Interference suppression method, apparatus, device, and storage medium

Abstract

The application provides an interference suppression method, device, equipment and storage medium, and relates to the technical field of communication. The method comprises the following steps: introducing an optimal phase misalignment angle to perform phase optimization on a serving cell; based on the residual interference power spectral density prediction value of each candidate time-frequency resource block at a future preset time after phase optimization of the serving cell, the bandwidth of each candidate time-frequency resource block and the corresponding serving cell useful signal power, the expected signal quality of each candidate time-frequency resource block at the future preset time is calculated; in response to the expected signal quality of the candidate time-frequency resource block being less than a preset quality threshold, a candidate time-frequency resource block avoidance strategy is performed on a target user; otherwise, a candidate time-frequency resource block allocation strategy is performed on the target user, and the serving cell adopts a transmission signal after phase optimization on the candidate time-frequency resource block. The application can realize fast response to dynamic interference, low signaling overhead and support for phase-level interference suppression.

Description

Technical Field

[0001] This invention relates to the field of communication technology, and in particular to an interference suppression method, an interference suppression device, a computer device, and a computer-readable storage medium. Background Technology

[0002] In 5G NR (New Radio) hybrid macro-micro networks, in order to improve capacity, cover blind spots, and enhance the user experience at the edge, operators will deploy a large number of cell nodes (including outdoor small base stations, indoor pico base stations, home base stations, etc.).

[0003] However, under co-channel deployment, the following problems exist: 1) Downlink interference: Due to coverage overlap between cells, especially at cell edges, user equipment (UE) may receive downlink signals from multiple cells. These signals have the same spectrum, directly causing strong interference; 2) Uplink interference: When uplink receivers (gNB receivers) of multiple cells simultaneously listen to the same frequency, the uplink signals of neighboring users will be mistakenly received as interference, reducing demodulation performance.

[0004] To address these issues, related technologies have proposed schemes such as eICIC (Enhanced Inter-Cell Interference Coordination), FeICIC (Further Enhanced Inter-Cell Interference Coordination), CoMP (Coordinated Multi-Point), CLI mitigation (Cross-Link Interference Mitigation), and Dynamic TDD CLI (Dynamic Time Division Duplex Cross-Link Interference Mitigation). However, these schemes suffer from technical problems such as slow response to dynamic interference, high signaling overhead, and difficulty in supporting phase-level interference suppression. Summary of the Invention

[0005] This invention was developed to at least partially address the technical problems of existing interference suppression schemes, such as slow response to dynamic interference, high signaling overhead, and difficulty in supporting phase-level interference suppression.

[0006] According to one aspect of the present invention, an interference suppression method is provided, comprising: Phase optimization is performed by introducing an optimal phase misalignment angle in the serving cell; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell. Obtain the predicted residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization; Based on the predicted residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block, the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization is calculated. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold, a candidate time-frequency resource block avoidance strategy is executed for the target user. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to a preset quality threshold, a candidate time-frequency resource block allocation strategy is executed for the target user, and the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein, the target user is a user accessing the serving cell.

[0007] Optionally, the method for obtaining the optimal phase misalignment angle includes: Based on the complex channel coefficients from the serving cell to the target user, the complex channel coefficients from each interfering neighbor cell of the serving cell to the target user, the transmit phase difference between the serving cell and each interfering neighbor cell, and multiple candidate phase rotation angles, an interference suppression objective function is constructed. With minimizing the interference suppression objective function as the optimization objective, the optimal phase rotation angle is obtained from the multiple candidate phase rotation angles as the best phase misalignment angle.

[0008] Optionally, the interference suppression objective function is: ; in, The objective function is to suppress interference. The candidate phase rotation angle; This is the interference weighting factor, used to measure the degree of interference contribution of interfering neighbor cell k to the target users accessed by the serving cell, where K is the number of interfering neighbor cells of the serving cell. The complex channel coefficients from the serving cell to the target user at time t; The complex channel coefficients from the interfering neighboring cell k to the target user at time t; The transmit phase difference between the serving cell and the interfering neighbor cell k at time t; t is the current time.

[0009] Optionally, the acquisition of the predicted residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization includes: Based on the predicted interference power of each candidate time-frequency resource block of the serving cell at a future preset time before phase optimization, and the residual interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization, the percentage reduction in interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization is calculated. Based on the interference power reduction ratio and the predicted interference power spectral density of each candidate time-frequency resource block of the serving cell before phase optimization, the predicted residual interference power spectral density of each candidate time-frequency resource block of the serving cell after phase optimization is calculated.

[0010] Optionally, the predicted interference power value for each candidate time-frequency resource block at a future preset time before phase optimization is obtained by the following formula: ; in, To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. To predict the time offset; The bandwidth of the candidate time-frequency resource block; After phase optimization, the residual interference power of each candidate time-frequency resource block in the serving cell at a future preset time is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted residual interference power is generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them. To interfere with the interference signal of neighboring cell k at time k The signal amplitude on the candidate time-frequency resource block with frequency f; t is the current time. The time offset is used for prediction; K is the number of interfering neighboring cells of the serving cell; To interfere with the original phase of neighboring cell k; This is the optimal phase misalignment angle.

[0011] Optionally, the percentage reduction in interference power at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The percentage reduction in interference power on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted residual interference power generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them; t is the current time. To predict the time offset; The predicted residual interference power spectral density of each candidate time-frequency resource block in the serving cell after phase optimization is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0012] Optionally, the method for obtaining the predicted interference power spectral density includes: Based on the interference power spectral density of each candidate time-frequency resource block at the current moment before phase optimization and the predicted value of the total change in interference power spectral density of each candidate time-frequency resource block over a future preset time period, the initial predicted value of interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization is calculated; wherein, the future preset time is the end point of the future preset time period. Based on the initial predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization and the predicted value of the interference change caused by periodic fluctuations at a future preset time for each candidate time-frequency resource block, the final predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization is calculated.

[0013] Optionally, the initial predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; The interference power spectral density measured on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; t is the current time. To predict the time offset; The rate of change of interference power spectral density of candidate time-frequency resource blocks with frequency f in the serving cell before phase optimization; To serve the future time period on the candidate time-frequency resource block of frequency f before phase optimization in the service cell The predicted value of the total change in the interference power spectral density; The final predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0014] Optionally, the predicted value of the disturbance change is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on a candidate time-frequency resource block with frequency f; The peak amplitude of the periodic fluctuation component on the candidate time-frequency resource block at frequency f before phase optimization of the serving cell; The fluctuation period length of the periodic fluctuation component in the serving cell before phase optimization; To represent the phase of the periodic fluctuation component on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; where t is the current time. This is for predicting the time offset.

[0015] Optionally, the expected signal quality is calculated using the following formula: ; Among them, After phase optimization, the service cell is served at the time... The expected SINR value on the candidate time-frequency resource block with frequency f; It is a moment The useful signal power received by the target user from the serving cell on a candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; This represents the thermal noise power spectral density. The bandwidth of the candidate time-frequency resource block.

[0016] According to another aspect of the present invention, an interference suppression device is provided, comprising: The serving cell phase optimization module is configured to introduce an optimal phase misalignment angle in the serving cell for phase optimization; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell. The residual interference prediction module is configured to obtain the predicted value of the residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization. The expected signal quality calculation module is configured to calculate the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization, based on the predicted value of the residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block. The resource scheduling and avoidance module is configured to, for each candidate time-frequency resource block, execute a candidate time-frequency resource block avoidance strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold; and for each candidate time-frequency resource block, execute a candidate time-frequency resource block allocation strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to the preset quality threshold, wherein the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein the target user is a user accessing the serving cell.

[0017] According to another aspect of the present invention, a computer device is provided, including a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor performs the aforementioned interference suppression method.

[0018] According to another aspect of the present invention, a computer-readable storage medium is provided having a computer program stored thereon, wherein when the computer program is executed by a processor, the processor performs the aforementioned interference suppression method.

[0019] The technical solution provided by this invention may include the following beneficial effects: The interference suppression method and apparatus provided by this invention introduces an optimal phase misalignment angle in the serving cell for phase optimization, calculates the expected signal quality based on the predicted residual interference, and dynamically performs resource avoidance or allocation based on the comparison result of the expected signal quality and a threshold, using the phase-optimized transmission signal during allocation. This simultaneously achieves a lightweight closed loop that links short-term interference prediction, transmitter phase misalignment, and time-frequency scheduling, thereby enabling rapid response to dynamic interference, low signaling overhead, and support for phase-level interference suppression.

[0020] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims and drawings. Attached Figure Description

[0021] The accompanying drawings are provided to further understand the technical solutions of the present invention and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the technical solutions of the present invention, and do not constitute a limitation on the technical solutions of the present invention.

[0022] Figure 1 This is a flowchart illustrating an interference suppression method provided in an embodiment of the present invention; Figure 2 A flowchart illustrating another interference suppression method provided in an embodiment of the present invention; Figure 3 This is a schematic diagram of the interference suppression device provided in an embodiment of the present invention; Figure 4 This is a schematic diagram of the structure of a computer device provided in an embodiment of the present invention. Detailed Implementation

[0023] To make the objectives, technical solutions, and advantages of the embodiments of the present invention clearer, the specific implementation methods of the present invention will be described in detail below with reference to the accompanying drawings. It should be understood that the specific implementation methods described herein are for illustration and explanation only and are not intended to limit the present invention.

[0024] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this invention are used to distinguish similar objects and are not necessarily used to describe a set order or sequence; furthermore, in the absence of conflict, the embodiments and features in the embodiments of this invention can be arbitrarily combined with each other. In the following description, the use of suffixes such as "module," "component," or "unit" to represent elements is only for the convenience of the description of this invention and has no inherent meaning. Therefore, "module," "component," or "unit" can be used interchangeably.

[0025] The following interference suppression schemes have been proposed in related technologies: eICIC / FeICIC: Reduce downlink neighbor cell interference in LTE / NR heterogeneous networks through semi-static time-domain silence (ABS, Almost Blank Subframe) or enhanced interference cancellation; FeICIC further introduces interference cancellation technology at the receiver. CoMP: Joint transmission or cooperative decoding at the transmitter / receiver end, eliminating interference or turning interference into useful signals through shared CSI (Channel State Information) and joint scheduling; CLI mitigation / Dynamic TDD CLI: Dynamic TDD (Time Division Duplexing) introduces uplink / downlink misalignment interference risks.

[0026] However, the shortcomings of eICIC / FeICIC are that they are semi-static countermeasures at the time slot / power level, which slow down the response to short-term burst interference and uplink / downlink cross interference (especially dynamic-TDD, dynamic time division duplex); and the spectrum utilization is limited in ultra-dense scenarios.

[0027] The shortcomings of CoMP are that it requires low-latency, high-bandwidth Xn / X2 level cooperative signaling and accurate CSI (Channel State Information); in large-scale ultra-dense networks, the signaling / computation burden is large and the real-time performance is poor. The shortcoming of CLI mitigation / Dynamic TDD CLI is that solving CLI problems often focuses on TDD frame configuration coordination or beam pairing, with less attention paid to phase-level transmit control.

[0028] To address the aforementioned problems, this invention provides an interference suppression scheme that simultaneously integrates short-term interference prediction, base station transmitter phase misalignment, and real-time time-frequency scheduling to form a lightweight, millisecond-level closed-loop implementation system. This achieves rapid response to dynamic interference, low signaling overhead, and supports phase-level interference suppression. Specific embodiments are described in detail below.

[0029] Figure 1 This is a schematic flowchart illustrating an interference suppression method provided in an embodiment of the present invention. Figure 1 As shown, the method includes the following steps S101 to S105.

[0030] S101. Introduce an optimal phase misalignment angle in the serving cell for phase optimization; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell; S102. Obtain the predicted value of the residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization; S103. Based on the predicted residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block, the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization is calculated. S104. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold, a candidate time-frequency resource block avoidance strategy is executed for the target user; S105. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to a preset quality threshold, a candidate time-frequency resource block allocation strategy is executed for the target user, and the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein, the target user is a user accessing the serving cell.

[0031] In this embodiment, the optimal phase misalignment angle is introduced in the serving cell for phase optimization. The expected signal quality is calculated based on the predicted residual interference. Resource avoidance or allocation is dynamically performed according to the comparison result of the expected signal quality and the threshold. The phase-optimized transmission signal is used during allocation. This achieves a lightweight closed loop that links short-term interference prediction, transmitter phase misalignment and time-frequency scheduling. This enables rapid response to dynamic interference, low signaling overhead and support for phase-level interference suppression.

[0032] In one specific embodiment, in step S101, the method for obtaining the optimal phase misalignment angle includes the following steps S1a and S1b.

[0033] S1a. Based on the complex channel coefficients from the serving cell to the target user, the complex channel coefficients from each interfering neighbor cell of the serving cell to the target user, the transmit phase difference between the serving cell and each interfering neighbor cell, and multiple candidate phase rotation angles, construct the interference suppression objective function; S1b. With minimizing the interference suppression objective function as the optimization objective, the optimal phase rotation angle is obtained from the multiple candidate phase rotation angles as the best phase misalignment angle.

[0034] In this embodiment, by constructing an interference suppression objective function and solving for the optimal angle from multiple candidate phase rotation angles as the best phase misalignment angle, only a discrete search or simple optimization needs to be performed locally, without the need for inter-cell cooperative signaling, thus resulting in extremely low signaling overhead. Furthermore, the solution process can be completed in milliseconds, enabling rapid tracking of interference changes and improving the real-time performance of phase optimization.

[0035] In one specific implementation, the interference suppression objective function constructed in step S1a is: ; in, The objective function is to suppress interference. The candidate phase rotation angle; This is the interference weighting factor, used to measure the degree of interference contribution of interfering neighbor cell k to the target users accessed by the serving cell, where K is the number of interfering neighbor cells of the serving cell. The complex channel coefficients from the serving cell to the target user at time t; The complex channel coefficients from the interfering neighboring cell k to the target user at time t; The transmit phase difference between the serving cell and the interfering neighbor cell k at time t; t is the current time.

[0036] In this embodiment, the interference suppression objective function integrates the complex channel coefficients from the serving cell and each interfering neighboring cell to the target user, the transmit phase difference, and the interference weighting factor. By minimizing the weighted superposition power, the function accurately reflects the differentiated impact of different interference sources on the target user. The optimal phase misalignment angle obtained thereby can more accurately suppress coherent interference and improve phase-level interference suppression capability.

[0037] In one specific embodiment, step S102 includes the following steps S1021 and S1022.

[0038] S1021. Based on the predicted interference power of each candidate time-frequency resource block of the serving cell at a future preset time before phase optimization, and the residual interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization, the percentage reduction of interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization is calculated. S1022. Based on the interference power reduction ratio and the predicted interference power spectral density of each candidate time-frequency resource block of the serving cell at a future preset time before phase optimization, the predicted residual interference power spectral density of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization is calculated.

[0039] In this embodiment, the interference power reduction ratio is first calculated, and then applied to the original interference power spectral density prediction value to obtain the residual interference power spectral density prediction value, avoiding the high-complexity calculation of direct complex superposition. Therefore, it is beneficial to update the residual interference value of each resource block in real time within a millisecond-level scheduling cycle, meeting the real-time requirements of dynamic scheduling.

[0040] In one specific implementation, the predicted interference power value for each candidate time-frequency resource block at a future preset time in step S1021 before phase optimization is performed is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. To predict the time offset; The bandwidth of the candidate time-frequency resource block.

[0041] In this embodiment, the original total interference power is directly obtained using the predicted interference power spectral density and resource block bandwidth. The power spectral density in the frequency domain is converted into a resource block-level power value, which facilitates comparison with the subsequent residual interference power. This allows for accurate calculation of the interference reduction ratio, providing quantitative basic data for evaluating the phase optimization effect.

[0042] In one specific implementation, the residual interference power at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization in step S1021 is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted residual interference power is generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them. To interfere with the interference signal of neighboring cell k at time k The signal amplitude on the candidate time-frequency resource block with frequency f; t is the current time. The time offset is used for prediction; K is the number of interfering neighboring cells of the serving cell; To interfere with the original phase of neighboring cell k; This is the optimal phase misalignment angle.

[0043] In this embodiment, the total residual interference power is obtained by superimposing the amplitude and phase (including the optimal phase misalignment angle) of each interfering neighboring cell. This accurately reflects the vector superposition effect of each interfering signal at the target user's receiver after phase optimization, rather than a simple power addition. The residual interference power value obtained in this way can truly reflect the degree of suppression of coherent interference by phase optimization, providing a reliable basis for subsequent decision-making.

[0044] In one specific implementation, the percentage reduction in interference power (between 0 and 1) at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization in step S1021 is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The percentage reduction in interference power on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted residual interference power generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them; t is the current time. This is for predicting the time offset.

[0045] In this embodiment, the obtained interference power reduction ratio intuitively reflects the degree of interference suppression achieved by phase optimization. The base station scheduler can quickly determine whether the phase optimization is effective without performing complex number calculations. This ratio also serves as a key coefficient for subsequent residual interference spectral density calculations, making the interference suppression effect visible and quantifiable.

[0046] In one specific implementation, the predicted residual interference power spectral density of each candidate time-frequency resource block at a future preset time after phase optimization in step S1022 is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0047] In this embodiment, the residual interference power spectral density is quickly obtained by utilizing the interference power reduction ratio, avoiding repetitive calculations involving direct complex superposition. Since the ratio calculation already considers the phase relationships of all interference sources (i.e., the interfering neighboring cells of the serving cell), only one multiplication is needed to update the residual interference value. This approach significantly reduces computational complexity and facilitates real-time evaluation of the link quality of each resource block within a millisecond-level scheduling cycle.

[0048] In one specific embodiment, the method for obtaining the predicted interference power spectral density includes the following steps S2a and S2b.

[0049] S2a. Based on the interference power spectral density at the current moment of each candidate time-frequency resource block before phase optimization and the predicted value of the total change in interference power spectral density of each candidate time-frequency resource block over a future preset time period, the initial predicted value of interference power spectral density of each candidate time-frequency resource block before phase optimization is calculated; wherein, the future preset time is the end point of the future preset time period; S2b. Based on the initial predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization and the predicted value of the interference change caused by periodic fluctuations at a future preset time for each candidate time-frequency resource block, the final predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization is calculated.

[0050] In this embodiment, interference power spectral density prediction is divided into two independent steps: linear trend extrapolation and periodic fluctuation compensation. The linear part uses first-order extrapolation to quickly respond to sudden interference changes (such as sudden uplink transmission from a neighboring cell), while the periodic part compensates for regular fluctuations such as TDD uplink / downlink switching. The combination of these two steps ensures both real-time prediction and improved accuracy, enabling phase optimization and scheduling decisions to be based on more reliable interference estimates.

[0051] In one specific implementation, in step S2a, the initial predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; The interference power spectral density measured on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; t is the current time. To predict the time offset; The rate of change of interference power spectral density of candidate time-frequency resource blocks with frequency f in the serving cell before phase optimization; To serve the future time period on the candidate time-frequency resource block of frequency f before phase optimization in the service cell The predicted value of the total change in the interference power spectral density.

[0052] In this embodiment, a first-order linear extrapolation is performed by adding the current measured interference power spectral density value to the product of the interference power spectral density change rate and the time offset. This requires few parameters (only the current value and the change rate are needed), resulting in extremely low computational cost. It can quickly predict future short-term interference trends, meeting the real-time requirements of millisecond-level closed-loop control. Simultaneously, this extrapolation result provides a reliable linear benchmark for subsequent periodic compensation, ensuring the stability of the prediction model.

[0053] In one specific implementation, in step S2b, the final predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0054] In this embodiment, a periodic fluctuation compensation value is superimposed on the linear extrapolation result to obtain the final predicted interference power spectral density value, resulting in extremely low computational overhead. Therefore, the final predicted value can integrate the linear trend with other interference variation factors, providing a more accurate interference benchmark for subsequent phase optimization and resource scheduling.

[0055] In one specific implementation, in step S2b, the predicted value of the disturbance change is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on a candidate time-frequency resource block with frequency f; The peak amplitude of the periodic fluctuation component on the candidate time-frequency resource block at frequency f before phase optimization of the serving cell; The fluctuation period length of the periodic fluctuation component in the serving cell before phase optimization; To represent the phase of the periodic fluctuation component on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; where t is the current time. This is for predicting the time offset.

[0056] In this embodiment, the calculation of the periodic fluctuation compensation value adopts a sine function model. Different periodic interference modes (such as TDD uplink / downlink switching cycles of 5ms and 10ms) are flexibly fitted using three parameters: peak amplitude, period length, and current phase. It is easy to estimate using historical data, and once estimated, it can be used for a long time or updated slowly. The entire compensation process does not add any additional signaling interaction, ensuring the lightweight nature of the solution.

[0057] In one specific implementation, in step S103, the expected signal quality is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The expected SINR value on the candidate time-frequency resource block with frequency f; It is a moment The useful signal power received by the target user from the serving cell on a candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; This represents the thermal noise power spectral density. The bandwidth of the candidate time-frequency resource block.

[0058] In this embodiment, the formula for calculating the expected SINR (Signal to Interference plus Noise Ratio) accurately assesses the link quality after phase optimization; a higher value indicates better interference suppression. Based on the comparison between this value and a preset quality threshold, the base station scheduler can reliably determine whether to avoid or allocate resource blocks, ensuring that target users receive transmission quality that meets their service requirements.

[0059] The interference suppression method provided in this invention constructs a lightweight closed-loop mechanism from interference prediction and phase optimization to scheduling decision-making. First, an optimal phase misalignment angle is introduced for the serving cell to optimize the transmit phase. This angle is obtained by locally solving the interference suppression objective function, eliminating the need for inter-cell cooperative signaling and thus completing phase adjustment in milliseconds, enabling rapid response to dynamic interference. Based on this, short-time interference prediction techniques (including linear trend extrapolation and periodic fluctuation compensation) are used to obtain the predicted residual interference power spectral density of each candidate time-frequency resource block at future times. Then, the expected signal quality is calculated by combining the resource block bandwidth and useful signal power. Finally, based on the comparison between the expected signal quality and a preset threshold, resource avoidance or allocation is dynamically executed, and the phase-optimized transmit signal is used during allocation. The entire interference suppression process replaces the high-overhead cooperative signaling in traditional schemes with low-complexity calculations (such as linear extrapolation, proportional operations, and sine compensation), significantly reducing the signaling burden. At the same time, through phase-level fine adjustment and adaptive selection of time and frequency resources, it effectively suppresses coherent interference and improves spectrum utilization, thereby achieving rapid response to dynamic interference, low signaling overhead, and phase-level interference suppression, making it suitable for complex interference environments such as ultra-dense networks.

[0060] Figure 2 This is a schematic flowchart of another interference suppression method provided in an embodiment of the present invention. Figure 2 As shown, the method includes the following steps S201 to S203.

[0061] S201. Real-time interference measurement and short-term interference prediction.

[0062] In densely deployed cell environments, interference is not a static quantity; it fluctuates rapidly over time. First, neighboring cell scheduling strategies change, directly altering the interference environment. For example, when a neighboring cell suddenly schedules a user to begin uplink transmission, this uplink signal enters the serving cell receiver, causing sudden interference. UE location changes; even millimeter-wave or centimeter-level movements alter the interference distribution. Dynamic behaviors such as beam switching and power adjustments also affect interference. If scheduling only focuses on the current interference value, it will be too late to avoid interference peaks. Therefore, it's crucial to predict the interference trend (gradient) in advance to achieve interference prediction. Specifically, this means knowing in advance whether the interference will increase or decrease within a certain time window.

[0063] For each cell c in the target cell set, the average interference power spectral density I is calculated at time t. c (t): .

[0064] Among them, I c(t): The average interference power spectral density of cell c at time t and within the target frequency band [f1,f2] (unit dBm / Hz). B: The width of the target frequency band [f1,f2], i.e., the bandwidth (Hz); P c (f,t): The interference power spectral density (in dBm / Hz) measured in cell c at time t and frequency f, where f∈[f1,f2]. For ease of calculation, P can be set before calculation. c If the unit of (f,t) is converted from dBm / Hz to W / Hz, then the calculated I c The unit of (t) is W / Hz, which is then converted to dBm / Hz.

[0065] The significance of the formula for calculating the average interference power spectral density is to obtain the average interference power spectral density within the target frequency band, eliminating the influence of single-point frequency anomalies.

[0066] Then, the rate of change of interference is obtained using the finite difference method, and the interference gradient G of cell c at time t is calculated. c (t): .

[0067] Where Gc(t): interference gradient (unit: dBm / Hz / ms), representing the rate and direction of interference change. Positive Gc(t) → interference is increasing; negative Gc(t) → interference is decreasing; Δt′: Differential interval, taking one or more TTIs as a time window, i.e., one or more scheduling periods. A TTI (Transmission Time Interval) can be defined as 1ms.

[0068] This step requires predicting the interference level of each time-frequency resource block within the next scheduling cycle (a few milliseconds) before scheduling, rather than simply using the currently measured interference value. This allows subsequent phase misalignment and avoidance strategies to be planned in advance to address interference proactively.

[0069] Based on the historical interference power spectral density sequence I of cell c hist,c (f,tt n For each frequency point f, n=1,2,…,N, the rate of change ΔI of the interference power spectral density of cell c at frequency point f is calculated using a sliding window. c (f). Specifically, ΔI can be calculated using the two-point difference method or the linear regression method. c (f).

[0070] Two-point difference method: .

[0071] Where t is the current time; Δt is the length of the trend observation window (e.g., 20ms), which is much larger than the scheduling period. hist,c (f,t): The interference power spectral density (in dBm / Hz) measured at time t and frequency f in cell c. Since t is the current time, this parameter represents the interference power spectral density measured at the current time. ΔI c (f) is the rate of change of the interference power spectral density of cell c at frequency point f (unit: dBm / Hz / ms, i.e. how many dBm / Hz it changes per millisecond).

[0072] Linear regression method: .

[0073] Where N = Δt / Ts, Ts is the sampling interval, i.e., the time period (in ms) during which the system measures the interference power spectral density; t n It is the time offset relative to the current time t within the window Δt, for example, t1=Δt, t N =0; Is cell c at time ( t - Interference power spectral density (in dBm / Hz) measured at frequency point f.

[0074] Next, a first-order extrapolation + periodic component compensation method is used for short-term disturbance prediction.

[0075] First-order extrapolation: This method uses the time-varying trend of interference power spectral density to predict the interference power spectral density shortly afterward. It assumes that the interference change is approximately linear over a short period (i.e., the interference curve locally approximates a straight line). Based on recent measurement data, the "slope" or "rate of change" ΔI of the interference is first calculated. c (f), combined with the current interference power spectral density I hist,c (f,t), predict the disturbance after a short time τ. : .

[0076] Among them, I pred,linear,c (f,t+τ) represents the initial predicted value of the interference power spectral density of cell c at time (t+τ) and frequency f, where t is the current time and τ is the prediction time offset; I hist,c (f,t) represents the interference power spectral density measured in cell c at time t and frequency f; ΔI c (f) represents the rate of change of the interference power spectral density of cell c at frequency point f.

[0077] Periodic component compensation: Considering that interference in 5G NR, especially in TDD (Time-division Duplex) mode, does not change linearly but fluctuates periodically. For example, the fixed uplink / downlink handover cycle of neighboring cells (e.g., 5ms) can cause particularly high interference in certain subframes. The periodic pattern of service load (e.g., the timing bursts of eMBB scheduling) can cause interference to fluctuate in the same regular way as the service cycle, such as the periodic increase / decrease of interference power spectral density within each scheduling cycle.

[0078] Establish a periodic correction function: .

[0079] Among them, C period,c (f,t+τ): The predicted value of the amount of interference change caused by periodic fluctuations at frequency point f in cell c at future time (t+τ), where τ is the predicted time offset; A p,c (f): The peak amplitude of the periodic fluctuation component of cell c at frequency point f (predicting how much W / Hz it will increase interference). T p,c The fluctuation period length of the periodic fluctuation component in cell c (e.g., 5 ms, 10 ms) is generally greater than the scheduling period. Φ p,c (f,t): The phase of the periodic fluctuation component of cell c at frequency point f at time t (referred to as the periodic phase), indicating which point of the period cell c is currently in.

[0080] The periodic correction function outputs the periodic correction amount for the linear prediction value of cell c.

[0081] In this step, first-order extrapolation can quickly react to sudden trends (such as a neighboring cell suddenly increasing its transmission power), and period compensation can correct for regular fluctuations caused by TDD cycles and service patterns. Combined, the predicted value is closer to the actual future interference situation, and the final I is obtained. pred,c The formula for calculating (f,t+τ) is as follows: .

[0082] Among them, I pred,c (f,t+τ) represents the final predicted value of the interference power spectral density of cell c at frequency point f at future time (t+τ), which can also be called the final predicted value of interference power per unit bandwidth. I hist,c (f,t) represents the interference power spectral density measured in cell c at time t and frequency f, reflecting the current interference level; ΔI c(f)·τ represents the predicted value of the change in the interference power spectral density of cell c in the future time τ (linear trend prediction). C period,c (f,τ): The predicted value of the change in interference caused by periodic fluctuations at frequency point f in cell c at future time (t+τ) (periodic fluctuation correction).

[0083] τ: Prediction time offset (e.g., 0.5ms, 1ms), generally equal to the scheduling period.

[0084] Based on the final predicted values ​​of all interference power spectral densities within the target frequency band in the future scheduling window for cell c, the predicted interference matrix is ​​obtained. : .

[0085] Among them, I pred,c This represents the set of final predicted interference power spectral density values ​​for each discrete frequency point in the target frequency band [f1,f2] at each scheduling time within the future scheduling window of cell c, with each discrete frequency point corresponding to a resource block; the scheduling window is a set of future discrete times for which interference prediction needs to be performed, typically covering one or more scheduling cycles.

[0086] The output of this step includes: average interference power spectral density I c (t), disturbance gradient G c (t) (rate of change), predicted short-time interference power spectral density I pred,c (f, t+τ). These outputs can be input into subsequent steps (phase misalignment calculation and joint scheduling) to determine whether advance avoidance is needed and to adjust the phase compensation amount.

[0087] S202. Calculation of phase misalignment angle.

[0088] In densely deployed cell environments, neighboring cell signals often use the same frequency resources (co-frequency deployment). Therefore, interference signals from neighboring cells manifest not only in power but also in phase. If two cells transmit signals with similar phases (signal phase difference close to 0°) at the same frequency and time slot, they will coherently superimpose at the receiver, significantly increasing the interference intensity. Conversely, if a phase offset is artificially introduced at the physical layer, the superposition of interference signals can be partially canceled or incoherent, reducing the effective interference power. Therefore, the goal of this step is to calculate the optimal amount of phase offset to be introduced based on the measured phase information of the interference source (i.e., the interfering neighboring cell of the serving cell). That is, to calculate a phase offset angle θopt so that when the neighboring cell interference signal and the serving cell signal meet in time-frequency resources, their phases are no longer perfectly aligned, thereby reducing coherent interference. This phase offset angle θopt will be used for subsequent physical layer transmit phase adjustment (e.g., adding a phase rotation factor to the precoding matrix or reference signal).

[0089] The data required for this step includes: h cu (t): The complex channel coefficient from the serving cell to the target UE at time t. This coefficient is a complex number whose amplitude reflects the attenuation or gain of the signal amplitude by the channel, and whose phase characterizes the phase rotation introduced by the channel to the signal carrier. The UE obtains h by measuring the demodulation reference signal (DM-RS). cu (t) is reported to the serving cell gNB (base station). t represents the current time.

[0090] h ic (t): The complex channel coefficients of the target UE accessed from interfering neighbor cell i to serving cell c at time t, representing the amplitude characteristics (attenuation or gain) and phase rotation characteristics of the signal from the interfering neighbor cell at the target UE receiver. It can be obtained through channel estimation based on the reference signal of the interfering neighbor cell received on the idle resource block of the serving cell, such as CSI-RS (Channel State Information Reference Signal).

[0091] c (t): The transmit phase of serving cell c at time t, which is the reference phase set by the gNB (base station) baseband modulator. This is an internal system parameter that can be directly obtained during baseband generation.

[0092] i (t): The transmission phase of the interfering neighboring cell i at time t.

[0093] w i Interference weighting factor: measures the degree of interference contribution of the interfering neighbor cell i to the target UE accessed by the serving cell.

[0094] Interference weighting factor w i The calculation formula is: .

[0095] in, The downlink interference power generated by neighboring cell i on the time-frequency resource block allocated to the target UE; The sum of downlink interference power generated by all interfering neighboring cells of the serving cell on the time-frequency resource blocks allocated to the target UE.

[0096] For interfering neighbor cell i, the phase difference relative to serving cell c at time t is: .

[0097] If Δ i (t)≈0° or 360° indicates that the signals from the two cells are coherently superimposed, posing the highest risk of interference; if Δ i If (t)≈90° or 270°, the superposition effect of the signals from the two cells tends to be incoherent, and the interference is low.

[0098] By considering all interference sources (i.e., all interfering neighboring cells of the serving cell), a phase adjustment that maximizes overall interference suppression is calculated, yielding the optimal phase misalignment angle θopt for the serving cell: .

[0099] in, : This indicates the value of the independent variable (candidate phase rotation angle θ) when the objective function for enabling interference suppression reaches its minimum value; θ: Candidate phase rotation angle, and θ∈[0,2π). Specifically, 0° to 360° can be divided into multiple steps (e.g., each step is divided into 5° or 10°) to obtain multiple angles as candidate phase rotation angles. : Iterate through and sum all interfering neighboring cells of the serving cell; w k Interference weighting factor: measures the degree of interference contribution of interfering neighbor cell i to the target UE accessed by the serving cell; | | 2 The square of the modulus of a complex number is equal to the square of the real part plus the square of the imaginary part. h cu (t): The complex channel coefficient from serving cell c to target UE at time t, which is a complex number; h kc (t): The complex channel coefficient of the target UE accessing the interfering neighbor cell k to the serving cell c at time t, which is a complex number; e j( ) : Complex exponential function, representing a complex number with a unit amplitude, whose phase is the angle within the parentheses; Δ k (t): The transmission phase difference between the interfering neighbor cell k and the serving cell c at time t.

[0100] This step requires selecting the optimal phase rotation angle θopt from all candidate phase rotation angles that minimizes the superposition power of the serving cell signal and neighboring cell interference signals. This optimization process involves finding an additional phase twist angle to allow the interference components and the useful signal to cancel each other out as much as possible at the receiver. The final output θopt is the optimal phase misalignment angle (in degrees). θopt is a common phase rotation angle at the serving cell level, applied to the serving cell's transmitted signal. In subsequent steps, θopt will be directly written into the precoding matrix or modulation symbol generation process to adjust the physical layer transmit phase.

[0101] Introducing the optimal phase misalignment angle θopt in the serving cell upgrades interference control from the power dimension to the phase dimension. Traditional systems often avoid resources at the scheduling or power control level, while this step directly performs fine-tuning at the physical layer, fundamentally reducing coherent interference. The optimal phase misalignment angle θopt obtained in this step can be combined with the short-term interference prediction in the previous step to adjust the phase in advance before the interference peak, rather than passively remedying it after the interference occurs.

[0102] S203. Dynamic avoidance of time and frequency resources and phase-linked scheduling.

[0103] While the phase misalignment step can effectively reduce interference at the physical layer, the extent of phase optimization is limited: if the power of the interfering signal is much greater than that of the useful signal, even if the phase is adjusted to the optimal level, the interference may only be reduced to a certain extent, rather than completely eliminated. Furthermore, the optimization effect of phase misalignment changes with rapid channel fading and user movement, posing a certain risk of failure.

[0104] Therefore, dynamic time-frequency resource avoidance is needed as a safety measure: when the predicted interference intensity on a resource block exceeds a threshold, and phase optimization is insufficient to guarantee SINR compliance, scheduling is adjusted in advance to avoid the interfered resource. Crucially, this avoidance must be linked to phase shifting: when interference intensity is moderate, phase shifting is prioritized to reduce interference and preserve more resources (saving spectrum). When interference intensity is excessively high, dynamic time-frequency resource avoidance is combined to provide double protection for link quality.

[0105] Therefore, it is necessary to calculate the predicted interference and residual interference after phase misalignment for each candidate time-frequency resource block in real time to determine whether the resource block should be allocated to the target UE, maximizing spectrum utilization while ensuring that the SINR of critical links meets the target. A candidate time-frequency resource block refers to a time-frequency resource block that the scheduler is evaluating and waiting to allocate to the target UE during the current scheduling cycle. Its availability indicator can be calculated based on a combination of phase optimization and interference prediction.

[0106] The parameters required for this step are: I pred (f,t+τ): The predicted value of the interference power spectral density of the serving cell at a time-frequency resource block of frequency f at a future time (t+τ), which is derived from step S201; θopt: The optimal phase misalignment angle of the serving cell, derived from step S202; SINR req The minimum SINR value required for the corresponding service is determined by the scheduling policy or service QoS requirements (e.g., eMBB requires ≥10 dB, URLLC requires ≥15 dB). P signal (f,t+τ): Serving cell useful signal power, representing the useful signal power received by the target UE from the serving cell at time (t+τ) and frequency f in the time-frequency resource block; G phase (f,t+τ): Phase optimization suppression factor, which represents the proportion of interference power reduction at time (t+τ) and frequency point f after the optimal phase misalignment angle θopt is introduced in the serving cell (the value ranges from 0 to 1, where 0 indicates that phase optimization has failed to reduce any interference power and 1 indicates that phase optimization has completely eliminated all predicted interference).

[0107] Phase optimization suppression factor G phase The formula for calculating (f,t+τ) is as follows: .

[0108] Among them, P interf,orig(f,t+τ): Original predicted interference power, representing the total predicted interference power that the serving cell will experience at time (t+τ) and frequency f before taking any interference suppression measures. This is the original interference risk level before base station scheduling, which can be obtained from the I predicted in the previous step. pred,c (f,t+τ) is calculated by multiplying the bandwidth of the time-frequency resource block.

[0109] Original predicted interference power P interf,orig The formula for calculating (f,t+τ) is: .

[0110] Among them, I pred,c (f,t+τ): The predicted interference power spectral density of the serving cell on the time-frequency resource block at frequency f at a future time (t+τ); B RB : The bandwidth of a time-frequency resource block, for example, the width of an RB in NR can be 180 kHz.

[0111] P interf,after-phase (f,t+τ): Residual interference power after phase misalignment is introduced into the serving cell. This represents the predicted residual interference power generated by the summation of all interference signals transmitted at time-frequency resource block (t+τ) and frequency f at time (t+τ) after phase optimization by introducing the optimal phase misalignment angle θopt into the serving cell, upon reaching the target UE. Since phase misalignment alters the relative phase between the interference waveform and the useful signal, causing some interference to cancel each other out, this value is typically less than P. interf,orig (f,t+τ).

[0112] After performing phase rotation on the serving cell transmitted signal using the optimal phase misalignment angle θopt, the total power of the serving cell signal and the neighboring cell interference signal superimposed at the target UE receiver in the serving cell is calculated.

[0113] Residual interference power P interf,after-phase The formula for calculating (f,t+τ) is: .

[0114] Among them, A k (f,t+τ): The signal amplitude (in square root of watts) of the k-th interference source on the time-frequency resource block at time (t+τ) and frequency f. k : The original phase of the k-th interference source.

[0115] For G phase In terms of P interf,orig This is a baseline value used to measure how much interference is reduced by phase optimization; Pinterf,after-phase This is the prediction result after phase optimization. G is calculated from both. phase This ratio is a key input parameter for the subsequent dynamic avoidance strategy because it reflects the true effect of phase optimization.

[0116] Next, the residual interference after phase optimization is calculated: .

[0117] in, Residual interference power spectral density represents the predicted value of the remaining interference power spectral density of the serving cell at time (t+τ) and frequency f in the time-frequency resource block after phase optimization. : Predicted interference power spectral density, representing the predicted value of the interference power spectral density of the serving cell at time (t+τ) and frequency f in the time-frequency resource block; Phase optimization suppression factor: This represents the percentage reduction in interference power at time (t+τ) and frequency f after the optimal phase misalignment angle θopt is introduced into the serving cell.

[0118] The significance of calculating the residual interference after phase optimization is that, from the original predicted interference value, the portion that can be canceled out by phase misalignment is subtracted to obtain the residual interference.

[0119] Then, calculate the expected SINR after phase optimization: .

[0120] in, The expected SINR value of the serving cell after phase optimization represents the expected SINR value of the serving cell at time (t+τ) and frequency f in the time-frequency resource block after phase optimization. Serving cell useful signal power, which represents the useful signal power received by the target UE from the serving cell at time (t+τ) and frequency f in the time-frequency resource block; The residual interference power spectral density of the serving cell represents the remaining interference power spectral density of the serving cell at time (t+τ) and frequency f in the time-frequency resource block after phase optimization. Thermal noise power spectral density, a constant; : Bandwidth of the time-frequency resource block.

[0121] If SINR phase (f,t)≥SINR reqThis indicates that phase misalignment alone is sufficient to meet link quality requirements, and avoidance is not necessary.

[0122] Define the avoidance flag function: .

[0123] When Avoid=1, the time-frequency resource block is marked as "unallocated to the target UE (interference sensitive)" in the scheduling table, or it is directly switched to the backup resource group. When Avoid=0, the time-frequency resource block optimized by the serving cell phase can be allocated to the target UE normally, and the base station scheduler should give priority to this type of resource block.

[0124] This step outputs a dynamic scheduling table containing the availability flags for each time-frequency resource block in the current scheduling period (calculated based on a combination of phase misalignment and interference prediction). This is a table similar to a "resource allocation list," used to tell the base station scheduler which time-frequency resource blocks are safe to use and which should be avoided within the current scheduling period (e.g., 1 ms or 10 ms).

[0125] A specific example is provided below, as shown in Table 1: Table 1

[0126] In Table 1, availability flags: 1 indicates that it is allowed to use, and 0 indicates that it is prohibited to use.

[0127] The dynamic scheduling table is called in real time by the base station scheduler to ensure that high-interference resource blocks are not selected when transmitting signals.

[0128] In practical applications, a threshold Gth can be set for the interference gradient Gc(t).

[0129] When Gc(t)≤Gth, it indicates that the interference is stable or changes slowly, and the base station scheduler performs scheduling according to the above scheme (using the Avoid flag to select available resource blocks).

[0130] When Gc(t) > Gth, it indicates a rapid increase in interference. The base station's scheduler can select from all video resource blocks with Avoid=0 according to the predicted interference power P of the serving cell. interf,orig Or predict the interference power spectral density I pred The resource blocks with lower interference are sorted and then allocated to the target UE.

[0131] This step also outputs a residual interference distribution map: This is a two-dimensional graph where the horizontal axis represents time and the vertical axis represents interference frequency. The color intensity indicates the strength of the interference (usually expressed in dBm). It shows how much residual interference remains in resource blocks at different times and frequencies after phase optimization. Operations personnel can use it to visually see the interference distribution trend, such as which frequency bands the interference is concentrated in and during which time periods it is most severe. This is used for subsequent long-term optimization, such as cell transmit power adjustment and spectrum reallocation.

[0132] The dynamic scheduling table provides "operational instructions" to the base station, telling the base station scheduler which time-frequency resource blocks are available and which are not. The residual interference distribution map is a "situation map" provided to engineers, allowing them to understand the spatial-temporal distribution of interference.

[0133] This step is not simply about adjusting the phase and then avoiding interference; rather, it dynamically changes the avoidance strategy based on the effects of phase optimization to maximize spectrum utilization. The avoidance decision is based not only on power thresholds but also on residual interference after phase misalignment, which is more precise than traditional static interference thresholds. Phase optimization resolves most interference, and combined with avoidance as a fallback, it ensures high reliability and high spectrum efficiency even in ultra-dense networks.

[0134] Steps S201 to S203 form a tightly linked closed-loop chain: Step S201 obtains the interference amplitude and phase information of each time-frequency resource block through real-time measurement and short-term prediction, providing "raw intelligence" for subsequent decision-making; Step S202 calculates the controllable optimal phase misalignment based on these predicted data, reducing the superimposed interference of co-frequency signals from neighboring cells in advance, essentially reducing the "noise environment" to a cleaner level; Step S203 utilizes the residual interference distribution after phase optimization to dynamically select the time-frequency resource with the lowest interference for scheduling, and links with the phase control strategy in real time to ensure that transmission and scheduling work collaboratively in the same optimization direction. These three links form a "measurement-control-application" closed loop, reducing physical layer interference and improving resource utilization at the scheduling layer.

[0135] The interference suppression method provided in this invention obtains the interference amplitude and phase information of each time-frequency resource block through real-time interference measurement and short-term interference prediction, providing raw information for subsequent decision-making. Based on the predicted data, it calculates the controllable optimal phase misalignment amount to reduce the superimposed interference of co-frequency signals from neighboring cells in advance. Utilizing the phase-optimized residual interference distribution, it dynamically selects the time-frequency resource block with the lowest interference for scheduling, and links it in real-time with the phase optimization strategy to ensure that transmission and scheduling work collaboratively in the same optimization direction. These three links form a closed loop of "measurement-control-application," which reduces physical layer interference and improves the resource utilization rate of the scheduling layer.

[0136] Figure 3This is a schematic diagram of the interference suppression device provided in an embodiment of the present invention. Figure 3 As shown, the device includes: a serving cell phase optimization module 301, a residual interference prediction module 302, a expected signal quality calculation module 303, and a resource scheduling and avoidance module 304.

[0137] The serving cell phase optimization module 301 is configured to introduce an optimal phase misalignment angle in the serving cell for phase optimization; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell. The residual interference prediction module 302 is configured to obtain the predicted value of the residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization. The expected signal quality calculation module 303 is configured to calculate the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization based on the predicted value of the residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block. The resource scheduling and avoidance module 304 is configured to, for each candidate time-frequency resource block, execute a candidate time-frequency resource block avoidance strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold; and for each candidate time-frequency resource block, execute a candidate time-frequency resource block allocation strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to the preset quality threshold, wherein the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein the target user is a user accessing the serving cell.

[0138] In one specific embodiment, the device further includes: an optimal phase misalignment angle acquisition module.

[0139] The optimal phase misalignment angle acquisition module is configured to construct an interference suppression objective function based on the complex channel coefficient from the serving cell to the target user, the complex channel coefficient from each interfering neighbor cell of the serving cell to the target user, the transmit phase difference between the serving cell and each interfering neighbor cell, and multiple candidate phase rotation angles; with minimizing the interference suppression objective function as the optimization objective, the optimal phase rotation angle is obtained from the multiple candidate phase rotation angles as the optimal phase misalignment angle.

[0140] In one specific implementation, the interference suppression objective function is: ; in, The objective function is to suppress interference. The candidate phase rotation angle; This is the interference weighting factor, used to measure the degree of interference contribution of interfering neighbor cell k to the target users accessed by the serving cell, where K is the number of interfering neighbor cells of the serving cell. The complex channel coefficients from the serving cell to the target user at time t; The complex channel coefficients from the interfering neighboring cell k to the target user at time t; The transmit phase difference between the serving cell and the interfering neighbor cell k at time t; t is the current time.

[0141] In one specific embodiment, the residual interference prediction module 302 includes an interference power reduction ratio calculation unit and a residual interference prediction unit.

[0142] The interference power reduction ratio calculation unit is set to calculate the interference power reduction ratio of the serving cell at a future preset time based on the predicted interference power value of each candidate time-frequency resource block before phase optimization and the residual interference power of each candidate time-frequency resource block after phase optimization. The residual interference prediction unit is configured to calculate the residual interference power spectral density prediction value of each candidate time-frequency resource block of the serving cell at a future preset time based on the interference power reduction ratio and the predicted interference power spectral density value of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization.

[0143] In one specific implementation, the predicted interference power value for each candidate time-frequency resource block of the serving cell at a future preset time before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. To predict the time offset; The bandwidth of the candidate time-frequency resource block.

[0144] In one specific implementation, the residual interference power at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted residual interference power is generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them. To interfere with the interference signal of neighboring cell k at time k The signal amplitude on the candidate time-frequency resource block with frequency f; t is the current time. The time offset is used for prediction; K is the number of interfering neighboring cells of the serving cell; To interfere with the original phase of neighboring cell k; This is the optimal phase misalignment angle.

[0145] In one specific implementation, the percentage reduction in interference power at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The percentage reduction in interference power on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted residual interference power generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them; t is the current time. This is for predicting the time offset.

[0146] In one specific implementation, the predicted residual interference power spectral density value for each candidate time-frequency resource block of the serving cell after phase optimization is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0147] In one specific embodiment, the device further includes an interference power spectral density prediction module. The interference power spectral density prediction module includes: a first interference prediction unit and a second interference prediction unit.

[0148] The first interference prediction unit is configured to calculate the initial predicted value of the interference power spectral density at the current time on each candidate time-frequency resource block before phase optimization of the serving cell and the predicted value of the total change of interference power spectral density at the future preset time on each candidate time-frequency resource block in the future preset time period. The future preset time is the end point of the future preset time period. The second interference prediction unit is set to calculate the final predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block before phase optimization of the serving cell, based on the initial predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block before phase optimization and the predicted value of the interference change caused by periodic fluctuations at a future preset time on each candidate time-frequency resource block.

[0149] In one specific implementation, the initial predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; The interference power spectral density measured on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; t is the current time. To predict the time offset; The rate of change of interference power spectral density of candidate time-frequency resource blocks with frequency f in the serving cell before phase optimization; To serve the future time period on the candidate time-frequency resource block of frequency f before phase optimization in the service cell The predicted value of the total change in the interference power spectral density.

[0150] In one specific implementation, the final predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

[0151] In one specific implementation, the predicted value of the disturbance change is calculated using the following formula: ; in, To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on a candidate time-frequency resource block with frequency f; The peak amplitude of the periodic fluctuation component on the candidate time-frequency resource block at frequency f before phase optimization of the serving cell; The fluctuation period length of the periodic fluctuation component in the serving cell before phase optimization; To represent the phase of the periodic fluctuation component on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; where t is the current time. This is for predicting the time offset.

[0152] In one specific implementation, the expected signal quality is calculated using the following formula: ; in, After phase optimization, the service cell is served at the time... The expected SINR value on the candidate time-frequency resource block with frequency f; It is a moment The useful signal power received by the target user from the serving cell on a candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; This represents the thermal noise power spectral density. The bandwidth of the candidate time-frequency resource block.

[0153] The interference suppression device provided in this invention constructs a lightweight closed-loop mechanism from interference prediction and phase optimization to scheduling decision-making. First, an optimal phase misalignment angle is introduced for the serving cell to optimize the transmit phase. This angle is obtained by locally solving the interference suppression objective function, eliminating the need for inter-cell cooperative signaling and thus completing phase adjustment in milliseconds, enabling rapid response to dynamic interference. Based on this, short-time interference prediction techniques (including linear trend extrapolation and periodic fluctuation compensation) are used to obtain the predicted residual interference power spectral density of each candidate time-frequency resource block at future times. Then, the expected signal quality is calculated by combining the resource block bandwidth and useful signal power. Finally, based on the comparison between the expected signal quality and a preset threshold, resource avoidance or allocation is dynamically executed, and the phase-optimized transmit signal is used during allocation. The entire interference suppression process replaces the high-overhead cooperative signaling in traditional schemes with low-complexity calculations (such as linear extrapolation, proportional operations, and sine compensation), significantly reducing the signaling burden. At the same time, through phase-level fine adjustment and adaptive selection of time and frequency resources, it effectively suppresses coherent interference and improves spectrum utilization, thereby achieving rapid response to dynamic interference, low signaling overhead, and phase-level interference suppression, making it suitable for complex interference environments such as ultra-dense networks.

[0154] Based on the same technical concept, embodiments of the present invention also provide a computer device, such as... Figure 4 As shown, the computer device includes a memory 401 and a processor 402. The memory 401 stores a computer program. When the processor 402 runs the computer program stored in the memory 401, the processor 402 executes the aforementioned interference suppression method.

[0155] Based on the same technical concept, embodiments of the present invention also provide a computer-readable storage medium storing a computer program thereon, wherein when the computer program is executed by a processor, the processor performs the aforementioned interference suppression method.

[0156] In summary, the interference suppression method, apparatus, computer device, and storage medium provided in this embodiment of the invention can find the optimal phase misalignment angle based on the interference prediction value and the phase distribution of the interference source, allowing multiple interference components to cancel each other out at the receiving end, and updating in real time. The interference prediction results are used for phase optimization and dynamic scheduling, respectively. Phase optimization changes the actual interference environment, and scheduling uses the latest prediction for resource allocation to achieve real-time adaptation. By utilizing the residual interference distribution after phase optimization, the time-frequency resources with the lowest interference are dynamically selected for scheduling, and are linked in real time with the phase control strategy to ensure that transmission and scheduling work together in the same optimization direction. This enables rapid response to dynamic interference, low signaling overhead, and supports phase-level interference suppression.

[0157] It will be understood by those skilled in the art that all or some of the steps, systems, or apparatuses disclosed above, and their functional modules / units, can be implemented as software, firmware, hardware, or suitable combinations thereof. In hardware implementations, the division between functional modules / units mentioned in the above description does not necessarily correspond to the division of physical components; for example, a physical component may have multiple functions, or a function or step may be performed collaboratively by several physical components. Some or all physical components may be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit (ASIC). Such software may be distributed on a computer-readable medium, which may include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media include, but are not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and can be accessed by a computer. Furthermore, it is well known to those skilled in the art that communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0158] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, and not to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those skilled in the art should understand that modifications can still be made to the technical solutions described in the foregoing embodiments, or equivalent substitutions can be made to some or all of the technical features; and these modifications or substitutions do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present invention.

Claims

1. An interference suppression method characterized by, include: Phase optimization is performed by introducing an optimal phase misalignment angle in the serving cell; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell. Obtain the predicted residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization; Based on the predicted residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block, the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization is calculated. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold, a candidate time-frequency resource block avoidance strategy is executed for the target user. For each candidate time-frequency resource block, in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to a preset quality threshold, a candidate time-frequency resource block allocation strategy is executed for the target user, and the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein, the target user is a user accessing the serving cell.

2. The interference suppression method according to claim 1, characterized in that, The method for obtaining the optimal phase misalignment angle includes: Based on the complex channel coefficients from the serving cell to the target user, the complex channel coefficients from each interfering neighbor cell of the serving cell to the target user, the transmit phase difference between the serving cell and each interfering neighbor cell, and multiple candidate phase rotation angles, an interference suppression objective function is constructed. With minimizing the interference suppression objective function as the optimization objective, the optimal phase rotation angle is obtained from the multiple candidate phase rotation angles as the best phase misalignment angle.

3. The interference suppression method according to claim 2, characterized in that, The objective function for interference suppression is: ； in, The objective function is to suppress interference. The candidate phase rotation angle; This is the interference weighting factor, used to measure the degree of interference contribution of interfering neighbor cell k to the target users accessed by the serving cell, where K is the number of interfering neighbor cells of the serving cell. The complex channel coefficients from the serving cell to the target user at time t; The complex channel coefficients from the interfering neighboring cell k to the target user at time t; The transmit phase difference between the serving cell and the interfering neighbor cell k at time t; t is the current time.

4. The interference suppression method according to claim 1, characterized in that, The acquisition of the predicted residual interference power spectral density for each candidate time-frequency resource block of the serving cell after phase optimization includes: Based on the predicted interference power of each candidate time-frequency resource block of the serving cell at a future preset time before phase optimization, and the residual interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization, the percentage reduction in interference power of each candidate time-frequency resource block of the serving cell at a future preset time after phase optimization is calculated. Based on the interference power reduction ratio and the predicted interference power spectral density of each candidate time-frequency resource block of the serving cell before phase optimization, the predicted residual interference power spectral density of each candidate time-frequency resource block of the serving cell after phase optimization is calculated.

5. The interference suppression method according to claim 4, characterized in that, The predicted interference power at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ； in, To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. To predict the time offset; The bandwidth of the candidate time-frequency resource block; After phase optimization, the residual interference power of each candidate time-frequency resource block in the serving cell at a future preset time is calculated using the following formula: ； in, After phase optimization, the service cell is served at the time... The predicted residual interference power is generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them. To interfere with the interference signal of neighboring cell k at time k The signal amplitude on the candidate time-frequency resource block with frequency f; t is the current time. The time offset is used for prediction; K is the number of interfering neighboring cells of the serving cell; To interfere with the original phase of neighboring cell k; This is the optimal phase misalignment angle.

6. The interference suppression method according to claim 4 or 5, characterized in that, The percentage reduction in interference power at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization is calculated using the following formula: ； in, After phase optimization, the service cell is served at the time... The percentage reduction in interference power on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted interference power on the candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted residual interference power generated by transmitting interference signals from all interfering neighboring cells on a candidate time-frequency resource block with frequency f to the target user and superimposing them; t is the current time. To predict the time offset; The predicted residual interference power spectral density of each candidate time-frequency resource block in the serving cell after phase optimization is calculated using the following formula: ； in, After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time The predicted interference power spectral density on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

7. The interference suppression method according to claim 5, characterized in that, The method for obtaining the predicted interference power spectral density includes: Based on the interference power spectral density of each candidate time-frequency resource block at the current moment before phase optimization and the predicted value of the total change in interference power spectral density of each candidate time-frequency resource block over a future preset time period, the initial predicted value of interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization is calculated; wherein, the future preset time is the end point of the future preset time period. Based on the initial predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization and the predicted value of the interference change caused by periodic fluctuations at a future preset time for each candidate time-frequency resource block, the final predicted value of the interference power spectral density of each candidate time-frequency resource block at a future preset time before phase optimization is calculated.

8. The interference suppression method according to claim 7, characterized in that, The initial predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ； in, To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; The interference power spectral density measured on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; t is the current time. To predict the time offset; The rate of change of interference power spectral density of candidate time-frequency resource blocks with frequency f in the serving cell before phase optimization; To serve the future time period on the candidate time-frequency resource block of frequency f before phase optimization in the service cell The predicted value of the total change in the interference power spectral density; The final predicted value of the interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell before phase optimization is calculated using the following formula: ； in, To serve the community before phase optimization, at time The predicted value of the interference power spectral density on the candidate time-frequency resource block with frequency f; To serve the community before phase optimization, at time Initial predicted values ​​of interference power spectral density on candidate time-frequency resource blocks with frequency f; To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on the candidate time-frequency resource block with frequency f; t is the current time. This is for predicting the time offset.

9. The interference suppression method according to claim 8, characterized in that, The predicted value of the disturbance change is calculated using the following formula: ； in, To serve the community before phase optimization, at time The predicted value of the change in interference caused by periodic fluctuations on a candidate time-frequency resource block with frequency f; The peak amplitude of the periodic fluctuation component on the candidate time-frequency resource block at frequency f before phase optimization of the serving cell; The fluctuation period length of the periodic fluctuation component in the serving cell before phase optimization; To represent the phase of the periodic fluctuation component on the candidate time-frequency resource block at time t and frequency f before phase optimization of the serving cell; where t is the current time. This is for predicting the time offset.

10. The interference suppression method according to claim 1, characterized in that, The expected signal quality is calculated using the following formula: ； in, After phase optimization, the service cell is served at the time... The expected SINR value on the candidate time-frequency resource block with frequency f; It is a moment The useful signal power received by the target user from the serving cell on a candidate time-frequency resource block with frequency f; After phase optimization, the service cell is served at the time... The predicted value of the remaining interference power spectral density on the candidate time-frequency resource block with frequency f; This represents the thermal noise power spectral density. The bandwidth of the candidate time-frequency resource block.

11. An interference suppression device, characterized in that, include: The serving cell phase optimization module is configured to introduce an optimal phase misalignment angle in the serving cell for phase optimization; wherein, the optimal phase misalignment angle is the phase rotation angle that can maximize the suppression of interference signals from all interfering neighboring cells of the serving cell. The residual interference prediction module is configured to obtain the predicted value of the residual interference power spectral density at a future preset time on each candidate time-frequency resource block of the serving cell after phase optimization. The expected signal quality calculation module is configured to calculate the expected signal quality of the serving cell at a future preset time on each candidate time-frequency resource block after phase optimization, based on the predicted value of the residual interference power spectral density, the bandwidth of each candidate time-frequency resource block, and the useful signal power of the serving cell corresponding to each candidate time-frequency resource block. The resource scheduling and avoidance module is configured to, for each candidate time-frequency resource block, execute a candidate time-frequency resource block avoidance strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being less than a preset quality threshold; and for each candidate time-frequency resource block, execute a candidate time-frequency resource block allocation strategy for the target user in response to the expected signal quality on the candidate time-frequency resource block being greater than or equal to the preset quality threshold, wherein the serving cell uses a phase-optimized transmission signal on the candidate time-frequency resource block; wherein the target user is a user accessing the serving cell.

12. A computer device, characterized in that, The device includes a memory and a processor, wherein the memory stores a computer program, and when the processor runs the computer program stored in the memory, the processor performs the interference suppression method according to any one of claims 1 to 10.

13. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by a processor, the processor performs the interference suppression method according to any one of claims 1 to 10.

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