Dual full-duplex communication method and apparatus for self-interference cancellation, device, and medium

Abstract

This application provides a method, apparatus, device, and medium for full-duplex communication with self-interference cancellation. The method includes: after entering full-duplex mode, obtaining the target optimal polarization state parameters of the transmitting antenna based on the current communication environment; controlling the transmitting antenna to transmit a signal according to the target optimal polarization state parameters and a preset first transmitting power; wherein the target optimal polarization state parameters are obtained by executing an optimization algorithm when the transmitting antenna's transmitting power is at a preset second transmitting power, and the objective function of the optimization algorithm is to minimize the power of the SI signal received by the receiving antenna; the second transmitting power is higher than the first transmitting power, and during the execution of the optimization algorithm based on the second transmitting power, the power of the SI signal received by the receiving antenna is always higher than the power of the base noise received by the receiving antenna. This method is used to improve the SI signal cancellation depth during full-duplex communication.

Description

Technical Field

[0001] This application relates to the field of communications, and in particular to a self-interference-cancelling full-duplex communication method, apparatus, device, and medium. Background Technology

[0002] Co-frequency Co-time Full-Duplex (CCFD) technology, which allows communication nodes to transmit and receive signals at the same frequency and in the same time slot, theoretically doubles the spectral efficiency and has become a key research direction for next-generation communication systems.

[0003] Currently, in CCFD technology, high-power signals from the transmitter enter the receiver through antenna coupling, multipath propagation, and other paths, forming extremely strong self-interference (SI) signals. If these SI signals cannot be eliminated to below the receiver's floor noise level, the receiver will be unable to properly demodulate the useful signal. Therefore, the core bottleneck of CCFD technology lies in how to eliminate the SI signals generated by the transmitter for the local receiver. In existing technologies, digital domain polarization self-interference cancellation methods have been extensively studied. This method calculates the optimal dual-polarization state of the transmitting antenna by executing an optimization algorithm with the objective function of minimizing SI power. This ensures that the polarization state of the transmitted signal after passing through the self-interference channel is orthogonal to the fixed polarization state of the receiving antenna, thereby achieving effective SI signal cancellation at the antenna level.

[0004] However, in practical deployments, when the SI power is reduced to near the level of the floor noise, the system's ability to detect the SI signal fails, causing the optimization algorithm to converge prematurely or fail, making it impossible to further reduce the SI signal below the floor noise. This results in incomplete SI cancellation during communication. Therefore, a more thorough full-duplex communication method with more complete self-interference cancellation is urgently needed. Summary of the Invention

[0005] This application provides a self-interference cancellation method, apparatus, device, and medium for full-duplex communication, which aims to improve the cancellation depth of SI signals during full-duplex communication.

[0006] In a first aspect, embodiments of this application provide a self-interference cancellation full-duplex communication method, including:

[0007] After entering full-duplex mode, the target optimal polarization state parameters of the transmitting antenna are obtained according to the current communication environment.

[0008] The transmitting antenna is controlled to transmit a signal according to the target's optimal polarization state parameters and a preset first transmission power.

[0009] The target optimal polarization state parameter is obtained by executing an optimization algorithm when the transmit power of the transmit antenna is at a preset second transmit power. The objective function of the optimization algorithm is to minimize the power of the SI signal received by the receive antenna. The second transmit power is higher than the first transmit power, and during the execution of the optimization algorithm based on the second transmit power, the power of the SI signal received by the receive antenna is always higher than the power of the base noise received by the receive antenna.

[0010] In one possible implementation, obtaining the target optimal polarization state parameters of the transmitting antenna based on the current communication environment includes:

[0011] If the storage unit contains an optimal polarization state parameter corresponding to the current communication environment, then the optimal polarization state parameter is used as the target optimal polarization state parameter.

[0012] In one possible implementation, obtaining the target optimal polarization state parameters of the transmitting antenna based on the current communication environment includes:

[0013] If the storage unit does not contain the optimal polarization state parameter corresponding to the current communication environment, the transmitting antenna is controlled to transmit a signal according to the second transmitting power, and the optimization algorithm is executed to solve for the optimal polarization state parameter corresponding to the current communication environment, and the optimal polarization state parameter is used as the target optimal polarization state parameter.

[0014] In one possible implementation, the step of controlling the transmitting antenna to transmit a signal according to the second transmitting power and executing the optimization algorithm to solve for the optimal polarization state parameters corresponding to the current communication environment includes:

[0015] Control the transmitting antenna to transmit signals according to the second transmitting power;

[0016] Initialize the iteration parameters of the optimization algorithm;

[0017] The optimization algorithm is executed based on the power of the SI signal received by the receiving antenna in real time under the second transmit power, until the iteration termination condition is met, and the optimal polarization state parameters corresponding to the current communication environment are obtained.

[0018] The optimal polarization state parameters include complex weights used to control the horizontal and vertical polarization of the transmitting antenna, respectively; the complex weights include amplitude weights and phase weights.

[0019] In one possible implementation, the termination conditions include the current iteration count reaching a preset maximum iteration count and the power of the SI signal being lower than a preset power threshold.

[0020] In one possible implementation, the optimization algorithm is a particle swarm optimization algorithm.

[0021] In one possible implementation, the method further includes:

[0022] The optimal polarization state parameters corresponding to the current communication environment are added to the storage unit.

[0023] Secondly, embodiments of this application provide a self-interference cancellation full-duplex communication device, comprising:

[0024] The acquisition module is used to acquire the target optimal polarization state parameters of the transmitting antenna based on the current communication environment after entering full-duplex mode.

[0025] The control module is used to control the transmitting antenna to transmit signals according to the target optimal polarization state parameters and the preset first transmitting power;

[0026] The target optimal polarization state parameter is obtained by executing an optimization algorithm when the transmit power of the transmit antenna is at a preset second transmit power. The objective function of the optimization algorithm is to minimize the power of the SI signal received by the receive antenna. The second transmit power is higher than the first transmit power, and during the execution of the optimization algorithm based on the second transmit power, the power of the SI signal received by the receive antenna is always higher than the power of the base noise received by the receive antenna.

[0027] In one possible implementation, the acquisition module is specifically used for:

[0028] If the storage unit contains an optimal polarization state parameter corresponding to the current communication environment, then the optimal polarization state parameter is used as the target optimal polarization state parameter.

[0029] In one possible implementation, the acquisition module is further specifically used for:

[0030] If the storage unit does not contain the optimal polarization state parameter corresponding to the current communication environment, the transmitting antenna is controlled to transmit a signal according to the second transmitting power, and the optimization algorithm is executed to solve for the optimal polarization state parameter corresponding to the current communication environment, and the optimal polarization state parameter is used as the target optimal polarization state parameter.

[0031] In one possible implementation, the acquisition module is specifically used for:

[0032] Control the transmitting antenna to transmit signals according to the second transmitting power;

[0033] Initialize the iteration parameters of the optimization algorithm;

[0034] The optimization algorithm is executed based on the power of the SI signal received by the receiving antenna in real time under the second transmit power, until the iteration termination condition is met, and the optimal polarization state parameters corresponding to the current communication environment are obtained.

[0035] The optimal polarization state parameters include complex weights used to control the horizontal and vertical polarization of the transmitting antenna, respectively; the complex weights include amplitude weights and phase weights.

[0036] In one possible implementation, the termination conditions in the acquisition module include the current iteration count reaching a preset maximum iteration count and the power of the SI signal being lower than a preset power threshold.

[0037] In one possible implementation, the optimization algorithm in the acquisition module is a particle swarm optimization algorithm.

[0038] In one possible implementation, the device further includes:

[0039] The storage module is used to add the optimal polarization state parameters corresponding to the current communication environment to the storage unit.

[0040] Thirdly, embodiments of this application provide a control device, including: a memory and a processor;

[0041] The memory stores computer-executed instructions;

[0042] The processor executes computer execution instructions stored in the memory, causing the processor to perform the first aspect and / or various possible implementations of the first aspect as described above.

[0043] Fourthly, embodiments of this application provide a computer-readable storage medium storing computer-executable instructions, which, when executed by a processor, are used to implement the first aspect and / or various possible implementations of the first aspect.

[0044] Fifthly, embodiments of this application provide a computer program product, including a computer program that, when executed by a processor, implements the first aspect and / or various possible implementations of the first aspect.

[0045] This application provides a method, apparatus, device, and medium for self-interference cancellation full-duplex communication. By pre-solving the optimal polarization state parameters with the goal of minimizing SI signal power at a higher transmission power (i.e., a second transmission power), and then transmitting the signal at normal power (i.e., a first transmission power) according to the solved optimal polarization state parameters, the power of the SI signal received in the receiving antenna is reduced to below the power of the floor noise, achieving deep SI signal cancellation and thus improving the quality of full-duplex communication. Simultaneously, the optimization algorithm executed at higher power makes SI signal detection more reliable, the feedback of the optimization algorithm clearer and smoother, less prone to getting trapped in local optima caused by noise, and convergence more stable and reliable, further improving the accuracy of the target optimal polarization state parameters. Furthermore, this solution is a pure software / algorithm process optimization, improving the system performance of existing hardware platforms by intelligently controlling the transmission power. It is easy to implement and deploy on existing platforms through firmware upgrades, without requiring hardware upgrades (such as analog-to-digital converters). The accuracy, dynamic range, or sensitivity of the converter (ADC) are improved, and it has the advantages of hardware optimization and easy deployment. Attached Figure Description

[0046] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application.

[0047] Figure 1 A flowchart illustrating a self-interference cancellation full-duplex communication method provided in Embodiment 1 of this application;

[0048] Figure 2 This is a flowchart illustrating a self-interference cancellation full-duplex communication method provided in Embodiment 2 of this application;

[0049] Figure 3 This is a schematic diagram of the structure of a self-interference cancellation full-duplex communication device provided in Embodiment 3 of this application;

[0050] Figure 4 This is a schematic diagram of the structure of a self-interference cancellation full-duplex communication device provided in Embodiment 4 of this application;

[0051] Figure 5 A schematic diagram of the control device provided in this application.

[0052] The accompanying drawings illustrate specific embodiments of this application, which will be described in more detail below. These drawings and descriptions are not intended to limit the scope of the concept in any way, but rather to illustrate the concept of this application to those skilled in the art through reference to particular embodiments. Detailed Implementation

[0053] Exemplary embodiments will now be described in detail, examples of which are illustrated in the accompanying drawings. When the following description relates to the drawings, unless otherwise indicated, the same numbers in different drawings denote the same or similar elements. The embodiments described in the following exemplary embodiments do not represent all embodiments consistent with this application. Rather, they are merely examples of apparatuses and methods consistent with some aspects of this application as detailed in the appended claims.

[0054] To facilitate understanding of the technical content of this solution, the background technology is described in detail below:

[0055] To address the self-interference problem in current full-duplex communication technologies, existing communication methods for digital domain polarization self-interference cancellation have been extensively studied. In this method, the transmitting antenna employs a dual-polarization array antenna with controllable polarization, while the receiving antenna uses an arbitrary fixed polarization. An optimization algorithm with the objective function of minimizing SI power is used to search and calculate the optimal dual-polarization state of the transmitting antenna, ensuring that the final polarization state of the transmitted signal after passing through the self-interference channel is exactly orthogonal to the fixed polarization state of the receiving antenna. Theoretically, when the polarizations are perfectly orthogonal, the receiving antenna will not receive any SI signal, thus achieving near-perfect SI cancellation at the antenna (also known as the air interface) level.

[0056] However, in actual field and hardware platform testing, this technology revealed a key problem: the system's detection capability fails when the SI power is reduced to near the floor noise level. Specifically, the scheme relies on an optimization algorithm to iteratively search for the optimal polarization state of the transmitting antenna. This algorithm requires a feedback loop, meaning it needs to detect the residual SI power of the transmitting antenna in real time, using this as a cost function to guide the next iteration. However, when the residual SI power approaches the floor noise, it becomes overwhelmed by noise. The detection sensitivity of the system (such as the ADC or SI detection module) drops significantly, making it unable to provide accurate feedback to the optimization algorithm (i.e., the cost function becomes blurred or filled with noise). This causes the optimization algorithm to converge prematurely or fail, unable to further reduce the SI below the floor noise. Ultimately, the depth of SI elimination is limited, making it difficult to achieve the ideal full-duplex communication requirements. Therefore, the key to solving this problem lies in overcoming the issue of system insensitivity and optimization algorithm failure caused by the SI signal power approaching the floor noise.

[0057] Based on the aforementioned background technology, the inventors first discovered through theoretical analysis that the polarization response of the self-interference channel is linear; therefore, the amount of elimination achievable by polarization orthogonality is independent of the transmit power. Based on this, the inventors proposed migrating the execution environment of the optimization algorithm from normal power to a high-power stage, utilizing the high signal-to-noise ratio (SNR) of the SI signal under high power to ensure that the detection module can provide accurate feedback. Subsequently, experimental verification showed that the optimization algorithm can stably converge to the optimal solution in the high-power stage, while after switching to normal power, the residual SI power automatically decreases below the floor noise due to its linear characteristics. In view of this, the self-interference elimination method based on a two-stage variable power assisted optimization strategy, as presented in this application, is hereby proposed.

[0058] It should be noted that this application applies to wireless communication systems deploying full-duplex communication technology, such as 6G base stations, industrial IoT gateways, and vehicle-to-everything (V2X) edge nodes. This application does not limit the specific application scenario of the solution. In these scenarios, communication nodes need to simultaneously transmit and receive signals on the same frequency and in the same time slot. The system architecture includes a transmitting antenna and a receiving antenna, wherein the transmitting antenna is configured as an adjustable dual-polarized array antenna, and the receiving antenna is configured as a fixed-polarized antenna. It should be understood that the method provided in this solution can be applied to control devices (such as baseband signal processing boards) in the aforementioned wireless communication systems.

[0059] The technical solution of this application and how the technical solution of this application solves the above-mentioned technical problems are described in detail below with specific embodiments. These specific embodiments can be combined with each other, and the same or similar concepts or processes may not be described again in some embodiments. The embodiments of this application will now be described with reference to the accompanying drawings.

[0060] Figure 1 This is a flowchart illustrating a self-interference cancellation full-duplex communication method provided in Embodiment 1 of this application, as shown below. Figure 1 As shown, the method includes:

[0061] S101. After entering full-duplex mode, the target optimal polarization state parameters of the transmitting antenna are obtained according to the current communication environment. The target optimal polarization state parameters are obtained by executing an optimization algorithm when the transmitting power of the transmitting antenna is at a preset second transmitting power.

[0062] The objective function of the above optimization algorithm is to minimize the power of the SI signal received by the receiving antenna.

[0063] In this step, the communication system will first be controlled to enter full-duplex mode. Then, considering that the communication environment is the key factor affecting the transmission characteristics of the SI channel, different communication environments will be adapted to different optimal polarization state parameters. Therefore, it is necessary to obtain the optimal polarization state parameters adapted to the current communication environment as the target optimal polarization state parameters.

[0064] The communication environment includes, for example, magnetic field environment and space reflection environment; polarization state parameters refer to the set of quantized parameters used to control the output of a specific polarization state of a dual-polarized transmitting antenna.

[0065] As a specific example, controlling the communication system to enter full-duplex mode includes: after receiving a mode switching command issued by the host computer of the communication system, controlling the communication system to enter full-duplex mode, configuring the transmitting antenna as a dual-polarized antenna with controllable polarization, and configuring the receiving antenna as a fixed-polarized antenna.

[0066] In detail, when the optimization algorithm is executed at the second transmit power, the objective function is to minimize the SI signal power received by the receiving antenna. The polarization state parameters of the transmitting antenna are adjusted iteratively. After each iteration, the power of the SI signal of the receiving antenna is detected in real time to guide the direction of the next iteration until the iteration stops. At this time, the polarization state parameters obtained by the algorithm convergence are the optimal polarization state parameters.

[0067] Among them, optimization algorithms are a class of mathematical methods that use an iterative trial-and-error-feedback adjustment logic to find the optimal solution in the solution space that satisfies the requirements of the objective function. This application does not impose specific restrictions on the selection of optimization algorithms; for example, optimization algorithms include Particle Swarm Optimization (PSO), Gradient Descent (GD), and Genetic Algorithms. In this scheme, the core objective of the optimization algorithm is to find a set of optimal polarization state parameters that satisfy the requirements of the objective function (i.e., minimize the power of the SI signal received by the received signal).

[0068] It should be understood that this scheme selects PSO as the optimization algorithm. Through the dynamic update of its individual optimal and group optimal solutions, it quickly guides parameter iteration, thereby achieving the effect of fast algorithm convergence and reduced computational overhead.

[0069] In addition, the setting of the second transmit power must meet the requirement that the second transmit power is higher than the first transmit power, and that during the process of executing the optimization algorithm based on the second transmit power, the power of the SI signal received by the receiving antenna is always higher than the power of the base noise received by the receiving antenna.

[0070] In detail, in order for the detection module used to detect the SI signal received by the receiving antenna to effectively distinguish the SI signal from the base noise, thereby providing reliable feedback for the optimization algorithm, the second transmit power should be set high enough so that the power of the SI signal received by the receiving antenna is always higher than the power of the base noise received by the receiving antenna during the execution of the optimization algorithm based on the second transmit power. It should be understood that if the setting of the second transmit power meets this condition, the second transmit power will also be higher than the first transmit power.

[0071] It should be noted that this application does not impose specific restrictions on the specific value of the second transmission power. In practical applications, experimental tests can be conducted based on factors such as the normal transmission power of the communication system (i.e., the first transmission power), the power of the base noise received by the antenna in the current communication environment, and the maximum transmission power of the communication system to obtain the second transmission power that meets the above requirements.

[0072] As a specific example, the second transmit power P2 = P1 + ΔP; where P1 represents the first transmit power, that is, the normal transmit power of the communication system; ΔP represents the preset power change value, such as 10dB, 12dB, 15dB, 20dB, etc.

[0073] It should be understood that when the optimization algorithm is executed at a higher second transmit power, even after initial suppression, the residual power of the SI signal is still much higher than the power of the basis noise, remaining above the sensitivity range of the detection module. This allows the detection module to measure the power of the SI signal very sensitively and accurately. Correspondingly, the feedback signal is clearer, more accurate, and smoother, making the convergence reliability of the optimization algorithm higher. It is less likely to get trapped in local optima caused by noise and can efficiently converge to the true optimal solution (i.e., the polarization state parameters closest to the ideal orthogonal), thereby improving the robustness and convergence of the optimization algorithm, and thus improving the accuracy of the obtained optimal solution.

[0074] S102. Control the transmitting antenna to transmit signals according to the target's optimal polarization state parameters and the preset first transmitting power.

[0075] In this step, the digital domain polarization of the transmitting antenna will be controlled according to the target optimal polarization state parameters, and the transmitting antenna will be controlled to transmit signals at the normal transmitting power (i.e., the first transmitting power).

[0076] It should be understood that, since the self-interference channel and its polarization response are linear, when the polarization state of the transmitting antenna is fixed at the optimal orthogonal state, the power cancellation (dB value) of the SI signal it can provide is maintained. Compared to the transmit power P2 in the optimization iteration stage, the transmit power P1 at the time of signal transmission is equivalent to a decrease of ΔP. Therefore, the power P of the residual SI signal at the transmitting antenna is reduced. SI,residualBased on the power of the SI signal corresponding to the target optimal polarization state parameters determined by P2, ΔP will also be linearly reduced simultaneously (for example, if the transmit power is reduced by 10dB, the power of the residual SI signal will also be reduced by 10dB). Therefore, P SI,residual The power has been successfully reduced to below the floor noise level, achieving deep elimination of the SI signal and effectively ensuring the quality of normal full-duplex communication.

[0077] This application provides a full-duplex communication method with self-interference cancellation. By pre-solving the optimal polarization state parameters with the goal of minimizing SI signal power at a higher transmit power (i.e., the second transmit power), and then transmitting the signal at normal power (i.e., the first transmit power) according to the solved optimal polarization state parameters, the power of the SI signal received in the receiving antenna is reduced to below the power of the base noise, achieving deep cancellation of the SI signal and thus improving the quality of full-duplex communication. Simultaneously, the optimization algorithm executed at higher power makes the detection reliability of the SI signal higher, the feedback of the optimization algorithm clearer and smoother, less prone to getting trapped in local optima caused by noise, and convergence more stable and reliable, further improving the accuracy of the target optimal polarization state parameters. Furthermore, this solution is a pure software / algorithm process optimization. By intelligently controlling the transmit power, it improves the system performance of existing hardware platforms. It is easy to implement and deploy on existing platforms through firmware upgrades, without requiring improvements to the accuracy, dynamic range, or sensitivity of hardware (such as analog-to-digital converters, ADCs), offering advantages of hardware optimization and ease of deployment.

[0078] Furthermore, Figure 2 This is a flowchart illustrating a self-interference cancellation full-duplex communication method provided in Embodiment 2 of this application, as shown below. Figure 2 As shown in the embodiments of this application, the implementation of step S101 in the above embodiments is described in detail, including:

[0079] S201. Obtain the data stored in the storage unit.

[0080] S202. Determine whether there are optimal polarization state parameters in the storage unit that correspond to the current communication environment.

[0081] The storage unit can be any device with data storage function in the communication system, such as a register in the communication system.

[0082] Specifically, if the storage unit contains the optimal polarization state parameter corresponding to the current communication environment, then step S203 is executed; if the storage unit does not contain the optimal polarization state parameter corresponding to the current communication environment, then step S204 is executed.

[0083] S203. Take the optimal polarization state parameter corresponding to the current communication environment as the target optimal polarization state parameter.

[0084] It should be understood that if the iterative calculation of the optimal solution has been performed in the current communication environment, the corresponding optimal polarization state parameters can be directly called from the storage unit for the configuration of signal parameters in this full-duplex communication.

[0085] It should be noted that the optimal polarization state parameters stored in the storage unit, corresponding to the current communication environment, were obtained by executing an optimization algorithm when the transmit power of the transmitting antenna was at a preset second transmit power during a historical stage of the same communication environment.

[0086] S204. Control the transmitting antenna to transmit signals according to the second transmitting power, and execute the optimization algorithm to solve for the optimal polarization state parameters corresponding to the current communication environment, and use the optimal polarization state parameters as the target optimal polarization state parameters.

[0087] It should be understood that if the iterative calculation of the optimal solution has not been performed in the current communication environment before, the transmitting antenna will be controlled to transmit the signal at the second transmission power, and the optimization algorithm will be executed at the second transmission power to solve for the optimal polarization state parameters corresponding to the current communication environment, which will be used for the configuration of signal parameters in this full-duplex communication.

[0088] In one possible implementation, this step may include steps 3.1 to 3.3 as follows:

[0089] Step 3.1: Control the transmitting antenna to transmit signals at the second transmitting power.

[0090] In this step, the transmitting power of the transmitting antenna needs to be adjusted to the second transmitting power, and the transmitting antenna needs to be controlled to transmit signals according to the second transmitting power.

[0091] In the specific implementation of the solution, the transmitter's transmit power can be set to a second transmit power by controlling the digital gain or analog attenuator. It should be understood that after adjusting the transmit antenna's transmit power to the second transmit power, the power of the SI signal received by the transmit antenna is also correspondingly higher, meeting the requirement of being above the floor noise level, and can be clearly and accurately measured by the SI detection module.

[0092] Step 3.2: Initialize the iteration parameters of the optimization algorithm.

[0093] The iteration parameters include the parameters to be optimized, the algorithm operation control parameters, and the convergence determination parameters.

[0094] For example, if the optimization algorithm is a particle swarm optimization algorithm, the iteration parameters may include, for example, the number of particles, the maximum number of iterations, the position and velocity of each particle, etc.

[0095] Step 3.3: Using the power of the SI signal received by the receiving antenna in real time under the second transmit power as the basis for iteration, execute the optimization algorithm until the iteration termination condition is met, and obtain the optimal polarization state parameters corresponding to the current communication environment.

[0096] In this step, the optimization algorithm will continuously iterate using the precisely measured power of the SI signal until it converges to obtain the optimal solution (i.e., the optimal polarization state parameters).

[0097] The optimal polarization state parameters include complex weights used to control the horizontal polarization of the transmit antenna. and complex weights used to control the vertical polarization of the transmitting antenna The complex weights include amplitude weights and phase weights.

[0098] In detail, ,in, This represents the amplitude weight used to control the horizontal polarization of the transmitting antenna. This represents the phase weights used to control the horizontal polarization of the transmitting antenna; , This represents the amplitude weight used to control the vertical polarization of the transmitting antenna. This represents the phase weights used to control the vertical polarization of the transmitting antenna.

[0099] It should be understood that in practical applications, dual-polarized transmitting antennas have two independent signal excitation ports: horizontal polarization and vertical polarization. By configuring a set of complex weights for each of the two ports, commands are issued to adjust the energy ratio and phase difference of the two signals, so that the two signals can be spatially superimposed to form a transmitting signal that meets the requirements of the target's optimal polarization state.

[0100] As a specific example, termination conditions include the current iteration count reaching the preset maximum iteration count and the SI signal power falling below a preset power threshold.

[0101] The setting of the power threshold can be determined based on the actual application of this solution, and this application does not impose specific restrictions on it. It is understood that the power threshold value will be higher than the power of the base noise received by the receiving antenna.

[0102] It should be understood that by setting the above dual iteration termination conditions, the optimization algorithm can stop iterating immediately when the SI power drops to the target level first, avoiding meaningless computational waste and shortening the parameter optimization time. At the same time, when the SI signal power is difficult to reach the target quickly in complex environments, the upper limit of the number of iterations prevents the algorithm from running indefinitely, ensuring the stability and real-time performance of the system. Ultimately, this achieves the effect of efficiently obtaining the optimal polarization state parameters that meet the self-interference cancellation requirements, improving the startup efficiency and communication reliability of full-duplex mode.

[0103] The method provided in steps 3.1 to 3.3 above, by controlling the transmitting antenna to transmit a signal at a second transmitting power, completing the initialization of the optimization algorithm iteration parameters, and running the optimization algorithm until convergence based on the SI signal power detected in real time by the receiving antenna at this power, obtains the optimal polarization state parameters covering the horizontal plan and the complex weight of the vertical polarization. This allows the optimization algorithm to achieve accurate parameter optimization based on the measured feedback data with a high signal-to-noise ratio, achieving a deep orthogonal matching between the polarization state of the self-interference signal and the polarization state of the receiving antenna, efficiently reducing the power of the residual SI signal to below the floor noise, and significantly improving the reliability of full-duplex communication.

[0104] In one possible implementation, step S204 may further include: adding the optimal polarization state parameters corresponding to the current communication environment to the storage unit.

[0105] It should be understood that this implementation adds the optimal polarization state parameters corresponding to the current communication environment to the storage unit so that when entering full-duplex mode again in the same communication environment, these optimal polarization state parameters can be directly called to control the digital domain polarization of the transmitting antenna, thereby simplifying the full-duplex communication process and improving the real-time performance of full-duplex communication.

[0106] The self-interference cancellation full-duplex communication method provided in this application directly retrieves the target optimal polarization state parameters from the storage unit when the communication environment remains unchanged. This allows for skipping redundant iterative optimization processes and directly reusing verified effective parameters to achieve rapid self-interference cancellation when the environment is stable. Simultaneously, when the communication environment changes, a high-power-based iterative optimization process is initiated to solve for the optimal polarization state parameters adapted to the current communication environment. This serves as the means to obtain the target optimal polarization state parameters, enabling precise iteration based on the power feedback of the high signal-to-noise ratio SI signal under high power when the environment changes. This ensures that the parameters are highly adapted to the new environment, ultimately achieving the effect of significantly shortening the real-time time of full-duplex communication and reducing the computational overhead of control equipment.

[0107] Figure 3 This is a schematic diagram of the structure of a self-interference cancellation full-duplex communication device provided in Embodiment 3 of this application, as shown below. Figure 3 As shown, the self-interference cancellation full-duplex communication device 30 provided in this embodiment includes:

[0108] The acquisition module 301 is used to acquire the target optimal polarization state parameters of the transmitting antenna according to the current communication environment after entering full-duplex mode.

[0109] Control module 302 is used to control the transmitting antenna to transmit signals according to the target optimal polarization state parameters and the preset first transmitting power;

[0110] The target optimal polarization state parameters are obtained by executing an optimization algorithm when the transmit power of the transmit antenna is at a preset second transmit power. The objective function of the optimization algorithm is to minimize the power of the SI signal received by the receive antenna. The second transmit power is higher than the first transmit power, and during the process of executing the optimization algorithm based on the second transmit power, the power of the SI signal received by the receive antenna is always higher than the power of the base noise received by the receive antenna.

[0111] The self-interference cancellation full-duplex communication device 30 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0112] Figure 4 This is a schematic diagram of the structure of a self-interference cancellation full-duplex communication device provided in Embodiment 4 of this application, as shown below. Figure 4 As shown, based on the above embodiments, the self-interference cancellation full-duplex communication device 30 provided in this embodiment further includes:

[0113] Storage module 303 is used to add the optimal polarization state parameters corresponding to the current communication environment to the storage unit.

[0114] In one possible implementation, the acquisition module 301 is specifically used for:

[0115] If the storage unit contains the optimal polarization state parameter corresponding to the current communication environment, then the optimal polarization state parameter is taken as the target optimal polarization state parameter.

[0116] In one possible implementation, the acquisition module 301 is further specifically used for:

[0117] If the optimal polarization state parameter corresponding to the current communication environment does not exist in the storage unit, the transmitting antenna is controlled to transmit a signal at the second transmitting power, and an optimization algorithm is executed to solve for the optimal polarization state parameter corresponding to the current communication environment, and the optimal polarization state parameter is used as the target optimal polarization state parameter.

[0118] In one possible implementation, the acquisition module 301 is specifically used for:

[0119] Control the transmitting antenna to transmit signals at the second transmission power;

[0120] Initialize the iteration parameters of the optimization algorithm;

[0121] The optimization algorithm is executed based on the power of the SI signal received by the receiving antenna in real time under the second transmit power, until the optimal polarization state parameters corresponding to the current communication environment are obtained when the iteration termination condition is met.

[0122] The optimal polarization state parameters include complex weights used to control the horizontal and vertical polarization of the transmitting antenna, respectively; the complex weights include amplitude weights and phase weights.

[0123] In one possible implementation, the termination conditions in the acquisition module 301 include the current iteration number reaching a preset maximum iteration number and the power of the SI signal being lower than a preset power threshold.

[0124] In one possible implementation, the optimization algorithm in the acquisition module 301 is the particle swarm optimization algorithm.

[0125] The self-interference cancellation full-duplex communication device 30 provided in this embodiment can execute the method provided in the above method embodiment. Its implementation principle and technical effect are similar, and will not be described in detail here.

[0126] Figure 5 A schematic diagram of the control device provided in this application. Figure 5 As shown, the control device 40 provided in this embodiment includes at least one processor 401 and a memory 402. Optionally, the device 40 further includes a communication component 403. The processor 401, memory 402, and communication component 403 are connected via a bus 404.

[0127] In a specific implementation, at least one processor 401 executes computer execution instructions stored in memory 402, causing at least one processor 401 to perform the above-described method.

[0128] Among these, control equipment includes, for example, the baseband signal processing board in a full-duplex communication system.

[0129] The specific implementation process of processor 401 can be found in the above method embodiments, and its implementation principle and technical effect are similar. It will not be repeated here.

[0130] In the above embodiments, it should be understood that the processor can be a Central Processing Unit (CPU), or other general-purpose processors, digital signal processors (DSPs), application-specific integrated circuits (ASICs), etc. The general-purpose processor can be a microprocessor or any conventional processor. The steps of the method disclosed in this invention can be directly implemented by a hardware processor, or implemented by a combination of hardware and software modules within the processor.

[0131] The memory may include read-only memory and random access memory. The memory may be volatile or non-volatile, or may include both. Non-volatile memory may include read-only memory (ROM), programmable read-only memory (PROM), erasable programmable read-only memory (EPROM), electrically erasable programmable read-only memory (EEPROM), or flash memory. Volatile memory may include random access memory (RAM), which serves as an external cache. Many forms of RAM are available by way of example, but not limitation. Examples include Static Random Access Memory (SRAM), Dynamic Random Access Memory (DRAM), Synchronous DRAM (SDRAM), Double Data Rate SDRAM (DDR SDRAM), Enhanced Synchronous DRAM (ESDRAM), Sync Link DRAM (SLDRAM), and Direct Rambus RAM (DR RAM).

[0132] The bus can be an Industry Standard Architecture (ISA) bus, a Peripheral Component Interconnect (PCI) bus, or an Extended Industry Standard Architecture (EISA) bus, etc. Buses can be categorized as address buses, data buses, control buses, etc. For ease of illustration, the buses shown in the accompanying drawings are not limited to a single bus or a single type of bus.

[0133] This application also provides a computer program product, including a computer program that, when executed, implements the above-described method.

[0134] This application also provides a computer-readable storage medium storing computer-executable instructions, which, when executed, implement the above-described method.

[0135] The aforementioned readable storage medium can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as SRAM, EEPROM, EPROM, PROM, ROM, magnetic storage, flash memory, magnetic disk, or optical disk. The readable storage medium can be any available medium accessible to a general-purpose or special-purpose computer.

[0136] An exemplary readable storage medium is coupled to a processor, enabling the processor to read information from and write information to the readable storage medium. Of course, the readable storage medium can also be a component of the processor. The processor and the readable storage medium can reside within an ASIC. Alternatively, the processor and the readable storage medium can exist as discrete components in a device.

[0137] The division of units is merely a logical functional division; in actual implementation, there may be other division methods. For example, multiple units or components may be combined or integrated into another system, or some features may be ignored or not executed. Furthermore, the coupling or direct coupling or communication connection shown or discussed may be indirect coupling or communication connection through some interfaces, devices, or units, and may be electrical, mechanical, or other forms.

[0138] The units described as separate components may or may not be physically separate. The components shown as units may or may not be physical units; that is, they may be located in one place or distributed across multiple network units. Some or all of the units can be selected to achieve the purpose of this embodiment according to actual needs.

[0139] In addition, the functional units in the various embodiments of the present invention can be integrated into one processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0140] If a function is implemented as a software functional unit and sold or used as an independent product, it can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of this invention, or the part that contributes to the prior art, or a part of the technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions to cause a computer device (which may be a personal computer, server, or network device, etc.) to execute all or part of the steps of the methods of the various embodiments of this invention. The aforementioned storage medium includes various media capable of storing program code, such as USB flash drives, portable hard drives, ROM, RAM, magnetic disks, or optical disks.

[0141] Those skilled in the art will understand that all or part of the steps of the above-described method embodiments can be implemented by hardware related to program instructions. The aforementioned program can be stored in a computer-readable storage medium. When executed, the program performs the steps of the above-described method embodiments; and the aforementioned storage medium includes various media capable of storing program code, such as ROM, RAM, magnetic disks, or optical disks.

[0142] Finally, it should be noted that other embodiments of the invention will readily occur to those skilled in the art upon consideration of the specification and practice of the invention disclosed herein. This invention is intended to cover any variations, uses, or adaptations of the invention that follow the general principles of the invention and include common knowledge or customary techniques in the art not disclosed herein, and is not limited to the precise structures described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of the invention is limited only by the appended claims.

Claims

1. A self-interference cancellation full-duplex communication method, characterized in that, include: After entering full-duplex mode, the target optimal polarization state parameters of the transmitting antenna are obtained according to the current communication environment. The transmitting antenna is controlled to transmit a signal according to the target's optimal polarization state parameters and a preset first transmission power. The target optimal polarization state parameter is obtained by executing an optimization algorithm when the transmit power of the transmit antenna is at a preset second transmit power. The objective function of the optimization algorithm is to minimize the power of the SI signal received by the receive antenna. The second transmit power is higher than the first transmit power, and during the execution of the optimization algorithm based on the second transmit power, the power of the SI signal received by the receive antenna is always higher than the power of the base noise received by the receive antenna.

2. The method according to claim 1, characterized in that, The step of obtaining the target optimal polarization state parameters of the transmitting antenna based on the current communication environment includes: If the storage unit contains an optimal polarization state parameter corresponding to the current communication environment, then the optimal polarization state parameter is used as the target optimal polarization state parameter.

3. The method according to claim 2, characterized in that, The method further includes: If the storage unit does not contain the optimal polarization state parameter corresponding to the current communication environment, the transmitting antenna is controlled to transmit a signal according to the second transmitting power, and the optimization algorithm is executed to solve for the optimal polarization state parameter corresponding to the current communication environment, and the optimal polarization state parameter is used as the target optimal polarization state parameter.

4. The method according to claim 3, characterized in that, The process involves controlling the transmitting antenna to transmit a signal at the second transmitting power and executing the optimization algorithm to obtain the optimal polarization state parameters corresponding to the current communication environment, including: Control the transmitting antenna to transmit signals according to the second transmitting power; Initialize the iteration parameters of the optimization algorithm; The optimization algorithm is executed based on the power of the SI signal received by the receiving antenna in real time under the second transmit power, until the iteration termination condition is met, and the optimal polarization state parameters corresponding to the current communication environment are obtained. The optimal polarization state parameters include complex weights used to control the horizontal and vertical polarization of the transmitting antenna, respectively; the complex weights include amplitude weights and phase weights.

5. The method according to claim 4, characterized in that, The termination conditions include the current iteration count reaching the preset maximum iteration count and the SI signal power being lower than the preset power threshold.

6. The method according to claim 4, characterized in that, The optimization algorithm is the particle swarm optimization algorithm.

7. The method according to any one of claims 3 to 6, characterized in that, The method further includes: The optimal polarization state parameters corresponding to the current communication environment are added to the storage unit.

8. A self-interference cancellation full-duplex communication device, characterized in that, include: The acquisition module is used to acquire the target optimal polarization state parameters of the transmitting antenna based on the current communication environment after entering full-duplex mode. The control module controls the transmitting antenna to transmit signals according to the optimal polarization state parameters and the preset first transmission power; The target optimal polarization state parameter is obtained by executing an optimization algorithm when the transmit power of the transmit antenna is at a preset second transmit power. The objective function of the optimization algorithm is to minimize the power of the SI signal received by the receive antenna. The second transmit power is higher than the first transmit power, and during the execution of the optimization algorithm based on the second transmit power, the power of the SI signal received by the receive antenna is always higher than the power of the base noise received by the receive antenna.

9. A control device, characterized in that, include: Memory, processor; The memory stores computer-executed instructions; The processor executes computer execution instructions stored in the memory, causing the processor to perform the method as described in any one of claims 1-7.

10. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores computer-executable instructions, which, when executed by a processor, are used to implement the method as described in any one of claims 1-7.

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