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

Abstract

The present application provides a signal transmission method and related equipment for rate division multiple access based on constructed interference. Taking into account the existence of eavesdropping terminals, from the perspective of physical layer security, a constructive interference algorithm is used for processing to determine constructive interference construction conditions. The interference control algorithm is combined for processing to determine eavesdropping constraint conditions, and the signal received by the eavesdropping terminal is controlled 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. Then, according to such a target power allocation strategy, the base station and multiple user terminals are controlled to execute the signal transmission process, thereby avoiding the problem of high energy consumption.

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 based on rate division multiple access (RDMA) with 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 face unprecedented challenges, including achieving higher data throughput, ensuring more reliable connections, accommodating large-scale device connections, and addressing the heterogeneity of Quality of Service (QoS) requirements. This has led to more significant issues with data leakage and high energy consumption. Therefore, preventing data leakage and excessive energy consumption has become a pressing issue. Summary of the Invention

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

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

[0005] 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 using a transmission signal determination algorithm to obtain a transmission signal of the base station;

[0006] Each of the plurality of user terminals is used as a target user terminal, and the target user terminal processes the signal sent by the base station using a user terminal reception signal determination algorithm to obtain a reception signal of the target user terminal;

[0007] The target user terminal processes, based on a received signal of the target user terminal, a signal-to-noise ratio determination algorithm for user terminal decoding of 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, based on the received signal of the target user terminal, a realization rate determination algorithm for a user terminal private data stream to obtain a realization rate of the private data stream of the target user terminal;

[0008] The eavesdropping end processes the base station's transmitted signal through the eavesdropping end's received signal determination algorithm to obtain the eavesdropping end's received signal;

[0009] 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;

[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 an 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 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. Based on the signal-to-noise ratio constraint, the rate constraint, the constructive interference construction condition, and the eavesdropping constraint, the controller processes the objective function through a power allocation algorithm of a genetic algorithm, 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.

[0013] Based on the same inventive concept, the second aspect of this 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] As can be seen from the above, 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 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. BRIEF DESCRIPTION OF THE DRAWINGS

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

[0016] Figure 1 This is a flow chart 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 Schematic diagram of the relationship between the total transmit power, public information transmit power, and private information transmit 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 showing the proportions 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 Schematic diagram of the relationship between the average total transmit power, public transmit power, and private transmit power and distance for different schemes under the condition of SNR=5dB in an embodiment of the present application;

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

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

[0023] Figure 2G-1 This is 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 This is a second schematic diagram of received signal points of user 1 and an eavesdropper under different conditions according to an embodiment of the present application;

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

[0026] Figure 2H-1 This is a fourth schematic diagram of received signal points of user 1 and an eavesdropper under different conditions according to an embodiment of the present application;

[0027] Figure 2H-2 This is a fifth schematic diagram of received signal points of user 1 and an eavesdropper under different conditions according to an embodiment of the present application;

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

[0029] Figure 3 A structural block diagram of signal transmission 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 this application more clear, this 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 have the usual meanings understood by people with ordinary skills in the field to which this application belongs. The "first", "second" and similar words used in the embodiments of the present application do not indicate any order, quantity or importance, but are only used to distinguish different components. "Include" or "comprise" and similar words mean that the elements or objects appearing before 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 may 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 this 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 a user's active request, a prompt message is sent to the user to clearly inform the user that the operation requested will require the acquisition and use of 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 this application based on the prompt message.

[0035] As an optional but non-limiting implementation, in response to a 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. Furthermore, the pop-up window may also contain a selection control for the user to select "agree" or "disagree" to provide personal information to the electronic device.

[0036] It is understandable that the above notification and user authorization process are merely illustrative and do not constitute a limitation on the implementation of this application. Other methods that comply with relevant laws and regulations may also be applied to the implementation 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 face unprecedented challenges, including achieving higher data throughput, ensuring more reliable connections, accommodating large-scale device connections, and addressing the heterogeneity of Quality of Service (QoS) requirements. This has led to more significant data leakage and high energy consumption. Physical layer security (PLS), unlike traditional encryption methods, leverages the inherent randomness of wireless channels, offering performance advantages in terms of computational complexity and adaptability to heterogeneous environments.

[0038] Multiple access (MA) technology is at the core of wireless communications. Traditionally, multiple access schemes are categorized into two types: orthogonal and non-orthogonal. However, this classification does not 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). At the transmitter, information is divided into a public stream and a private stream. The public stream carries information for decoding by all users, while the private stream is targeted at specific users. In recent years, the following research on RSMA has been conducted in related technologies:

[0039] The problem of maximizing the total confidentiality spectrum efficiency (SE) for two user classes in an RSMA system is considered: one class of users whose private information flows require information security protection, and the other class of users who do not. Alternatively, the research focuses on RSMA-based communication systems under transmission power constraints, aiming to maximize the minimum secure rate (MSR) of legitimate users. Alternatively, artificial noise (AN) is introduced into RSMA, and the problem of maximizing the minimum user rate under security constraints is addressed. Alternatively, RSMA is combined with a smart reflecting surface (RIS) to propose an energy efficiency optimization algorithm for 6G multi-cellular communication systems. Current research shows that RSMA surpasses SDMA and NOMA in terms of degrees of freedom (DoF), efficiency, versatility, flexibility, robustness, and low latency. Alternatively, constructive interference (CI) precoding is an innovative symbol-level precoding scheme. Unlike traditional linear precoding methods such as minimum mean square error (MMSE), maximum ratio transmission (MRT), and zero forcing (ZF), CI leverages channel state information (CSI) and inherent data symbol information to locate interfering signals within the constructive interference region of the relevant symbols, thereby converting multiuser interference (MUI) into useful received power. By leveraging spatial and symbol-level degrees of freedom (DoF), CI significantly improves symbol error rate (SER) performance and reduces transmission power. Closed-form expressions for CI are proposed for various modulation schemes, including phase-shift keying (PSK) and quadrature amplitude modulation (QAM), under both strict and non-strict phase rotation. Alternatively, a secure precoding algorithm based on constructive-destructive (CD) interference is proposed for scenarios involving a single eavesdropper, enabling energy-efficient secure information transmission and secure wireless power transfer (SWIPT). Alternatively, an existing CD-based precoding scheme is modified to fully utilize the entire destructive interference (DI) region, effectively countering intelligent eavesdroppers. Alternatively, symbol-level precoding is employed to enhance the security of multi-user multiple-input, multiple-output (MU-MIMO) communication systems when the eavesdropper's CSI is unknown. CI precoding has been integrated with various wireless systems, including massive MIMO systems, smart metasurface (RIS)-assisted systems, and non-orthogonal multiple access (NOMA), and has shown significant potential in enhancing physical layer security, reducing transmission power, and improving summation 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 for utilizing CI is proposed, which uses the existing strict phase rotation-derived closed-form CI coding to process private information and calculate the traversal and rate of RS, but does not consider the presence of eavesdroppers.

[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. This application uses CI precoding for private information in the RSMA system, allowing each user to convert interference into useful information during decoding, thereby enhancing their decoding capabilities. (2) The energy consumption of existing RSMA technology is too high, and there is little research on its encoding method. This 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. 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 the security of the data.

[0042] Based on the above background, this application proposes a multi-user multiple-input single-output (MU-MISO) RSMA system (CRSMA) scheme assisted by CI technology, and proposes a downlink CRSMA system model that includes eavesdroppers to supplement the traditional RSMA multi-user interference and data leakage problems. In addition, it also proposes a problem statement for minimizing the base station transmit 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 the transmission power to achieve green and secure RSMA.

[0043] In response to the problem of multi-user interference in wireless communication scenarios, this application adopts 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 coding methods in RSMA systems and the problem of excessive energy consumption of RSMA, this application proposes a problem statement of minimizing the base station transmission power, which reduces 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 light-weight 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 for keys without assuming that the attacker has limited computing power. (4) Multi-User Multiple Input Single Output (MU-MISO): A MU-MISO system is a wireless communication system that efficiently utilizes wireless resources. It achieves spatial diversity and spatial multiplexing by equipping the transmitter (called a base station or access point) with multiple antennas, thereby improving communication performance and spectrum efficiency. This system can simultaneously serve multiple single-antenna user terminals (called user equipment) within the same frequency band at the same time, significantly improving wireless communication performance.

[0045] An 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 into account the existence of the eavesdropping terminal, from the perspective of physical layer security, a 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 signal received by the eavesdropping terminal is controlled 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, and thus the eavesdropping terminal cannot 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, which can avoid the problem of high energy consumption.

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

[0047] In 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, a key node in the wireless communication network, is responsible for communicating with user devices (such as mobile phones and laptops). During 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 messages, and video streams. These data are generated by the user device and need to be transmitted to other devices or network nodes via the wireless communication network.

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

[0050] After receiving user data and preamble data, the base station processes it using a transmission signal determination algorithm. This algorithm determines the optimal transmission signal based on the current communication environment (e.g., signal interference, noise level, channel conditions) and system requirements (e.g., data rate, bit error rate). This process may involve signal optimization, resource allocation, power control, and other aspects to ensure efficient and reliable data transmission to the target user device.

[0051] After processing by the transmit signal determination algorithm, the base station ultimately generates one or more transmit signals. These transmit signals are the result of encoding and modulating the original user data and pre-coded data. They are designed to adapt to the current communication environment and system requirements. The base station then transmits these transmit signals via an antenna into a wireless channel, allowing the user terminal to receive and decode the original user data.

[0052] In step 102, each of the plurality of user terminals is used as a target user terminal. The target user terminal processes the signal sent by the base station using a user terminal receiving signal determination algorithm to obtain a receiving signal of the target user terminal.

[0053] In this step, the base station sends signals to all user terminals. These signals contain the 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 effects, and interference during transmission.

[0054] Each target user terminal processes the received signal using its own received signal determination algorithm. The goal is to extract useful information (i.e., the data destined for that 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 data even in the presence of noise and interference.

[0056] In step 103, the target user terminal processes the received signal of the target user terminal using a signal-to-noise ratio determination algorithm for user terminal decoding of public information to obtain a signal-to-noise ratio of the public information decoded by the target user terminal. The target user terminal also processes the received signal of the target user terminal using 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. This information is crucial for the normal operation of the system.

[0058] The signal-to-noise ratio (SNR) is the ratio of signal power to noise power and is an important indicator of communication system performance. A high SNR indicates better signal quality and a lower decoding error rate.

[0059] The target user terminal first receives signals from a base station or other transmitting source. It then processes these signals using the same SNR determination algorithm used for decoding public information on the user terminal to calculate the SNR for decoding public information. This algorithm may involve multiple steps, including signal demodulation, decoding, and noise estimation.

[0060] In multi-user wireless communication systems, a private data stream is a data stream that is sent exclusively to a specific user and remains confidential to other users. Private data streams are typically 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, and interference.

[0062] The target user end also calculates the achieved rate of its private data stream based on the received signal using the user end private data stream achieved rate determination algorithm. This algorithm may involve multiple aspects such as signal quality assessment, 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 eavesdropper refers to an unauthorized entity that attempts to intercept or monitor communications between the base station and the user terminal. This eavesdropper may be an attacking user device or entity, or some form of monitoring system.

[0065] To extract useful information from the base station's signal, the eavesdropper processes the received signal using its own received signal determination algorithm. This algorithm typically aims to separate the useful signal from noise and interference and recover the original transmitted 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 eavesdropper processes the received signal using the signal-to-noise ratio (SNR) algorithm used to determine the signal-to-noise ratio of public information decoded by the eavesdropper. This algorithm evaluates the ratio of signal to noise (i.e., the signal-to-noise ratio, SNR) when the eavesdropper attempts to decode public information. The SNR is an important indicator of signal quality; a high SNR means a clearer signal with less noise, making it easier to correctly decode.

[0069] By applying the above algorithm, an eavesdropper can calculate the signal-to-noise ratio (SNR) when attempting to decode a public message. This value is important to the eavesdropper because it indicates the likelihood of successful eavesdropping. If the SNR is high, the eavesdropper is more likely to successfully decode the message; if the SNR is low, decoding may fail or result in 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 target user terminal receives signals from the external environment, which may contain useful information (such as voice and data) or interference signals (such as noise and other communication signals). The quality of the received signal is crucial to the function and performance of the target user terminal.

[0072] Constructive interference algorithms are used to address interference components in received signals. They attempt to leverage these interfering signals, using specific processing methods, to positively impact the received useful signal. This is known as "constructive interference." The goal of these algorithms is to improve signal reception quality, potentially by boosting signal strength and increasing the signal-to-noise ratio.

[0073] By running a constructive interference algorithm, the target user end analyzes the received signal and determines how to constructively interfere under specific conditions. These conditions may include parameters such as the signal's frequency, phase, and strength, as well as how to adjust these parameters to maximize the effectiveness of constructive interference. Once these conditions are determined, the target user end can use this information to optimize its signal processing, 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 an eavesdropping constraint condition.

[0075] In this step, the interference control algorithm is used to prevent the legitimate communicating parties from intentionally inflicting interference on the eavesdropping end (to enhance the security of the 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] In step 108, the controller constructs an objective function based on the base station's transmitted signal, 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. Based on the signal-to-noise ratio constraint, the rate constraint, the constructive interference construction condition, and the eavesdropping constraint, the controller processes the objective function through 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 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] A genetic algorithm is an optimization algorithm that simulates natural selection and heredity. In this scenario, it is used to find the optimal power allocation strategy—that is, how to allocate base station transmit power to achieve optimal system performance while satisfying all the aforementioned conditions (including signal-to-noise ratio, private data flow rate, constructive interference structure, 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. 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 base station's transmit signal based on the user data and the pre-coded data using the following formula:

[0085]

[0086] Where x represents the base station's transmission signal, 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 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 W1, ..., W to K users respectively. K In RSMA, the information W k Divide into public part W c，k and private part W p，k . Common part W c，1 ,...,W c，K Merge into public information W c , and encodes it into a common stream s using the codebook shared by all users 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, while the public part is pre-encoded in a multicast manner, so the transmission signal at the BS (i.e. the base station's sending signal) is expressed as:

[0088]

[0089] Where s=[s c ,s1,s2,...,s K ] T , (i.e. user data), s k The unit standard M phase shift keying (PSK) modulation is used. 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 ,p1,p2,...,p K ] is the pre-encoder matrix (i.e. pre-encoded data). c ∈C N×1 It is 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, thereby ensuring 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 transmitted by the base station using 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 using the following formula:

[0093]

[0094] Among them, y k represents the received signal of target user terminal k, h k ∈C N×1 is the channel between the base station and the target user terminal k, X represents the base station's transmission signal, 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 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 terminal k, considering the Rayleigh block fading channel, and assuming that the channel state information (CSI) of the target user terminal and the eavesdropper is completely known at the BS; is the additive white Gaussian noise (AWGN) at the target user end k.

[0098] The user end's received signal determination algorithm enables the target user end to successfully acquire 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 using a signal-to-noise ratio determination algorithm for user terminal decoding public information to obtain a 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 Gaussian white 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 Gaussian white 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 user terminal.

[0104] In the above scheme, if Figure 2A As shown in the figure, at the receiving end (RSMAReceiver), each user end first treats all private information streams as noise and decodes the public information stream. Then, under the assumption of error-free decoding, it uses continuous interference cancellation (SIC) to remove the public information 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 using 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 =log2(1+γ c，k ) The achievable rate of public information is To ensure that all users can successfully decode public information. In addition, R 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 = [c1, c2, ..., 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 using an algorithm for determining the realization rate of the user terminal private data stream 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 Gaussian white 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 Gaussian white 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 terminal decoding private information, is the user-side index, i represents the order of the index of the user terminal.

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

[0115] R p，k =log2(1+γp，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 and decodes the public information stream. Then, under the assumption of error-free decoding, it uses Successive Interference Cancellation (SIC) to remove the public information 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. 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 =log2(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 using the following formula:

[0124]

[0125] 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 terminal e, X represents the base station's transmission signal, is the additive white Gaussian noise at the eavesdropping end e, p c ∈C N×1 It is the public data stream s in user data c The pre-encoder data, p k ∈C N×1is 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 at the eavesdropping end can be expressed as follows:

[0127]

[0128] Among them, h e ∈C N×1 is the channel between BS and 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 terminal decodes the received signal of the eavesdropping terminal and determines the channel h between the base station and the eavesdropping terminal e from the received signal of the eavesdropping terminal. 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 terminal decodes the received signal of the eavesdropping terminal and determines the channel h between the base station and the eavesdropping terminal e from the received signal of the eavesdropping terminal. 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 terminal is determined by the following formula:

[0133]

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

[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 and cannot 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 s 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 above method can quickly and accurately determine the signal-to-noise ratio of the public information decoded by the eavesdropping end.

[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 in 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 in 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] Among them, 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 is represented in the form of a complex plane (a) and explained using QPSK as an example (M = 4). k is the symbol that the target user k is interested in, and its complex plane coordinate is For QPSK modulation, s k The decision boundaries of are R axis and I axis. In order to quantify the QoS requirements, let Γ k is the signal-to-noise ratio requirement of target user terminal k. When the private information of other user terminals 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 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] It is necessary to design P 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. Projection in the direction. Figure 2A In the modulation constellation diagram, the signal received by the target user terminal 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 k After 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 in the complex plane The square root of the additive white Gaussian noise σ at the eavesdropping end e 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 in the complex plane The square root of the additive white Gaussian noise σ at the eavesdropping end e 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 eavesdropper can only receive information from the interference (red) area of ​​the user side, while the user side uses constructive interference construction conditions to store the received private information in the green area. Therefore, the eavesdropper cannot steal private information from the user side, thereby ensuring communication security.

[0163] In some embodiments, the controller of the present application determines the target power allocation strategy by processing the power allocation algorithm based on the power allocation algorithm based on the signal-to-noise ratio of each user terminal decoding public information of the base station's transmission signal, the implementation rate of the private data stream of each user terminal, and the eavesdropping constraint condition described in the constructive interference construction condition, 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] stγ 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 eavesdropping parties.

[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 eavesdropper 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 objective and constraints. The information S is encoded as a positive unit 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] Using polar coordinates to represent the received signal, after triangular transformation, this constraint is equivalent to the following two constraints:

[0186]

[0187] Here, α represents the phase difference between the noise-free signal actually received by the user end and 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 phase difference between the noise-free signal actually received from the eavesdropping end and 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 inherently convex, 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. To solve this type of coupled variable problem, the common 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 the problem into 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, that is, c k，mi n≤c k ≤c k，max , but cannot 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 c k The lower limit of:

[0208]

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

[0210]

[0211] Merge 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 address 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 top 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 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 the user distance and the signal-to-noise ratio threshold of the user and the eavesdropper. All simulation results are based on the average of 1000 independent channel measurements.

[0223] like Figure 2B As shown in FIG, 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 is shown. 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 As ,increases, the three transmission powers 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 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 proportion of the public information rate gradually increases, while the proportion of the private information rate gradually decreases. Figure 2BThe results in

[15] are consistent with those in

[16] , 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. Conversely, the decrease in the proportion of the private information transmission rate indicates that as the SNR increases, the proportion of individual 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 transmission power of the two schemes with different Γ k For simplicity, we set all users Γ k =Γ. Figure 2E As shown in the figure, the transmit power of the CRSMA scheme is always lower than that of the baseline scheme. At SNR values ​​of 3dB and 4dB, the total transmit power of the two schemes is very close. As Γ gradually increases, the transmit power of the baseline scheme increases 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. Figure 2F This study includes two simulation sets, each containing a system consisting of three groups of users. In the first case, the distances between the users and the base station are set to 20m, 100m, and 200m respectively; in the second case, the distances are increased to 50m, 150m, and 250m respectively. Figure 2FAs can be seen in the figure, the increased total distance in the latter case requires more private power to be allocated to each user compared to the former. In a single simulation, the CRSMA scheme exhibits a clear balance in power allocation among the three users, almost independent of distance, in stark 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 a beneficial signal, thereby enhancing their received information. As a result, users with weaker channels do not have to increase their transmission power to overcome channel degradation, as is required in traditional NOMA systems.

[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 two eavesdroppers are described in three different Γ and Γ. e The received signal points under the following conditions: 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 located 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 this 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 the eavesdropper. 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. Comparison 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 constructed area; as the eavesdropper’s SNR threshold increases, ,the receiving points also become more scattered, but closer to the boundary of the user’s ,constructed area, which may increase the risk of the eavesdropper correctly decoding ,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 in a distributed scenario and performed by multiple devices working together. In such a distributed scenario, one of the multiple devices may only perform one or more steps of the method of the embodiment of the present application, and the multiple devices will interact with each other to complete the method.

[0230] It should be noted that the above description is limited to some embodiments of the present application. Other embodiments are within the scope of the appended claims. In some cases, the actions or steps recited in the claims may be performed in an order different from that described in the above embodiments and still achieve the desired results. Furthermore, the processes depicted in the accompanying drawings do not necessarily require the specific order or sequential order shown to achieve the desired results. In certain 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 provided in a signal transmission system, the system including 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 using 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 performing processing based on the base station's transmitted signal using a user terminal received signal determination algorithm to obtain a received signal of the target user terminal; performing processing based on the target user terminal's received signal using a user terminal decoded public information signal-to-noise ratio determination algorithm to obtain a signal-to-noise ratio of the target user terminal decoded public information; and performing processing based on the target user terminal's received signal using a user terminal private data stream implementation rate determination algorithm to obtain an implementation rate of the target user terminal's private data stream; and determining a constructive interference construction condition based on the target user terminal's received signal using a constructive interference algorithm.

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

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

[0237] For the convenience of description, the above devices are described as being divided into various modules according to their functions. Of course, when implementing this application, the functions of each module can be implemented in the same or multiple software and / or hardware.

[0238] The apparatus 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 described in detail 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 runnable on the processor. When the processor executes the program, it implements the signal transmission method of rate division multiple access based on constructed interference described in any of the above embodiments.

[0240] Figure 4 A more specific hardware structure diagram of an electronic device provided in this embodiment is shown. 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 communicatively connected to each other within the device via the bus 405.

[0241] The processor 401 can be implemented using 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 devices, dynamic storage devices, 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 through software or firmware, the relevant program code is stored in the memory 402 and is called and executed by the processor 401.

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

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

[0245] The bus 405 comprises a pathway for transmitting information between 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 a specific implementation, the device may also include other components necessary for normal operation. In addition, it will be understood by those skilled in the art that the above device may only include the components necessary to implement the embodiments of this 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 structured 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 media of this embodiment include permanent and non-permanent, removable and non-removable media that can be used to store information by any method or technology. The information can be computer-readable instructions, data structures, program modules 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 disc read-only memory (CD-ROM), digital versatile disc (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] Those 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 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, for simplicity of description and discussion, and in order not to make the embodiment of the application difficult to understand, the known power supply / ground connection with integrated circuit (IC) chip and other components may or may not be shown in the accompanying drawings provided. In addition, the device can be shown in the form of a block diagram to avoid making the embodiment of the application difficult to understand, and this also takes into account the following fact, that is, the details of the embodiment of these block diagram devices are highly dependent on the platform to be implemented in the embodiment of the application (that is, these details should be fully within the scope of understanding of those skilled in the art). When specific details (for example, circuit) are set forth to describe exemplary embodiments of the application, it will be apparent to those skilled in the art that the embodiment of the 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 invention has been described in conjunction with specific embodiments thereof, many alternatives, modifications, and variations of these embodiments will be apparent to those skilled in the art based on the foregoing description. For example, other memory architectures (e.g., dynamic RAM (DRAM)) may utilize 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 scope of protection 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 obtains user data and pre-coded data corresponding to the user data, and processes the user data and the pre-coded data using a transmission signal determination algorithm to obtain a transmission signal of the base station; Each of the plurality of user terminals is used as a target user terminal, and the target user terminal processes the signal sent by the base station using a user terminal reception signal determination algorithm to obtain a reception signal of the target user terminal; The target user terminal processes, based on a received signal of the target user terminal, a signal-to-noise ratio determination algorithm for user terminal decoding of 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, based on the received signal of the target user terminal, a realization rate determination algorithm for a user terminal private data stream to obtain a realization rate of the private data stream of the target user terminal; The eavesdropping end processes the base station's transmitted signal through the eavesdropping end's received signal determination algorithm to obtain the eavesdropping end's received signal; 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; 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 an 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 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. Based on the signal-to-noise ratio constraint, the rate constraint, the constructive interference construction condition, and the eavesdropping constraint, the controller processes the objective function through a power allocation algorithm of a genetic algorithm, 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.

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 base station's transmit signal based on the user data and the pre-coded data using the following formula: Where X represents the base station's transmission signal, 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 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 by using 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 using the following formula: Among them, y k represents the received signal of target user terminal k, h k ∈C N×1 is the channel between the base station and the target user terminal k, X represents the base station's transmission signal, 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 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, wherein The target user terminal processes the received signal of the target user terminal using a signal-to-noise ratio determination algorithm for user terminal decoding public information to obtain a signal-to-noise ratio of the target user terminal decoding public information, 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 Gaussian white 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 Gaussian white 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 user's index.

5. The method according to claim 1, wherein The target user terminal processes the received signal of the target user terminal by using the user terminal private data stream realization rate determination algorithm to obtain the realization rate of the target user terminal private data stream, 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 Gaussian white 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 Gaussian white 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 terminal decoding private information, is the user-side index, i represents the order of the user's index; The target user terminal determines the realization rate of the private data stream of the target user terminal based on the signal-to-noise ratio of the private information decoded by the target user terminal using the following formula: 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 base station's transmitted signal through the eavesdropping end's received signal determination algorithm to obtain the eavesdropping end's received signal, including: The eavesdropping end determines the received signal of the eavesdropping end based on the transmitted signal of the base station 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 terminal e, X represents the base station's transmission signal, is the additive white Gaussian noise at the eavesdropping end e, p c ∈ N×1 It is the public data stream s in 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 by using 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, 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 terminal is determined by the following formula: in, represents the signal-to-noise ratio of the public information decoded by the eavesdropping terminal, is the user-side index, i represents the order of the user's index.

8. The method according to claim 1, characterized in that The target user end processes a 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 in 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 in 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: Among them, k represents the order of the user end, 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 an 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 in the complex plane The square root of the additive white Gaussian noise σ at the eavesdropping end e 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 in the complex plane The square root of the additive white Gaussian noise σ at the eavesdropping end e 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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