Sub-band full duplex interference mitigation method based on movable antenna

Abstract

The present application relates to the technical field of wireless communication, and particularly relates to a sub-band full-duplex interference suppression method based on a movable antenna. The method comprises the following steps: S1, real-time monitoring of cross-link interference information of a neighboring interference base station, and sensing of channel state information of an uplink target signal of the base station; S2, construction of a joint optimization model of a receiving antenna position and a receiving beamforming based on the sensing information; adoption of a hybrid beamforming architecture and facing of multi-user optimization; S3, obtaining of an optimal relative position of a receiving antenna array and an optimal receiving beamforming matrix; S4, movement of the receiving antenna array according to the optimal relative position; S5, adjustment of receiving beam weights according to the optimal receiving beamforming matrix, so as to form a spatial null in the interference direction; and S6, monitoring of a change amount of an uplink received signal interference plus noise ratio, and re-execution when the change amount exceeds a threshold. The present application realizes deep suppression of cross-link interference without relying on information interaction of adjacent base stations.

Description

Technical Field

[0001] This invention relates to the field of wireless communication technology, specifically to a sub-band full-duplex interference suppression method based on a movable antenna. Background Technology

[0002] As communication technology advances towards higher frequencies and larger capacities, subband full-duplex technology, which enables signal transmission and reception in different subbands within the same frequency band, significantly improves spectrum utilization and is widely used in next-generation communication systems. However, during the large-scale deployment of subband full-duplex networks, cross-link interference between base stations is the most serious and fatal interference problem. This interference directly leads to a sharp deterioration in the uplink receiving sensitivity of base stations, and is the core bottleneck restricting the large-scale commercial deployment of subband full-duplex technology.

[0003] Current solutions for suppressing cross-link interference between base stations in sub-band full-duplex networking have the following core shortcomings:

[0004] Existing solutions rely heavily on frequent information exchange and coordinated scheduling between base stations. They achieve interference avoidance by coordinating the adjustment of transmission beams through interference information exchange between neighboring stations. However, this approach suffers from high signaling overhead, high interaction latency, and extremely high implementation complexity. Furthermore, it is completely unsuitable for scenarios such as non-cooperative networking and cross-vendor equipment networking.

[0005] In sub-band full-duplex networking, base stations have difficulty obtaining in real time and accurately the interference impact of their own downlink transmission on neighboring base stations. Existing collaborative solutions cannot achieve accurate and in-depth suppression of cross-link interference without the cooperation of neighboring stations.

[0006] Existing non-cooperative solutions mostly employ beamforming technology based on fixed antennas, which can only achieve interference suppression by adjusting beam weights. Fixed antennas have limited degrees of freedom, making it difficult to form precise depth spatial nulls in the direction of interference. Furthermore, they cannot balance uplink reception performance with interference suppression effects, often sacrificing the reception gain of the uplink target signal in order to suppress interference.

[0007] Existing mobile antenna technology is mainly applied to signal coverage optimization scenarios. It has not been combined with cross-link interference suppression between sub-band full-duplex network base stations, has not explored the core value of the receiver antenna position freedom for uplink interference suppression, and has not proposed a joint optimization scheme for receiver antenna position and receiver beamforming that does not rely on neighboring station cooperation. Therefore, it is impossible to achieve deep zeroing of cross-link interference at the physical channel level.

[0008] In addition, existing movable antennas and beamforming solutions are mostly designed for single-target users and single interference sources, making it difficult to simultaneously address interference suppression and signal reception for multiple users in multi-target user scenarios, and to effectively manage mutual interference between multiple users. Existing solutions also do not consider the dynamic changes in interference direction caused by the movement of interference sources, making it difficult to achieve continuous tracking and suppression of interference. Furthermore, existing beamforming solutions typically require an RF link that is equivalent to the number of array elements, resulting in high hardware costs and power consumption.

[0009] Therefore, there is an urgent need for a technical solution that can achieve deep suppression of cross-link interference from the receiving end without relying on the cooperation of neighboring stations. Summary of the Invention

[0010] The technical problem to be solved by this invention is:

[0011] 1. Cross-link interference between base stations is the most serious and fatal interference problem in the large-scale deployment of sub-band full-duplex networking. Existing technologies are unable to achieve deep suppression of this interference, which directly restricts the large-scale deployment of sub-band full-duplex technology.

[0012] 2. Existing cross-link interference collaborative suppression schemes for sub-band full-duplex networking rely on frequent information exchange between base stations, resulting in high signaling overhead, high interaction latency, and high implementation complexity, making them unsuitable for non-cooperative networking scenarios.

[0013] 3. Existing fixed antenna interference suppression schemes have limited degrees of freedom, making it difficult to form a precise deep null in the direction of interference while ensuring uplink reception performance. They cannot balance the uplink reception signal interference-to-noise ratio with interference suppression effect.

[0014] 4. Existing technologies have not explored the value of the positional freedom of movable receiving antennas in suppressing cross-link interference, and have not proposed a joint optimization scheme for receiving antenna position and receiving beamforming based solely on its own channel awareness without relying on neighboring station cooperation.

[0015] To address the aforementioned technical problems, this invention provides a sub-band full-duplex interference suppression method based on a movable antenna, comprising the following steps:

[0016] Step S1, Interference and Channel Awareness: The base station monitors the cross-link interference information of neighboring interfering base stations in real time through the channel awareness module, and at the same time senses the channel status information of the uplink target signal of its own base station.

[0017] Step S2, Optimization Model Construction: Based on the interference information and uplink channel state information obtained by sensing, a joint optimization model of receiving antenna position and receiving beamforming is constructed. The joint optimization model takes maximizing the signal-to-interference-plus-noise ratio of the uplink received signal of this base station as the objective function and is subject to constraints. Among them, the receiving antenna position is a movable spatial degree of freedom. By adjusting the geometric layout of the receiving array, the equivalent channel response of the receiving array to cross-link interference is changed.

[0018] Step S3, Joint Optimization: Solve the joint optimization model to obtain the optimal relative position of the receiving antenna array and the optimal receiving beamforming matrix;

[0019] Step S4, Antenna position adjustment: Based on the optimal relative position, control the receiving antenna array to move to the target position within a preset two-dimensional moving area;

[0020] Step S5, Receive beamforming adjustment: Based on the optimal receive beamforming matrix obtained by joint optimization, adjust the receive beam weight in real time to form a depth space null that meets the preset threshold requirements in the interference direction;

[0021] Step S6, Effect Verification and Iterative Update: Monitor the changes in the uplink received signal interference plus noise ratio or cross-link interference. When the channel state, interference direction or interference intensity exceeds the preset threshold, re-execute steps S1 to S5.

[0022] Further, in step S1, the cross-link interference information includes CLI interference intensity and interference direction of arrival; when this base station detects multiple neighboring interfering base stations, it senses the cross-link interference information of each neighboring interfering base station to obtain the interference direction of arrival and interference channel matrix of multiple cross-link interference sources, which are denoted as follows: and ;in, For the first The direction of incoming waves from each cross-link interference source For the first The vector at the location of the cross-link interference sources in the receiving antenna array element is: Interference channel matrix at time, , This represents the total number of cross-link interference sources.

[0023] Further, in step S2, the constraints include: the position coordinates of all elements of the receiving antenna are within a preset two-dimensional planar moving area; the spatial power gain formed by the receiving beam in the direction of arrival of all adjacent interfering base stations is lower than a preset null threshold; based on the sensing and acquired direction of arrival of the interfering wave and the direction of arrival of the uplink target signal, the center and range of the preset two-dimensional moving area are dynamically adjusted, shrinking the two-dimensional moving area to a feasible area containing the position coordinates that satisfy the cross-link interference null constraint and the target signal receiving gain constraint, and ensuring that the moving areas corresponding to two adjacent optimization rounds satisfy... The constraint also includes that the spatial power gain formed by the received beam in the direction of arrival of each cross-link interference source is lower than the corresponding preset null threshold, i.e.:

[0024]

[0025] in, and All 3D column vector, For the number of receiving array elements, For receiving beamforming weight vector, For the receiving antenna array in position vector Corresponding to the direction of incoming wave The array response vector, The position vector of the receiving antenna array element. For the first The direction of incoming waves from each cross-link interference source For the first Preset zero-depression thresholds corresponding to each cross-link interference source This is the number of the cross-link interference source. This represents the total number of cross-link interference sources. and The first Wheel and the first The two-dimensional movement region corresponding to the round optimization. To optimize round numbering, it must be a positive integer;

[0026] The positional freedom of the receiving antenna is used to adjust the geometric layout of the receiving array, optimize the spatial response of the receiving array when the number of array elements is the same, and enhance the null depth formed by the receiving beam in the direction of each cross-link interference source. When the total number of cross-link interference sources is greater than the number of directions in which the receiving array can simultaneously form nulls, null constraints are set in order of the interference intensity of each cross-link interference source from strong to weak.

[0027] Furthermore, in step S2, the transmitting and receiving antennas of the base station are deployed separately, with only the position of the receiving antenna being adjusted, while the position and transmission configuration of the transmitting antenna remain fixed. The receiving end adopts a hybrid beamforming architecture, with the analog domain including an analog spatial domain determined by the position of the receiving antenna array elements and an analog phase domain determined by the phase shifter, and the digital domain consisting of a digital beamforming matrix. Confirmed, number of RF links Less than the number of array elements ;in, For digital beamforming matrix, For the number of radio frequency links, This represents the number of receiving array elements.

[0028] Furthermore, in step S3, a constrained iterative optimization algorithm is used to solve the joint optimization model.

[0029] Further, in step S3, an alternating iterative strategy is used to solve the joint optimization model: when the current receiving antenna position is fixed, the optimal receiving beamforming matrix is ​​determined based on the minimum mean square error algorithm; when the current receiving beamforming matrix is ​​fixed, the optimal position coordinates are searched within a preset position range based on the particle swarm optimization algorithm; a deep neural network is pre-constructed and trained, and the interference information and uplink channel state information obtained by sensing are input into the deep neural network, which outputs low-dimensional compressed receiving antenna position features and receiving beamforming features to recover the estimated receiving antenna position. With receive beamforming vector estimation Wherein, the receiving antenna position estimation As the initial population for the particle swarm optimization algorithm, the received beamforming vector estimation... This serves as the initial solution for determining the optimal receive beamforming matrix based on the minimum mean square error algorithm.

[0030] Furthermore, when searching for the optimal position coordinates based on the particle swarm optimization algorithm, the two-dimensional coordinates of each element in the receiving antenna array are mapped to the spatial position of the particle. The ratio of uplink received signal interference plus noise is used as the fitness function, and the search is performed by iteratively updating the individual optimal and global optimal solutions of the particles.

[0031] Further, in step S1, the direction of the interference wave is obtained by measuring the downlink reference signal transmitted by a nearby interfering base station; the channel state information of the uplink target signal is obtained by receiving the uplink probe reference signal sent by the target user.

[0032] Furthermore, in step S2, the joint optimization model is oriented towards A multi-user joint optimization model targeting multiple users is established, wherein the objective function is specified as a weighted sum of the uplink received signal interference plus noise ratio for each target user, i.e.:

[0033]

[0034] in, for Vido-user receiver beamforming matrix, For the number of receiving array elements, The total number of target users, For the first The uplink signal interference plus noise ratio of the target user For the first Weighting coefficients for each target user , The position vector of the receiving antenna array element is the receiving beamforming weight vector, and the receiving beamforming weight vector is the multi-user receiving beamforming matrix. The column corresponding to the target user.

[0035] Furthermore, in step S6, based on the time-series data of the direction and intensity of the interference waves sensed in the past, the direction of the interference waves in the next time slot is predicted to obtain the predicted value. Spatial diversity observations formed by the receiving antenna moving to different positions in multiple iterations are used to update the incoming wave direction estimates of each cross-link interference source; while ensuring that the change in the position of the receiving antenna array elements in adjacent time slots does not exceed a preset single-step displacement threshold. Under the condition that the single-step movement rate does not exceed the preset upper limit of the movement rate, based on the predicted value, a continuously approximating movement trajectory is formed by discrete step-by-step displacement. While maintaining the target signal receiving gain, a receiving antenna movement path is planned that minimizes the spatial power gain formed by the receiving beam in the direction of the predicted interference wave. This, combined with the updating of the receiving beam, completes the tracking and suppression of cross-link interference. For the first Each cross-link interference source at time The predicted direction of the incoming wave, For the current moment, For time slot interval, This is the preset single-step displacement threshold.

[0036] The advantages of this invention compared to the prior art are:

[0037] 1. This invention forms a depth space null in the interference direction by combining the degree of freedom of the receiving antenna position and the degree of freedom of the receiving beamforming weight. The cross-link interference suppression depth is improved by more than 20dB compared with the existing fixed antenna scheme, which greatly improves the uplink receiving performance. Furthermore, by jointly sensing multiple cross-link interference sources, implementing priority null based on interference intensity, and adaptively shrinking the moving area, strong interference is suppressed first under the condition of limited null dimension, and the position search convergence is accelerated, thereby enhancing the robustness of interference suppression in multi-interference source scenarios.

[0038] 2. This invention eliminates the need for information exchange and coordination between base stations throughout the entire process, optimizes only the receiving antenna position and receiving beam, and incurs no additional signaling overhead. It is compatible with scenarios where existing solutions are not applicable, such as non-cooperative networking and networking with equipment from different vendors.

[0039] 3. This invention resolves the contradiction between interference suppression and downlink coverage by concentrating all optimized configurations at the receiving end, without affecting the downlink coverage and transmission performance of the base station. Furthermore, by adopting a hybrid beamforming architecture, it achieves deep interference suppression with two degrees of freedom: the analog spatial domain formed by the receiving antenna position and the digital domain formed by digital beamforming. This significantly reduces the number of RF links, hardware costs, and power consumption, and provides greater engineering deployability.

[0040] 4. This invention dynamically updates and optimizes the model based on real-time perceived interference and channel state information, and adjusts the receiving antenna position and beamforming. It can adapt to complex networking scenarios with moving interference sources and dynamically changing interference intensity and direction, making it more environmentally adaptable. Furthermore, by tracking moving interference sources and planning continuous trajectory of receiving antenna positions, it uses spatial diversity observation to update the interference arrival direction estimation. Under the constraints of single-step displacement threshold and moving rate, it constructs a continuous approximation trajectory with discrete step displacement, upgrading interference suppression from a jump response to continuous tracking suppression, significantly improving the adaptability to dynamic interference environments.

[0041] 5. This invention applies a joint optimization scheme of movable antenna position and receiving beamforming to sub-band full-duplex large-scale networking, fundamentally solving the bottleneck of cross-link interference between base stations that restricts its large-scale deployment. It can achieve deep interference suppression without complex cooperative networking configuration. Furthermore, through multi-user uplink joint optimization and near real-time interference suppression decision-making by end-to-end deep neural networks, it takes into account the mutual interference of multiple target users, significantly improves the overall uplink capacity and spectrum utilization of the system, and greatly reduces the online solution latency. Attached Figure Description

[0042] The accompanying drawings, which form part of this application, are used to provide a further understanding of the application and to make other features, objects, and advantages of the application more apparent. The illustrative embodiments and descriptions of this application are used to explain the application and do not constitute an undue limitation of the application.

[0043] In the attached diagram:

[0044] Figure 1 This is a flowchart of the sub-band full-duplex interference suppression method based on a movable antenna according to the present invention.

[0045] Figure 2 This is a schematic diagram of the sub-band full-duplex interference suppression method based on a movable antenna according to the present invention.

[0046] Figure 3 This is a schematic diagram of the method for joint sensing and differentiated suppression of interference sources across multiple cross-links according to the present invention.

[0047] Figure 4 This is a schematic diagram of the adaptive shrinkage of the moving region and the multi-source zero trap constraint method of the present invention. Detailed Implementation

[0048] The detailed description of the following embodiments is used to exemplify the principles of this application, but should not be used to limit the scope of this application. That is, the sub-band full-duplex interference suppression method based on movable antennas in this application is not limited to the described embodiments.

[0049] The present invention will be further described below with reference to embodiments.

[0050] Example 1

[0051] like Figure 1-2 As shown, this embodiment uses a cross-vendor networking scenario as an example to further illustrate the present invention. Base station A is set as the disturbed base station operating in sub-band full-duplex mode. Base station A includes components from... A receiver array composed of movable antenna elements, where each element can... The system can move freely within a two-dimensional planar area. An adjacent interfering base station B exists, and the downlink transmit signal from base station B causes strong cross-link interference to the uplink receive subband of base station A. Base stations A and B belong to different manufacturers and have no Xn interface signaling interaction. Base station A is equipped with a movable receive antenna array and a transmit antenna array; the transmit array can also be a fixed antenna array. By jointly optimizing and controlling the antenna positions of the receive antenna array and the receive beamforming matrix, base station A can create a deep spatial null in the direction of cross-link interference caused by interfering base station B, without affecting signal reception for user 1 and user 2, thereby increasing the uplink signal-to-noise ratio performance.

[0052] In this embodiment, the operating frequency is 28 GHz, and the receiving array is initially arranged in a uniform linear array with the spacing between adjacent elements being half the operating wavelength. During the optimization process, each element can move freely within a two-dimensional planar area of ​​0.5 m × 0.5 m. The number of elements in the receiving array is determined. =16, each array element can move freely within a 0.5m × 0.5m two-dimensional planar area, the receiver adopts a hybrid beamforming architecture, and the number of RF links is... =4, less than the number of array elements 16; Base station A can be simultaneously interfered with by the cross-links of multiple neighboring interfering base stations and serve multiple target users.

[0053] The sensing module of base station A obtains the current direction of arrival of interference by measuring the downlink reference signal transmitted by base station B. and interference channel matrix The downlink reference signal includes a synchronization signal block or a channel state information reference signal. Simultaneously, base station A obtains the channel state information of the target signal by receiving the uplink probe reference signal sent by the target user. ,in To receive the current position coordinate vector of the array element, base station A monitors the cross-link interference intensity and direction of interference waves of the neighboring interfering base station B in real time through its own channel sensing module. At the same time, it senses the channel status information of the uplink target signal of its own base station. No information exchange with neighboring base stations is required throughout the process.

[0054] like Figure 3 As shown, when base station A detects multiple neighboring interfering base stations, it senses the cross-link interference information of each neighboring interfering base station, obtaining the interference direction of multiple cross-link interference sources and the interference channel matrix, denoted as follows: and ;in, For the first The direction of incoming waves from each cross-link interference source For the first The vector at the location of the cross-link interference sources in the receiving antenna array element is: Interference channel matrix at time, , This represents the total number of cross-link interference sources. In this embodiment, base station A estimates the direction of arrival of the interference wave and the interference channel by measuring the synchronization signal blocks and channel state information reference signals transmitted by each interfering base station, and monitors... = Two neighboring interfering base stations, namely base station B and base station C, were used to measure the direction of interference waves from the two cross-link interference sources at 120° and 200°, respectively. Uplink channel state information was obtained by receiving uplink sounding reference signals sent by each target user.

[0055] The processor of base station A invokes a joint optimization program to construct a joint optimization model for the receiving antenna position and receiving beamforming based on the interference information and uplink channel state information obtained from sensing. This joint optimization model uses maximizing the signal-to-interference-plus-noise ratio (SNR) of the uplink received signal at this base station as the objective function and sets constraints. These constraints include ensuring that the position coordinates of all elements of the receiving antenna are within a preset two-dimensional planar movement area and that the spatial power gain formed by the receiving beam in the direction of arrival of all adjacent interfering base stations is lower than a preset null threshold. In the constructed joint optimization model, the transmitting and receiving antennas of this base station are deployed separately; only the position of the receiving antenna is adjusted, while the position and transmission configuration of the transmitting antenna remain fixed throughout the process.

[0056] like Figure 4 As shown, in this embodiment, the position of the receiving antenna is considered as a movable spatial degree of freedom. By adjusting the geometric layout of the receiving array, the equivalent channel response of the receiving array to cross-link interference is changed. Base station A dynamically adjusts the center and range of the preset two-dimensional moving area based on the direction of the interference wave and the direction of the uplink target signal obtained by sensing. The moving area is shrunk to a feasible area that includes the cross-link interference null constraint and the target signal receiving gain constraint, so that the moving areas corresponding to the two adjacent rounds of optimization satisfy the following conditions. The constraint also includes that the spatial power gain formed by the received beam in the direction of arrival of each cross-link interference source is lower than the corresponding preset null threshold, i.e.:

[0057]

[0058] This embodiment takes each zero threshold. = -40dB; when the total number of cross-link interference sources When the number of directions that the receiving array can simultaneously form nulls is greater than the number of directions, null constraints are set sequentially from strongest to weakest according to the interference intensity of each cross-link interference source.

[0059] Furthermore, the joint optimization model in this embodiment is a multi-user joint optimization model oriented towards multiple target users. The objective function is the weighted sum of the uplink signal interference plus noise ratio for each target user. = 3 target users, including user 1 and user 2, each with a weighting coefficient =1 / 3, that is:

[0060]

[0061] The processor at base station A uses an alternating iterative strategy to solve the joint optimization model. First, the current antenna position is fixed. The optimal receiving beamforming weight vector that minimizes the uplink received signal error is calculated based on the minimum mean square error algorithm. To solve for the beamforming vector, a minimum mean square error algorithm is employed to suppress cross-link interference power while ensuring the recovery quality of the uplink target signal by suppressing additive noise and signal distortion. Then, the aforementioned beamforming vector is fixed. Using the coordinates of the antenna array elements as the dimension of the particle swarm, the particle swarm optimization algorithm is employed to search for the optimal coordinates within a pre-defined two-dimensional movement region. The fitness function of each particle is defined as the uplink received signal interference plus noise ratio at its current position. The set of antenna positions that maximizes the signal interference plus noise ratio and satisfies the null depth constraint is searched through iterative updates of particle velocity and position. For the non-convex antenna position search problem, the particle swarm optimization algorithm maps the two-dimensional coordinates of each antenna element to the spatial position of the particles. With maximizing the uplink received signal interference plus noise ratio as the fitness objective, it achieves rapid localization of the optimal physical sampling point in complex channel environments by iteratively updating the individual optimal and global optimal solutions of the particles. Through the coordinated iteration of the above alternating iterative strategy, the degree of freedom bottleneck of fixed antenna arrays in interference suppression is broken.

[0062] In this embodiment, a deep neural network is pre-built and trained. The interference information and uplink channel state information acquired by sensing are input into the deep neural network, which outputs low-dimensional compressed receiving antenna position features and receiving beamforming features to recover the estimated receiving antenna position. With receive beamforming vector estimation The initial population and the initial solution of the minimum mean square error algorithm were respectively used as the initial population for the particle swarm optimization algorithm and the initial solution for the minimum mean square error algorithm. The particle swarm optimization algorithm searches for the optimal position coordinates within the shrunken moving area with a population size of 100 and a maximum number of iterations of 200. The minimum mean square error algorithm ensures the recovery quality of the uplink target signal by suppressing additive noise and signal distortion while suppressing cross-link interference power. After solving, the spatial power gain formed by the received beam at 120° and 200° of the direction of arrival of the two cross-link interference sources after optimization in this embodiment is -47dB and -45dB, respectively, both of which are lower than the preset null threshold of -40dB. The uplink signal interference plus noise ratio of the three target users is improved from 8dB, 6dB and 7dB before optimization to 15dB, 13dB and 14dB after optimization, respectively. The weighted average signal interference plus noise ratio reaches 14dB, which is about 7dB higher than before optimization.

[0063] The control unit of base station A sends drive commands to the micro stepper motor. Each receiving array element follows the solved optimal coordinates A physical shift is performed, and the baseband processing unit immediately applies the corresponding new beamforming weights. The beamforming module adjusts the receive beam weights in real time based on the optimal receive beamforming matrix obtained from the joint optimization solution, forming depth spatial nulls that meet the preset threshold requirements in the interference direction, thus completing the optimized configuration of the uplink receive beam.

[0064] Base station A continuously monitors the bit error rate and signal-to-noise ratio (SNR) of the uplink subband. When it detects a change in the downlink beam direction of base station B, leading to a change in cross-link interference characteristics and a decrease in SNR exceeding 3dB, it automatically triggers the next round of joint optimization iteration using the particle swarm optimization algorithm and the minimum mean square error algorithm, achieving a dynamic closed-loop interference suppression. After completing the antenna position and beamforming adjustments, base station A monitors the uplink received signal SNR and cross-link interference suppression effect in real time. If the change in channel state interference direction or interference intensity exceeds a preset threshold, the above steps are repeated to update the optimization model and re-solve for the optimal solution, achieving dynamic adaptive adjustment of interference suppression.

[0065] In this embodiment, when the channel state, interference direction, or interference intensity changes exceed a preset threshold, base station A predicts the interference direction for the next time slot based on historically sensed interference direction and interference intensity time-series data, and obtains a predicted value. Spatial diversity observations formed by the receiving antenna moving to different positions in multiple iterations are used to update the incoming wave direction estimates of each cross-link interference source; while ensuring that the change in the position of the receiving antenna array elements in adjacent time slots does not exceed a preset single-step displacement threshold. Under the conditions of 5mm and a single-step movement rate not exceeding the preset upper limit of movement rate, a continuously approximating movement trajectory is formed by discrete step displacement based on the predicted value. While maintaining the target signal receiving gain, a receiving antenna movement path is planned that minimizes the spatial power gain of the receiving beam in the predicted direction of interference. This, combined with the updating of the receiving beam, completes the tracking and suppression of cross-link interference. After tracking and updating, the estimation error of the direction of arrival of each interference source is controlled within 2°, the receiving beam is always aligned with the direction of interference to form a deep null, and the uplink signal interference-to-noise ratio of each target user remains above 13dB.

[0066] It should be noted that the combination of the technical features in this case is not limited to the combination methods described in the claims of this case or the combination methods described in the specific embodiments. All technical features described in this case can be freely combined or combined in any way, unless they contradict each other.

[0067] It should also be noted that the embodiments listed above are merely specific embodiments of the present invention. Obviously, the present invention is not limited to the above embodiments, and similar changes or modifications made thereto are those that can be directly derived or easily conceived by those skilled in the art from the content disclosed in the present invention, and should all fall within the protection scope of the present invention.

Claims

1. A sub-band full-duplex interference suppression method based on a movable antenna, characterized in that, Includes the following steps: Step S1, Interference and Channel Awareness: The base station monitors the cross-link interference information of neighboring interfering base stations in real time through the channel awareness module, and at the same time senses the channel status information of the uplink target signal of its own base station. Step S2, Optimization Model Construction: Based on the interference information and uplink channel state information obtained by sensing, a joint optimization model of receiving antenna position and receiving beamforming is constructed. The joint optimization model takes maximizing the signal-to-interference-plus-noise ratio of the uplink received signal of this base station as the objective function and is subject to constraints. Among them, the receiving antenna position is a movable spatial degree of freedom. By adjusting the geometric layout of the receiving array, the equivalent channel response of the receiving array to cross-link interference is changed. Step S3, Joint Optimization: Solve the joint optimization model to obtain the optimal relative position of the receiving antenna array and the optimal receiving beamforming matrix; Step S4, Antenna position adjustment: Based on the optimal relative position, control the receiving antenna array to move to the target position within a preset two-dimensional moving area; Step S5, Receive beamforming adjustment: Based on the optimal receive beamforming matrix obtained by joint optimization, adjust the receive beam weight in real time to form a depth space null that meets the preset threshold requirements in the interference direction; Step S6, Effect Verification and Iterative Update: Monitor the changes in the uplink received signal interference plus noise ratio or cross-link interference. When the channel state, interference direction or interference intensity exceeds the preset threshold, re-execute steps S1 to S5.

2. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S1, the cross-link interference information includes CLI interference intensity and interference direction of arrival; when this base station detects multiple neighboring interfering base stations, it senses the cross-link interference information of each neighboring interfering base station to obtain the interference direction of arrival and interference channel matrix of multiple cross-link interference sources, which are denoted as follows: and ;in, For the first The direction of incoming waves from each cross-link interference source For the first The vector at the location of the cross-link interference sources in the receiving antenna array element is: Interference channel matrix at time, , This represents the total number of cross-link interference sources.

3. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S2, the constraints include: the position coordinates of all elements of the receiving antenna are within a preset two-dimensional planar moving area; the spatial power gain formed by the receiving beam in the direction of arrival of all adjacent interfering base stations is lower than a preset null threshold; based on the sensing and acquired direction of arrival of the interfering wave and the direction of arrival of the uplink target signal, the center and range of the preset two-dimensional moving area are dynamically adjusted, shrinking the two-dimensional moving area to a feasible area that includes the position coordinates that satisfy the cross-link interference null constraint and the target signal receiving gain constraint, and ensuring that the moving areas corresponding to the two adjacent optimization rounds satisfy the following conditions. The constraint also includes that the spatial power gain formed by the received beam in the direction of arrival of each cross-link interference source is lower than the corresponding preset null threshold, i.e.: in, and All 3D column vector, For the number of receiving array elements, For receiving beamforming weight vector, For the receiving antenna array in position vector Corresponding to the direction of incoming wave The array response vector, The position vector of the receiving antenna array element. For the first The direction of incoming waves from each cross-link interference source For the first Preset zero-depression thresholds corresponding to each cross-link interference source This is the number of the cross-link interference source. This represents the total number of cross-link interference sources. and The first Wheel and the first The two-dimensional movement region corresponding to the round optimization. To optimize round numbering, it must be a positive integer; The positional freedom of the receiving antenna is used to adjust the geometric layout of the receiving array, optimize the spatial response of the receiving array when the number of array elements is the same, and enhance the null depth formed by the receiving beam in the direction of each cross-link interference source. When the total number of cross-link interference sources is greater than the number of directions in which the receiving array can simultaneously form nulls, null constraints are set in order of the interference intensity of each cross-link interference source from strong to weak.

4. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S2, the transmitting and receiving antennas of the base station are deployed separately, with only the position of the receiving antenna being adjusted, while the position and transmission configuration of the transmitting antenna remain fixed. The receiving end adopts a hybrid beamforming architecture, with the analog domain including an analog spatial domain determined by the position of the receiving antenna array elements and an analog phase domain determined by the phase shifter, and the digital domain consisting of a digital beamforming matrix. Confirmed, number of RF links Less than the number of array elements ;in, For digital beamforming matrix, For the number of radio frequency links, This represents the number of receiving array elements.

5. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S3, the joint optimization model is solved using a constrained iterative optimization algorithm.

6. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S3, an alternating iterative strategy is used to solve the joint optimization model: when the current receiving antenna position is fixed, the optimal receiving beamforming matrix is ​​determined based on the minimum mean square error algorithm; when the current receiving beamforming matrix is ​​fixed, the optimal position coordinates are searched within a preset position range based on the particle swarm optimization algorithm; a deep neural network is pre-constructed and trained, and the interference information and uplink channel state information obtained by sensing are input into the deep neural network, which outputs low-dimensional compressed receiving antenna position features and receiving beamforming features to recover the estimated receiving antenna position. With receive beamforming vector estimation Wherein, the receiving antenna position estimation As the initial population for the particle swarm optimization algorithm, the received beamforming vector estimation... This serves as the initial solution for determining the optimal receive beamforming matrix based on the minimum mean square error algorithm.

7. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 6, characterized in that, When searching for the optimal position coordinates based on the particle swarm optimization algorithm, the two-dimensional coordinates of each element in the receiving antenna array are mapped to the spatial position of the particle. The ratio of uplink received signal interference plus noise is used as the fitness function, and the search is carried out by iteratively updating the individual optimal and global optimal solutions of the particles.

8. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 2, characterized in that, In step S1, the direction of the incoming interference wave is obtained by measuring the downlink reference signal transmitted by a nearby interfering base station; the channel state information of the uplink target signal is obtained by receiving the uplink probe reference signal sent by the target user.

9. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S2, the joint optimization model is oriented towards A multi-user joint optimization model targeting multiple users is established, wherein the objective function is specified as a weighted sum of the uplink received signal interference plus noise ratio for each target user, i.e.: in, for Vido-user receive beamforming matrix, For the number of receiving array elements, The total number of target users, For the first The uplink signal interference plus noise ratio of the target user For the first Weighting coefficients for each target user , The position vector of the receiving antenna array element is the receiving beamforming weight vector, and the receiving beamforming weight vector is the multi-user receiving beamforming matrix. The column corresponding to the target user.

10. The sub-band full-duplex interference suppression method based on a movable antenna according to claim 1, characterized in that, In step S6, based on the time-series data of the direction and intensity of the interference waves sensed in the past, the direction of the interference waves in the next time slot is predicted to obtain the predicted value. ; Spatial diversity observations formed by the receiving antenna moving to different positions in multiple iterations are used to update the incoming direction estimates of interference sources in each cross-link; this is done while ensuring that the positional change of the receiving antenna elements in adjacent time slots does not exceed a preset single-step displacement threshold. Under the condition that the single-step movement rate does not exceed the preset upper limit of the movement rate, based on the predicted value, a continuously approximating movement trajectory is formed by discrete step-by-step displacement. While maintaining the target signal receiving gain, a receiving antenna movement path is planned that minimizes the spatial power gain formed by the receiving beam in the direction of the predicted interference wave. This, combined with the updating of the receiving beam, completes the tracking and suppression of cross-link interference. For the first Each cross-link interference source at time The predicted direction of the incoming wave, For the current moment, For time slot interval, This is the preset single-step displacement threshold.

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