, characterized in that The target user terminal processes the received signal of the target user terminal through a user terminal private data stream realization rate determination algorithm based on the received signal of the target user terminal to obtain the realization rate of the private data stream of the target user terminal, including: The target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal. k , and the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The target user terminal is based on the channel h between the base station and the target user terminal k k , and the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the target user end k The signal-to-noise ratio of the private information decoded by the target user terminal is determined by the following formula: Among them, γ p，k represents the signal-to-noise ratio of the target user end decoding private information, is the user-side index, i represents the order of the index of the user end; The target user terminal determines the realization rate of the private data stream of the target user terminal through the following formula based on the signal-to-noise ratio of the private information decoded by the target user terminal: R p，k =log2(1+γ p，k ) Among them, R p，k represents the realization rate of the private data flow of the target user end, γ p，k Indicates the signal-to-noise ratio of the target user end decoding private information.

6. The method according to claim 1, characterized in that The eavesdropping end processes the sent signal of the base station through a received signal determination algorithm of the eavesdropping end to obtain the received signal of the eavesdropping end, including: The eavesdropping end determines the received signal of the eavesdropping end based on the transmitted signal of the base station by using the following formula: Among them, y e represents the received signal of the eavesdropping end, h e ∈C N×1 is the channel between the base station and the eavesdropping end e, X represents the sending signal of the base station, is the additive white Gaussian noise at the eavesdropping end e, p c ∈ N×1 It is the public data stream s in the user data c The pre-encoder data, p k ∈C N×1 is the private data stream S in the kth user data k The pre-encoder data, is the user-side index, 7. The method according to claim 1, characterized in that The eavesdropping end processes the received signal of the eavesdropping end through a signal-to-noise ratio determination algorithm for decoding public information by the eavesdropping end to obtain a signal-to-noise ratio of the public information decoded by the eavesdropping end, including: The eavesdropping end decodes the received signal of the eavesdropping end and determines the channel h between the base station and the eavesdropping end e from the received signal of the eavesdropping end e , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the eavesdropping end e The eavesdropping end decodes the received signal of the eavesdropping end and determines the channel h between the base station and the eavesdropping end e from the received signal of the eavesdropping end. e , and public data streams in user data c The pre-encoder data p c , the private data stream S in the i-th user data i The pre-encoder data p i , additive white Gaussian noise at the eavesdropping end e The signal-to-noise ratio of the public information decoded by the eavesdropping end is determined by the following formula: in, represents the signal-to-noise ratio of the public information decoded by the eavesdropping end, is the user-side index, i represents the order of the index of the client.

8. The method according to claim 1, characterized in that The target user end processes the received signal of the target user end through a constructive interference algorithm to determine a constructive interference construction condition, including: The target user terminal decodes the received signal of the target user terminal, and determines the channel h between the base station and the target user terminal k from the received signal of the target user terminal. k , the private data stream S in the i-th user data i The pre-encoder data p i , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane Additive Gaussian white noise at the target user end k The signal-to-noise ratio requirement of the target user terminal k is Γ k ; The target user terminal is based on the channel h between the base station and the target user terminal k k , the private data stream S in the i-th user data i The pre-encoder data p i , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane Additive Gaussian white noise at the target user end k The signal-to-noise ratio requirement of the target user terminal k is Γ k , the constructive interference construction condition is determined by the following formula: Where k represents the order of the client. is the user-side index, 9. The method according to claim 1, characterized in that: The eavesdropping end processes the received signal of the eavesdropping end through an interference control algorithm to determine the eavesdropping constraint condition, including: The eavesdropping end is based on the received signal y of the eavesdropping end e Decode the received signal y from the eavesdropping end e Determine the additive white Gaussian noise n at the eavesdropping end e e , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane The square root of the additive white Gaussian noise at the eavesdropping end e is σ e , the signal-to-noise ratio requirement of the eavesdropping end e is Γ e ; The eavesdropping end is based on the received signal y of the eavesdropping end e Decode the received signal y from the eavesdropping end e Determine the additive white Gaussian noise n at the eavesdropping end e e , the phase φ of the signal of the private information received by the target user k that the eavesdropper wants to eavesdrop on k , and the angle by which the received signal is rotated clockwise on the complex plane The square root of the additive white Gaussian noise at the eavesdropping end e is σ e , the signal-to-noise ratio requirement of the eavesdropping end e is Γ e , the eavesdropping constraint condition is determined by the following formula:

10. An electronic device comprising a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the program, the method according to any one of claims 1 to 9 is implemented.

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