Interference suppression method and device, intelligent reflector system and storage medium

Abstract

The invention provides an interference suppression method and device, an intelligent reflecting surface system and a storage medium, and relates to the technical field of sensing systems and low-altitude economy. Obtaining target sensing information by sensing the positions of the plurality of base stations and the plurality of user equipment, the target sensing information comprising the position information of the plurality of base stations and the plurality of user equipment; determining a reflection weight vector according to the target sensing information, wherein the reflection weight vector is obtained under the condition that the signal interference of the sensing system is minimized according to the target sensing information and the multipath phase constraint is satisfied; and deploying the reflection weight vector to the plurality of reflection units. According to the method, the signal interference of the multi-base-station and multi-user-equipment communication sensing system can be reduced, the communication quality and the sensing precision of the multi-user equipment are ensured, and meanwhile, the resource overhead of the communication sensing system is not increased.

Description

Technical Field

[0001] The present invention relates to the technical fields of communication-sensing integrated systems and low-altitude economy, and particularly to an interference suppression method, apparatus, intelligent reflecting surface system, and storage medium. Background Art

[0002] In recent years, the integrated communication and sensing (ISAC) technology has attracted much attention due to its high-efficient spectrum, power, and hardware reuse capabilities. The sixth-generation (6G) mobile communication network will integrate communication and sensing functions, and can simultaneously support user communication and sense dynamic targets around the base station. However, scenarios with interference in the environment will further pose challenges to the communication-sensing integrated system, because in multi-user device (MU) and multi-base station (MB) scenarios, communication and sensing performance will be limited by interference.

[0003] Collaborative MB communication-sensing integrated systems can achieve interference suppression. However, due to the spatial dispersion of multiple base stations, achieving clock synchronization of MBs at the signal level will result in increased resource overhead of the multi-base station multi-user device communication-sensing system and excessive resource overhead. In addition, directly performing time-division multiplexing and frequency-division multiplexing of resources will reduce the communication-sensing efficiency of the system. Summary of the Invention

[0004] The present invention provides an interference suppression method, apparatus, intelligent reflecting surface system, and storage medium to solve the defects in the prior art that the collaborative multi-base station multi-user device communication-sensing system either has excessive resource overhead or low communication-sensing efficiency, so as to reduce signal interference in the multi-base station multi-user device communication-sensing system, ensure the communication quality and sensing accuracy of multi-user devices, and at the same time not increase the resource overhead of the multi-base station multi-user device communication-sensing system.

[0005] The present invention provides an interference suppression method applied to an intelligent reflecting surface system. The intelligent reflecting surface system is arranged in a communication-sensing system. The communication-sensing system includes multiple base stations and multiple user devices. The multiple base stations and the multiple user devices communicate and sense non-cooperatively. The intelligent reflecting surface system includes multiple reflecting units, and the method includes the following steps: Sense the positions of the multiple base stations and the multiple user devices to obtain target sensing information, where the target sensing information includes the position information of the multiple base stations and the multiple user devices; Determine a reflection weight vector according to the target sensing information. The reflection weight vector is obtained under the condition of minimizing the signal interference of the communication-sensing system according to the target sensing information and satisfying the multipath phase constraint. The reflection weight vector is used to represent the setting parameters corresponding to the multiple reflecting units, and the multipath phase constraint is used to represent the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user devices being affected by the signal phases on multiple propagation paths; Deploy the reflection weight vector to the multiple reflection units.

[0006] According to an interference suppression method provided by the present invention, determining the reflection weight vector according to the target perception information includes: Pair the position information of the multiple base stations and the multiple user equipments in the target perception information to obtain at least one base station-user equipment pair, and the distance between the base station and the user equipment in each base station-user equipment pair meets a preset distance requirement; According to the position information of each base station-user equipment pair in the at least one base station-user equipment pair, determine the combined communication signal vector received by the multiple user equipments, the combined perception signal vector received by the multiple base stations, and the uncontrollable multipath phase of the effective communication and sensing signal of the communication and sensing system, where the effective communication and sensing signal is used to characterize the signal transmitted between each pair of base station information, and the uncontrollable multipath phase is used to characterize the phase on the multipath that does not pass through the intelligent reflecting surface system; Obtain the reflection weight vector according to the combined communication signal vector, the combined perception signal vector, and the uncontrollable multipath phase. The reflection weight vector is obtained by minimizing the total power of the received signals in the combined communication signal vector and the combined perception signal vector, and satisfying that the uncontrollable multipath phase is the same as the path adjustment phase of the intelligent reflecting surface system.

[0007] According to an interference suppression method provided by the present invention, determining the combined communication signal vector received by the multiple user equipments, the combined perception signal vector received by the multiple base stations, and the uncontrollable multipath phase of the effective communication and sensing signal of the communication and sensing system according to the position information of each base station-user equipment pair in the at least one base station-user equipment pair includes: Obtain the combined communication signal vector according to the channel matrix from the multiple base stations to the intelligent reflecting surface system and the channel matrix from the intelligent reflecting surface system to the multiple user equipments. The downlink communication signals received by the multiple user equipments are determined according to the position information of the multiple user equipments relative to the intelligent reflecting surface system and the position information of the multiple base stations; Obtain the combined perception signal vector according to the direct vision channel matrix from the multiple base stations to the multiple user equipments and the weight matrix of the target group reflecting surface, where the target group reflecting surface is used to characterize the reflection parameters of the multiple user equipments corresponding to the multiple base stations at different positions; Obtain the uncontrollable multipath phase according to the distance information from the multiple base stations to the multiple user equipments and between the multiple base stations in the target perception information, in combination with the weight matrix of the target group reflecting surface.

[0008] A interference suppression method provided by the present invention, obtaining the reflection weight vector according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multipath phase, includes: An optimization problem expression is obtained according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multipath phase. The optimization problem expression includes an optimization formula and a constraint formula. The optimization formula is used to minimize the total power of the received signal, and the constraint formula is used to maintain the signal amplitude and align the controllable path phase and the uncontrollable path phase; The optimization problem expression is solved by constructing an objective function to obtain the reflection weight vector. The objective function is used to represent the Lagrangian function.

[0009] A interference suppression method provided by the present invention, the multiple base stations use signals of the same frequency band and provide communication services and sensing services for the multiple user equipments in a space division multiplexing manner.

[0010] A interference suppression method provided by the present invention, the intelligent reflecting surface system is deployed at the middle position of the multiple base stations. The multiple reflecting units of the intelligent reflecting surface system have independent weight control capabilities, and the reflection mode of the intelligent reflecting surface system supports serving the multiple user equipments and the multiple base stations in parallel.

[0011] The present invention also provides an interference suppression device, which is applied to an intelligent reflecting surface system. The intelligent reflecting surface system is arranged in a communication and sensing system. The communication and sensing system includes multiple base stations and multiple user equipments. The multiple base stations and the multiple user equipments communicate and sense non-cooperatively. The intelligent reflecting surface system includes multiple reflecting units, and includes the following modules: A position sensing module, configured to sense the positions of the multiple base stations and the multiple user equipments to obtain target sensing information, where the target sensing information includes the position information of the multiple base stations and the multiple user equipments; A weight determination module, configured to determine a reflection weight vector according to the target sensing information. The reflection weight vector is obtained while minimizing the signal interference of the communication and sensing system and satisfying the multipath phase constraint. The reflection weight vector is used to represent the setting parameters corresponding to the multiple reflecting units. The multipath phase constraint is used to represent the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user equipments being affected by the signal phases on multiple propagation paths; A weight deployment module, configured to deploy the reflection weight vector to the multiple reflecting units.

[0012] The present invention also provides an intelligent reflecting surface system, which includes a plurality of reflecting units, a memory, a processor, and a computer program stored on the memory and running on the processor. When the processor executes the computer program, the interference suppression method described in any one of the above is implemented.

[0013] The present invention also provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, the interference suppression method described in any one of the above is implemented.

[0014] The present invention also provides a computer program product, which includes a computer program. When the computer program is executed by a processor, the interference suppression method of the intelligent reflecting surface system described in any one of the above is implemented.

[0015] The interference suppression method, device, intelligent reflecting surface system, and storage medium provided by the present invention obtain target perception information by perceiving the positions of the plurality of base stations and the plurality of user equipments. The target perception information includes the position information of the plurality of base stations and the plurality of user equipments. A reflection weight vector is determined according to the target perception information. The reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint. The reflection weight vector is used to represent the setting parameters corresponding to the plurality of reflecting units. The multipath phase constraint is used to represent the constraint conditions generated by the signal phases received by the plurality of base stations and the plurality of user equipments being affected by the signal phases on multiple propagation paths. The reflection weight vector is deployed to the plurality of reflecting units. This method can reduce the signal interference of the communication and sensing system with multiple base stations and multiple user equipments, ensure the communication quality and sensing accuracy of multiple user equipments, and at the same time does not increase the resource overhead of the communication and sensing system with multiple base stations and multiple user equipments. Description of the Drawings

[0016] In order to more clearly illustrate the technical solutions in the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0017] Figure 1 It is a schematic flowchart of the interference suppression method provided by the present invention.

[0018] Figure 2 It is a schematic flowchart of the method for determining the reflection weight vector provided by the present invention.

[0019] Figure 3 It is a schematic diagram of the base station multi-user - communication and sensing system model provided by the present invention.

[0020] Figure 4 It is a schematic diagram of the LoS communication and sensing channel model from a single base station to multiple users provided by the present invention.

[0021] Figure 5 It is a structural diagram of an integrated communication and sensing architecture assisted by an intelligent reflecting surface system provided by the present invention.

[0022] Figure 6 It is a schematic structural diagram of an interference suppression device provided by the present invention.

[0023] Figure 7 It is a schematic diagram of the physical structure of an intelligent reflecting surface system provided by the present invention. Detailed implementation manners

[0024] To make the objectives, technical solutions, and advantages of the present invention clearer, the technical solutions in the present invention will be clearly and completely described below with reference to the accompanying drawings in the present invention. Obviously, the described embodiments are some, but not all, of the embodiments of the present invention. All other embodiments obtained by those of ordinary skill in the art based on the embodiments in the present invention without creative efforts shall fall within the protection scope of the present invention.

[0025] In recent years, the integrated communication and sensing (ISAC) technology has attracted much attention due to its high-efficiency spectrum, power, and hardware reuse capabilities. The sixth-generation (6G) mobile communication network will integrate communication and sensing functions and be able to support user communication and sense dynamic targets around the base station simultaneously. However, the scenario with interference in the environment will further pose challenges to the communication and sensing system because in the multi-user equipment (MU) and multi-base station (MB) scenarios, the communication and sensing performance will be limited by interference.

[0026] A collaborative MB communication and sensing system can achieve interference suppression. However, due to the spatial dispersion of multiple base stations, achieving clock synchronization of MB at the signal level will cause an increase in the resource overhead of the multi-base station multi-user equipment communication and sensing system and excessive resource overhead. In addition, directly performing time-division multiplexing and frequency-division multiplexing of resources will reduce the communication and sensing efficiency of the system. How to achieve spatial division multiplexing through interference suppression by utilizing the sparsity of the spatial positions of multiple base stations and multiple users (MBMU) is an important challenge.

[0027] In view of this, an embodiment of the present invention provides an interference suppression method. By perceiving the positions of the multiple base stations and the multiple user equipments, target perception information is obtained, and the target perception information includes the position information of the multiple base stations and the multiple user equipments; a reflection weight vector is determined according to the target perception information, and the reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint. The reflection weight vector is used to characterize the set parameters corresponding to the multiple reflection units, and the multipath phase constraint is used to characterize the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user equipments affected by the signal phases on multiple propagation paths; the reflection weight vector is deployed to the multiple reflection units. This method can reduce the signal interference of the communication and sensing system with multiple base stations and multiple user equipments, ensure the communication quality and sensing accuracy of multiple user equipments, and at the same time does not increase the resource overhead of the communication and sensing system with multiple base stations and multiple user equipments. Among them, the communication and sensing system includes a communication system, a sensing system, and a communication and sensing integrated system.

[0028] Next, the technical solutions in the embodiments of the present invention will be described with reference to the accompanying drawings in the embodiments of the present invention.

[0029] Figure 1 It is a schematic flowchart of the interference suppression method provided by the present invention. The interference suppression method can be applied to an intelligent reflecting surface system, and the intelligent reflecting surface system can be various types of intelligent reflecting surface systems with information processing capabilities during implementation. The intelligent reflecting surface system includes multiple reflection units. The interference suppression method of the intelligent reflecting surface system can be applied to the intelligent reflecting surface system, and the intelligent reflecting surface system is arranged in a communication and sensing system. The communication and sensing system includes multiple base stations and multiple user equipments, and the multiple base stations and the multiple user equipments communicate and sense non-cooperatively. As Figure 1 shown, the method may include the following steps 101 to step 103: Step 101: Perceive the positions of the multiple base stations and the multiple user equipments to obtain target perception information, where the target perception information includes the position information of the multiple base stations and the multiple user equipments.

[0030] It should be noted that several base stations cover an area with sensing requirements and no cell division (CF); within the sensing service area, each base station transmits communication waveforms to its corresponding served user equipment (UE), and at the same time, each base station uses the reflected echo to sense its served UE, and each base station serves users in the environment non-cooperatively. There is a deployed Reconfigurable Intelligent Surface (RIS) system in the sensing service area to assist the non-cooperative multi-base station multi-user (MBMU) integrated sensing and communication (ISAC) system transmission.

[0031] Among them, the RIS system can sense the positions of the multiple base stations and the multiple user devices to obtain target sensing information, and the target sensing information includes the position information of the multiple base stations and the multiple user devices. The RIS system improves the communication sensing performance of the multiple base stations and the multiple user devices by regulating the controllable reflection path signals of radio signals and utilizing the multi-path signal characteristics.

[0032] Exemplarily, sensing the positions of the multiple base stations and the multiple user devices may include three steps: (1) Signal transmission and reception: The base station transmits wireless signals, which are reflected by the RIS system during propagation and then reach the user device. At the same time, the base station receives the echo signals from the RIS system and the user device. (2) Signal analysis and processing: The central processing unit analyzes the received signals using advanced signal processing algorithms. These algorithms may include measurements and calculations of parameters such as time of arrival (TOA), time difference of arrival (TDOA), angle of arrival (AoA), received signal strength indication (RSSI), etc. By analyzing these parameters, the path changes of the signals during propagation can be inferred, and thus the relative position relationship between the base station and the user device can be determined. (3) Position calculation and optimization: After obtaining the relative position relationship between the base station and the user device, the central processing unit calculates the exact positions of the base station and the user device using algorithms such as triangulation and multilateration. Further, in order to improve the accuracy and stability of positioning, it may be necessary to optimize and adjust the reflection weight vector of the RIS system to achieve customization and optimization of the signal propagation environment.

[0033] Step 102: Determine the reflection weight vector according to the target sensing information. The reflection weight vector is obtained under the condition of minimizing the signal interference of the integrated sensing and communication system while satisfying the multi-path phase constraint. The reflection weight vector is used to represent the set parameters corresponding to the multiple reflection units, and the multi-path phase constraint is used to represent the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user devices being affected by the signal phases on multiple propagation paths.

[0034] It should be noted that the RIS system can be equipped with a multi-modal sensing module, and the required reflection weight vector can be calculated based on the sensing results of the user and the base station. Among them, the RIS system processor uses an optimization algorithm to adjust the reflection weight vector of the RIS system through the controller, so as to minimize the interference of the communication signal of the target and the interference of the echo sensing signal, while maintaining the performance of sensing and communication.

[0035] The algorithm ensures that the multi-path phase of the effective communication and sensing signal is the same as the phase adjusted by the RIS system path, ensuring the signal strength of the effective communication and sensing signal at the receiving end. At the same time, the RIS system processor calculates the required weights by minimizing the sum of the powers of all receiving ends, so as to minimize the power of the interference signal while maintaining the performance of sensing and communication.

[0036] Exemplarily, the method for obtaining the reflection weight vector under the condition of minimizing the signal interference of the communication and sensing system according to the target sensing information and satisfying the multi-path phase constraint may vary according to different application scenarios and technical requirements. For example, it can minimize the total power or the current power of the received signal, and set constraint conditions that satisfy the multi-path phase constraint, etc.

[0037] Step 103: Deploy the reflection weight vector to the multiple reflection units.

[0038] It should be noted that the RIS system can deploy weights to the corresponding reflecting array elements through the controller. For example, it can control the amplitude and phase of each reflecting array element located on the RIS system according to the calculated weights.

[0039] The present invention utilizes the interference suppression technology enabled by the intelligent reflecting surface (RIS) system to reduce the multi-base station multi-user interference according to the spatial distribution of multiple base stations (MBs), so that the MBs can ensure the communication quality and sensing accuracy of multiple user devices with the assistance of the RIS system. At the same time, the non-cooperative MB fundamentally solves the problem of the increased resource overhead of the communication and sensing system of multiple base stations and multiple user devices caused by clock synchronization.

[0040] In some embodiments, the multiple base stations use signals of the same frequency band and provide communication services and sensing services for the multiple user devices in the form of spatial division multiplexing.

[0041] It should be noted that there are multiple base stations with communication, sensing, and communication-sensing system capabilities in a certain area where wireless communication-sensing system services are provided; the multiple base stations use signals in the same frequency band and implement communication and sensing services for multiple user devices through spatial division multiplexing. In the communication-sensing service area, each base station transmits a communication waveform to its corresponding served user equipment (UE), and at the same time, each base station uses the reflected echo to sense its served UE, and each base station serves the users in the environment non-cooperatively. Multiple communication base stations serve multiple communication users simultaneously, multiple sensing base stations serve multiple sensing users simultaneously, and multiple communication-sensing base stations serve multiple communication-sensing users simultaneously. Among them, there is no signal-level cooperation relationship among the multiple base stations; one radio frequency link of each base station serves one communication, sensing, or communication-sensing user.

[0042] In some embodiments, the intelligent reflecting surface system is deployed at the middle position among the multiple base stations. The multiple reflecting units of the intelligent reflecting surface system have independent weight control capabilities, and the reflection mode of the intelligent reflecting surface system supports serving the multiple user devices and the multiple base stations in parallel.

[0043] It should be noted that the interference suppression method does not require signal-level synchronization between multiple base stations and the RIS system, can significantly reduce the synchronization and joint processing overhead required by the multi-station cooperation scheme, is applicable to the non-cooperative deployment scenario in the next-generation ISAC system, and has significant technological innovation and application value.

[0044] Among them, the RIS system can real-time sense the position information of multiple users in the service area through a multi-modal sensing module; the RIS system calculates the optimal reflection weight vector according to the sensed user information, that is, the target sensing information, through its built-in processor, and deploys the weights to each reflecting element through a controller, so as to optimize the communication signal performance and sensing performance.

[0045] In addition, the controller of the RIS system can adopt a distributed architecture, and each reflecting element has independent weight control capabilities; the reflection mode of the RIS system supports multi-user parallel service, and optimizes communication performance, sensing accuracy, and energy efficiency at the same time.

[0046] Figure 2 It is a schematic flow chart of the method for determining the reflection weight vector provided by the present invention. As Figure 2 shown, the determining the reflection weight vector according to the target sensing information may include: Step 201: Pair the position information of the multiple base stations and the multiple user devices in the target sensing information to obtain at least one base station-user pair, and the distance between the base station and the user device in each base station-user pair meets a preset distance requirement.

[0047] Exemplarily, the intelligent reflecting surface (RIS) system can sense through multi-modal that receiver RX1 is approaching base station BS1, while receiver RX2 is approaching base station BS2. The RIS system can pair RX1 with BS1 and RX2 with BS2, and then calculate the weights on the RIS system through a processor to suppress multi-base-station multi-user interference (MBMUI).

[0048] Step 202: According to the position information of each base-station user pair in the at least one base-station user pair, determine the combined communication signal vectors received by the multiple user devices, the combined sensing signal vectors received by the multiple base stations, and the uncontrollable multi-path phases of the effective sensing signals of the communication and sensing system. The effective sensing signals are used to characterize the signals transmitted between each base-station information pair, and the uncontrollable multi-path phases are used to characterize the phases on the multi-paths that do not pass through the intelligent reflecting surface system.

[0049] Exemplarily, a channel model can be established. The user equipment UE is located in different directions relative to the RIS system. In this case, the downlink communication signals received by the user equipment can be obtained.

[0050] Step 203: Obtain the reflection weight vector according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multi-path phase. The reflection weight vector is obtained by minimizing the total power of the received signals in the combined communication signal vector and the combined sensing signal vector, and satisfying the condition that the uncontrollable multi-path phase is the same as the path adjustment phase of the intelligent reflecting surface system.

[0051] It should be noted that the RIS system processor can use an optimization algorithm to adjust the RIS system reflection weight vector through a controller, so as to minimize the interference of the target communication signal and the interference of the echo sensing signal, while maintaining the performance of sensing and communication.

[0052] Exemplarily, the optimal closed-form solution of the RIS system can be obtained by deriving the interference cancellation optimization problem. To solve the MBMUI problem, it can be proposed to minimize the total power received by the sensing and communication receivers while maintaining the signal amplitude.

[0053] The embodiment of the present invention provides an interference suppression method, which ensures that the multi-base stations can still ensure the communication quality and sensing accuracy when providing non-cooperative communication and sensing integrated services with the assistance of the RIS system.

[0054] In some embodiments, determining the combined communication signal vectors received by the multiple user equipments, the combined sensing signal vectors received by the multiple base stations, and the uncontrollable multipath phases of the effective communication and sensing signals of the communication and sensing system according to the position information of each base station user pair among the at least one base station user pair may include: obtaining the combined communication signal vectors according to the channel matrix from the multiple base stations to the intelligent reflecting surface system and the channel matrix from the intelligent reflecting surface system to the multiple user equipments, where the downlink communication signals received by the multiple user equipments are determined according to the position information of the multiple user equipments relative to the intelligent reflecting surface system and the position information of the multiple base stations; obtaining the combined sensing signal vectors according to the direct vision channel matrix from the multiple base stations to the multiple user equipments and the weight matrix of the target group reflecting surface, where the target group reflecting surface is used to characterize the reflection parameters of the multiple user equipments in different positions corresponding to the multiple base stations; obtaining the distance information from the multiple base stations to the multiple user equipments and between the multiple base stations according to the target sensing information, and combining the weight matrix of the target group reflecting surface to obtain the uncontrollable multipath phases.

[0055] Figure 3 is a schematic diagram of a multi-base-station multi-user communication and sensing system provided by the present invention. As Figure 3 shown, the user equipments UE are located in different directions relative to the RIS system to establish a channel model. In this case, the downlink communication signals received by the user equipments can be expressed as: where represents the source signal vector from base stations (BS), is Gaussian noise with zero mean. Each base station and user equipment uses one antenna for communication. The channel matrix from the multi-base station (MB) to the RIS system is denoted as , and the channel matrix from the RIS system to the multi-user (MU) is denoted as . Since and have similar structures, they are uniformly represented as: where is the beam steering vector of the th incident / outgoing signal, is the direction angle of the th base station / user equipment relative to the RIS system. The weight matrix is a diagonal matrix, and each diagonal element represents the weight value of the reflecting element. Since the BS is usually at a certain height above the user equipment MU, for example, millimeter-wave (mmWave) transmission usually requires the base station to be deployed at a sufficient height to avoid obstacles and barriers, so as to ensure the realization of line-of-sight (LoS) transmission.

[0056] Figure 4 is a schematic diagram of the single-base-station to multi-user LoS communication and sensing channel model provided by the present invention. As Figure 4 shown, the received communication signal vector after combining with the line-of-sight communication channel can be expressed as: wherein, the LoS channel matrix from the MB to the MU is Here, respectively represent the incident directions from the th base station (BS) to the th user equipment (UE). It should be noted that, is similar to , but its beam steering vector is irregular, represents the irregular incident steering vector of the th base station. This irregularity stems from the different spacings between multi-users (MUs) and the variation of the incident directions from the base station to the user equipment. We extract the radar cross section (RCS) of the user equipment as a diagonal matrix and introduce path loss to simplify the derivation. In this case, multi-users (MUs) at different positions relative to the multi-base station (MB) can be equivalently modeled as a target group reflecting surface (TS). Compared with the controllable reconfigurable intelligent surface (RIS), the target group reflecting surface (TS) is uncontrollable and irregular. Therefore, the sensed signal received by the multi-base station can be expressed as: wherein, is the weight matrix of the target group reflecting surface (TS). It should be noted that, is a diagonal matrix, and each element of it consists of the radar cross section (RCS) of each user equipment (UE). Each RCS can be regarded as a "cell" of the TS, which is similar to the weight matrix of the RIS system. In addition, since the echo signal will return to the transmission direction, we respectively use and to replace the outgoing matrices of the RIS system and the TS. The matrix represents the LoS channel between multi-base stations (MBs), where has zero diagonal elements because it is assumed that each base station has performed self-interference cancellation. To simplify the formula, we will and The beam steering vectors in are combined with the path loss. Specifically, using the point-by-point product, we express the combined beam steering vector for communication as: where is the path loss factor of the cascaded link. Similarly, the combined beam steering vector for sensing can be expressed as: and It should be noted that and have different receiving directions. The symbols with a horizontal line represent the sensing vector and scalar, and their path loss value is . The path loss vector contains N cascaded path loss values. Although the specific geometric positions of the transceiver, RIS system, and TS determine the path loss values, we assume that these positions are fixed within the coherence time, so the path loss values are constants. These path loss values correspond to N different incident / outgoing distances related to the TS. Further, the signal received by the MU can be re-expressed as: where the reflecting surface communication channel is ; The sensing signal reception vector can be re-expressed as: where the reflecting surface sensing channel / target group reflection channel is ; where is the column vector form of the main diagonal elements of , represents or , / is or. Using the above formulas, the signal-to-interference-plus-noise ratio (SINR) for communication and sensing can be expressed as: and .

[0057] It can be observed that when the number of users N is large enough, the received power mainly comes from the MBMUI interference power.

[0058] wherein, according to the target sensing information, the distance information between the multiple base stations and the multiple user equipments and between the multiple base stations is obtained, and combined with the weight matrix of the target group reflecting surface, the uncontrollable multipath phase is obtained.

[0059] It should be noted that since the direct distances from each base station to each user equipment and from each base station to each base station are determined, the path loss amplitude and matrix can be obtained through the distance relationship. and matrix D, combined with the group reflector phase matrix the uncontrollable multipath phase can be obtained.

[0060] In some embodiments, obtaining the reflection weight vector according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multipath phase includes: obtaining an optimization problem expression according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multipath phase, where the optimization problem expression includes an optimization formula and a constraint formula. The optimization formula is used to minimize the total power of the received signal, and the constraint formula is used to maintain the signal amplitude and align the controllable path phase and the uncontrollable path phase; solving the optimization problem expression by constructing an objective function, where the objective function is used to represent the Lagrangian function, to obtain the reflection weight vector.

[0061] Exemplarily, the RIS system processor uses an optimization algorithm to adjust the RIS system reflection weight vector through a controller, minimizing the interference of the target communication signal and the interference of the echo sensing signal, while maintaining the performance of sensing and communication.

[0062] The present invention obtains the optimal closed-form solution of the RIS system by deriving the interference cancellation optimization problem. To solve the MBMUI problem, it is proposed to minimize the total power received by the sensing and communication receivers while maintaining the signal amplitude. The optimization problem can be formulated as follows: where represents the expectation operator, represents the complex term phase. Although the total received power can be minimized through Equation (1), the signal amplitude is maintained through Constraint Equations (2) and (3), thereby only minimizing the MBMUI power. To illustrate this more clearly, we expand the signal received by the th user equipment (UE) as: For the th BS sensing receiver, the received signal is: where and are the terms in the th row and the th column of the corresponding matrix, respectively.

[0063] As shown in the above two equations, the objectives of Constraints (2) and (3) are to align the phases of the signals passing through the controllable path and the uncontrollable path. In this way, the signal amplitudes on the two paths can be phase-summed, and only the interference power is minimized. As a result, the total receiver power is minimized, and all interference components in other directions are also minimized, including the unknown interference components from potential interference sources (such as jammers) in unknown directions. To further solve the optimization problem, we re-express the phase alignment constraint as and where is a scaling factor. By defining the matrices The received power of the th communication signal can be written as: where , and is the th communication cross-term, is the noise power of the th communication receiver. Therefore, the total communication power of all UEs is: where , . For the total power of the BS sensing receiver, the present invention has: where: is the noise power of the th sensing receiver. and are defined similarly to . By removing the constant terms, the optimization problem (P1) can be simplified to: where , . In the above equation, represents the real part of the cross-product of the controllable RIS system path and the uncontrollable path. After substituting the constraints and removing the constant terms, we can obtain , where: However, minimizing introduces the implicit constraint , which causes the sum of to be a constant, maintaining the interference from the th transmitter to the th receiver through the RIS system. Therefore, we propose to remove the remaining , the final optimization problem (P3) is obtained: The present invention constructs the Lagrangian function of problem (P3) as follows: . The matrix in the above formula is a linear constraint matrix, which can be expressed as , where: , In addition, , where: The solution of problem (P3) can be derived through the following formula: Among them, represents the pseudo-inverse operation, and the power constraint formula can be guaranteed by linearly scaling . It should be noted that while the closed-form solution aligns the multipath phases of the target signal through the RIS system, it can minimize the MBMUI power.

[0064] Next, the exemplary application of the embodiment of the present invention in an actual application scenario will be described.

[0065] As Figure 3 shown, the embodiment of the present invention provides an interference suppression method for ISAC based on non-cooperative MBMU and RIS systems, including: 301. A number of base stations cover an area with communication and sensing requirements and no cell boundary (CF).

[0066] In 301, there are multiple base stations with communication, sensing, and communication and sensing system capabilities in a certain area providing ISAC services; multiple base stations use the same frequency band signal and implement multi-user (MU) communication and sensing services through spatial division multiplexing.

[0067] 302. In the communication and sensing service area, each base station transmits a communication waveform to its corresponding served user equipment (UE), and at the same time each base station uses the reflected echo to sense its served UE, and each base station serves the users in the environment non-cooperatively; In 302, we assume that the characteristics of the quasi-optical channel are determined by the direction and distance between the transceiver. As Figure 3As shown, an intelligent reflecting surface system (RIS) is deployed in the middle of multiple base stations (MB). Each base station (BS) operates non - cooperatively in a single - base - station mode, performing downlink transmission to the closest user equipment (UE), and at the same time using the echo signals reflected from the closest UE for target sensing.

[0068] 303. There is a deployed RIS system in the communication and sensing service area to assist in the ISAC transmission of non - cooperative MBMU. The RIS system is equipped with a multi - modal sensing module, which can calculate the required reflection weight vector based on the sensing results of users and base stations, and deploy the weights to the corresponding reflecting elements through a controller. In 303, the deployed RIS system belongs to a distributed system, which is equipped with a computing processor, a RIS system controller, and multi - modal sensing capabilities for obtaining the location information of multiple users (MU). The RIS system independently assists in integrated sensing and communication (ISAC) and does not need to be synchronized with multiple base stations. An embodiment of the present invention provides a non - cooperative multi - base - station multi - user communication and sensing system architecture assisted by an intelligent reflecting surface system. The architecture includes: several base stations covering an area with communication and sensing requirements and no cell boundary (CF); within the communication and sensing service area, each base station transmits a communication waveform to its corresponding served user equipment (UE), and at the same time each base station uses the reflected echo to sense its served UE. Each base station serves the users in the environment non - cooperatively; there is a deployed RIS system in the communication and sensing service area to assist in the ISAC transmission of non - cooperative MBMU. The RIS system is equipped with a multi - modal sensing module, which can calculate the required reflection weight vector based on the sensing results of users and base stations, and deploy the weights to the corresponding reflecting elements through a controller; the RIS system processor uses an optimization algorithm to adjust the RIS system reflection weight vector through the controller, minimizing the interference of the target communication signal and the interference of the echo sensing signal, while maintaining the performance of sensing and communication.

[0069] 304. The RIS system processor uses an optimization algorithm to adjust the RIS system reflection weight vector through the controller, minimizing the interference of the target communication signal and the interference of the echo sensing signal, while maintaining the performance of sensing and communication.

[0070] In 304, we obtain the optimal closed - form solution of the RIS system by deriving the interference suppression optimization problem. To solve the MBMUI problem, we propose to minimize the total power received by the sensing and communication receivers while maintaining the signal amplitude.

[0071] Figure 5 is the structural diagram of the integrated communication and sensing architecture assisted by the intelligent reflecting surface system provided by the present invention. As Figure 5As shown in the figure, the RIS system-assisted non-cooperative multi-base station multi-user communication and sensing system architecture includes: a base station communication and sensing signal transmitting and receiving module 501, a RIS sensing module 502, a RIS processor module 503, a RIS controller and its controlled reflection unit module 504, and a user signal receiving module 505. Among them, the base station communication and sensing signal transmitting and receiving module 501 is used to transmit communication and sensing signals and receive echo signals; the RIS sensing module 502 is used to obtain the position information of the MBs and MUs; the RIS processor module 503 is used to calculate weights through the obtained position information by an optimization algorithm to suppress MBMUI; the RIS controller and its controlled reflection unit module 504 are used to deploy the optimized weights and control the amplitude and phase of each reflection element on the RIS. The user signal receiving module 505 is used to demodulate the communication signals in the communication and sensing signals transmitted by the base station and implement the communication function.

[0072] The interference suppression method provided by the embodiment of the present invention is applied to a non-cooperative multi-base station multi-user (MBMU) communication and sensing system (ISAC) architecture. Through a communication and sensing signal transmitting and receiving module, it is used to transmit wireless signals and receive echo signals of the target; a RIS sensing module is used to obtain the position information of the MBMU; a RIS processor is used to calculate the required weights through the obtained position information by an optimization algorithm to suppress MBMUI; a RIS controller can control the amplitude and phase of each reflection element located on the RIS according to the calculated weights.

[0073] Based on the foregoing embodiments, the embodiment of the present invention provides an interference suppression device. Each module included in the device, as well as each unit included in each module, can be implemented by a processor; of course, it can also be implemented by specific logic circuits; during the implementation process, the processor can be a central processing unit (CPU), a microprocessor (MPU), a digital signal processor (DSP), etc.

[0074] The interference suppression device provided by the present invention will be described below. The interference suppression device described below can be correspondingly referred to the interference suppression method described above.

[0075] Figure 6 is a schematic structural diagram of the interference suppression device provided by the present invention. As Figure 6 shown, the device 600 includes a position sensing module 601, a weight determination module 602, and a weight deployment module 603, where: The position sensing module 601 is configured to sense the positions of the multiple base stations and the multiple user devices to obtain target sensing information, where the target sensing information includes the position information of the multiple base stations and the multiple user devices; A weight determination module 602, configured to determine a reflection weight vector according to the target perception information, where the reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint, and the reflection weight vector is used to characterize the setting parameters corresponding to the plurality of reflection units, and the multipath phase constraint is used to characterize the constraint conditions generated by the signal phases received by the plurality of base stations and the plurality of user equipments being affected by the signal phases on multiple propagation paths; A weight deployment module 603, configured to deploy the reflection weight vector to the plurality of reflection units.

[0076] In some embodiments, the weight determination module 602 includes a pairing unit, a vector unit, and a weight unit, where, The pairing unit is configured to perform pairing according to the location information of the plurality of base stations and the plurality of user equipments in the target perception information to obtain at least one base station-user pair, and the distance between the base station and the user equipment in each base station-user pair satisfies a preset distance requirement; The vector unit is configured to determine, according to the location information of each base station-user pair in the at least one base station-user pair, the combined communication signal vector received by the plurality of user equipments, the combined sensing signal vector received by the plurality of base stations, and the uncontrollable multipath phase of the effective communication and sensing signal of the communication and sensing system, where the effective communication and sensing signal is used to characterize the signal transmitted between each base station information pair, and the uncontrollable multipath phase is used to characterize the phase on the multipath that does not pass through the intelligent reflecting surface system; The weight unit is configured to obtain the reflection weight vector according to the combined communication signal vector, the combined sensing signal vector, and the uncontrollable multipath phase, where the reflection weight vector is obtained by minimizing the total power of the received signals in the combined communication signal vector and the combined sensing signal vector and satisfying the condition that the uncontrollable multipath phase is the same as the path adjustment phase of the intelligent reflecting surface system.

[0077] In some embodiments, the vector unit is specifically configured to: obtain the combined communication signal vector according to the channel matrix from the plurality of base stations to the intelligent reflecting surface system and the channel matrix from the intelligent reflecting surface system to the plurality of user equipments, where the downlink communication signals received by the plurality of user equipments are determined according to the location information of the plurality of user equipments relative to the intelligent reflecting surface system and the location information of the plurality of base stations; Obtain the combined sensing signal vector according to the direct vision channel matrix from the plurality of base stations to the plurality of user equipments and the weight matrix of the target group reflecting surface, where the target group reflecting surface is used to characterize the reflection parameters of the plurality of user equipments corresponding to the plurality of base stations at different positions; Based on the target perception information, obtain the distance information between the multiple base stations and the multiple user equipments, as well as between the multiple base stations, and combine the weight matrix of the target group reflector to obtain the non-controllable multipath phase.

[0078] In some embodiments, the weight unit is specifically configured to: obtain an optimization problem expression according to the combined communication signal vector, the combined perception signal vector, and the non-controllable multipath phase. The optimization problem expression includes an optimization formula and a constraint formula. The optimization formula is used to minimize the total power of the received signal, and the constraint formula is used to maintain the signal amplitude and align the controllable path phase and the non-controllable path phase. Solve the optimization problem expression by constructing an objective function to obtain the reflection weight vector, and the objective function is used to represent the Lagrangian function.

[0079] In some embodiments, the multiple base stations use signals of the same frequency band and provide communication services and perception services for the multiple user equipments in a spatial division multiplexing manner.

[0080] In some embodiments, the intelligent reflector system is deployed at the middle position of the multiple base stations. The multiple reflection units of the intelligent reflector system have independent weight control capabilities, and the reflection mode of the intelligent reflector system supports serving the multiple user equipments and the multiple base stations in parallel.

[0081] In the embodiments of the present invention, signal interference of a multi-base station multi-user equipment communication and sensing system can be reduced, the communication quality and sensing accuracy of the multi-user equipment can be ensured, and the resource overhead of the multi-base station multi-user equipment communication and sensing system is not increased at the same time.

[0082] Figure 7 It is a schematic diagram of the entity structure of the intelligent reflector system provided by the present invention. As Figure 7As shown in the figure, the intelligent reflecting surface system may include: a processor 710, a communications interface 720, a memory 730, a communication bus 740, and a plurality of reflecting units 750. Among them, the processor 710, the communications interface 720, the memory 730, and the plurality of reflecting units 750 complete communication with each other through the communication bus 740. The plurality of reflecting units 750 include a controller and a plurality of reflecting elements. The processor 710 can call the logical instructions in the memory 730 to execute an interference suppression method, which includes: perceiving the positions of the plurality of base stations and the plurality of user equipments to obtain target perception information, where the target perception information includes the position information of the plurality of base stations and the plurality of user equipments; determining a reflection weight vector according to the target perception information, where the reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint, the reflection weight vector is used to characterize the setting parameters corresponding to the plurality of reflecting units, and the multipath phase constraint is used to characterize the constraint conditions generated by the signal phases received by the plurality of base stations and the plurality of user equipments being affected by the signal phases on multiple propagation paths; and deploying the reflection weight vector to the plurality of reflecting units.

[0083] In addition, when the logical instructions in the above-mentioned memory 730 can be implemented in the form of software functional units and sold or used as an independent product, they can be stored in a computer-readable storage medium. Based on such an understanding, the technical solution of the present invention, in essence, or the part that contributes to the prior art, or a part of this technical solution, can be embodied in the form of a software product. This computer software product is stored in a storage medium and includes several instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute all or part of the steps of the methods described in various embodiments of the present invention. The foregoing storage medium includes: various media such as USB flash drives, mobile hard disks, read-only memories (ROM, Read-Only Memory), random access memories (RAM, Random Access Memory), magnetic disks, or optical discs that can store program codes.

[0084] On the other hand, the present invention also provides a computer program product, which includes a computer program that can be stored on a non-transitory computer-readable storage medium. When the computer program is executed by a processor, the computer can execute the interference suppression method provided by each of the above methods, and the method includes: perceiving the positions of the multiple base stations and the multiple user equipments to obtain target perception information, where the target perception information includes the position information of the multiple base stations and the multiple user equipments; determining a reflection weight vector according to the target perception information, where the reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint, and the reflection weight vector is used to represent the setting parameters corresponding to the multiple reflection units, and the multipath phase constraint is used to represent the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user equipments being affected by the signal phases on multiple propagation paths; and deploying the reflection weight vector to the multiple reflection units.

[0085] The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, the processes or functions according to the embodiments of the present invention are generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable devices. The computer instructions may be stored in a computer-readable storage medium, or transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server, or data center to another website, computer, server, or data center by wire (such as coaxial cable, optical fiber, digital subscriber line (DSL)) or wirelessly (such as infrared, wireless, microwave, etc.). The computer-readable storage medium may be any available medium that a computer can store, or a data storage device such as a server or data center that includes one or more integrated available media. The available medium may be a magnetic medium (for example, a floppy disk, a hard disk, a magnetic tape), an optical medium (for example, a DVD), or a semiconductor medium (for example, a solid state disk (SSD)).

[0086] In another aspect, the present invention further provides a non-transitory computer-readable storage medium, on which a computer program is stored. When the computer program is executed by a processor, it implements the interference suppression method provided by the above-mentioned various methods. The method includes: perceiving the positions of the multiple base stations and the multiple user equipments to obtain target perception information, where the target perception information includes the position information of the multiple base stations and the multiple user equipments; determining a reflection weight vector according to the target perception information, where the reflection weight vector is obtained under the condition of minimizing the signal interference of the communication and sensing system while satisfying the multipath phase constraint. The reflection weight vector is used to represent the setting parameters corresponding to the multiple reflection units, and the multipath phase constraint is used to represent the constraint conditions generated by the signal phases received by the multiple base stations and the multiple user equipments being affected by the signal phases on multiple propagation paths; deploying the reflection weight vector to the multiple reflection units.

[0087] The above computer-readable storage medium can be any combination of one or more computer-readable media. The computer-readable medium can be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the above. More specific examples (non-exhaustive list) of the computer-readable storage medium include: an electrical connection having one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM) or a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In this document, the computer-readable storage medium can be any tangible medium that contains or stores a program, and the program can be used by or combined with an instruction execution system, apparatus, or device.

[0088] The computer-readable signal medium can include a data signal propagated in a baseband or as part of a carrier wave, which carries the computer-readable program code. Such a propagated data signal can take various forms, including - but not limited to - electromagnetic signals, optical signals, or any suitable combination of the above. The computer-readable signal medium can also be any computer-readable medium other than the computer-readable storage medium, and the computer-readable medium can send, propagate, or transmit a program for use by or combined with an instruction execution system, apparatus, or device.

[0089] The program code contained on a computer-readable medium can be transmitted using any appropriate medium, including - but not limited to - wireless, wire, optical fiber cable, radio frequency (RF), etc., or any suitable combination of the above.

[0090] The computer program code for performing the operations of this specification can be written in one or more programming languages or combinations thereof. The programming languages include object-oriented programming languages such as Java, Smalltalk, C++, and also include conventional procedural programming languages such as the "C" language or similar programming languages. The program code can be executed entirely on the user's computer, partially on the user's computer, executed as a stand-alone software package, partially on the user's computer and partially on a remote computer, or entirely on a remote computer or server. In the case of a remote computer, the remote computer can be connected to the user's computer through any type of network, including a local area network (LAN) or a wide area network (WAN), or it can be connected to an external computer (e.g., by connecting through the Internet using an Internet service provider).

[0091] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separated, and the components shown as units may be on 7 network units. Some or all of the modules can be selected according to actual needs to achieve the purpose of the solution of this embodiment. A person of ordinary skill in the art can understand and implement it without creative effort.

[0092] Through the description of the above embodiments, those skilled in the art can clearly understand that each embodiment can be implemented by means of software plus a necessary general hardware platform, and of course, it can also be implemented by hardware. Based on this understanding, the above technical solution, in essence, or the part that contributes to the prior art can be embodied in the form of a software product. This computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, magnetic disk, optical disc, etc., and includes several instructions to enable a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0093] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention, rather than to limit them; although the present invention has been described in detail with reference to the foregoing embodiments, those of ordinary skill in the art should understand that they can still modify the technical solutions described in the foregoing embodiments, or perform equivalent replacements on some of the technical features; and these modifications or replacements do not make the essence of the corresponding technical solutions deviate from the spirit and scope of the technical solutions of the embodiments of the present invention.

Claims

1. An interference suppression method, characterized in that: Applied to an intelligent reflective surface system, the intelligent reflective surface system is arranged in a synaesthesia system, the synaesthesia system includes a plurality of base stations and a plurality of user equipments, the plurality of base stations communicate and sense with the plurality of user equipments in a non-cooperative manner, the intelligent reflective surface system includes a plurality of reflection units, and the method includes: sensing the locations of the plurality of base stations and the plurality of user equipments to obtain target sensing information, wherein the target sensing information includes the location information of the plurality of base stations and the plurality of user equipments; determining a reflection weight vector according to the target perception information, the reflection weight vector being obtained by minimizing signal interference of the synaesthesia system according to the target perception information and satisfying a multipath phase constraint, the reflection weight vector being used to characterize setting parameters corresponding to the multiple reflection units, and the multipath phase constraint being used to characterize a constraint condition generated by the influence of signal phases on multiple propagation paths on signal phases received by the multiple base stations and the multiple user equipments; The reflection weight vector is deployed to the plurality of reflection units.

2. The interference suppression method according to claim 1, characterized in that: The determining of the reflection weight vector according to the target perception information comprises: Pairing the multiple base stations and the multiple user equipments according to the location information of the target perception information to obtain at least one base station user pair, wherein the distance between the base station and the user equipment in each base station user pair meets a preset distance requirement; Determine, according to the location information of each base station user pair in the at least one base station user pair, a combined communication signal vector received by the multiple user devices, a combined perception signal vector received by the multiple base stations, and an uncontrollable multipath phase of an effective synaesthesia signal of the synaesthesia system, wherein the effective synaesthesia signal is used to characterize a signal transmitted between each base station information pair, and the uncontrollable multipath phase is used to characterize a phase on a multipath that does not pass through the smart reflective surface system; The reflection weight vector is obtained according to the combined communication signal vector, the combined perception signal vector and the uncontrollable multipath phase. The reflection weight vector is obtained by minimizing the total power of the received signals in the combined communication signal vector and the combined perception signal vector, and satisfying that the uncontrollable multipath phase is the same as the path adjustment phase of the intelligent reflection surface system.

3. The interference suppression method according to claim 2, characterized in that: The step of determining, according to the location information of each base station user pair in the at least one base station user pair, the combined communication signal vectors received by the multiple user equipments, the combined perception signal vectors received by the multiple base stations, and the uncontrollable multipath phase of the effective synaesthesia signal of the synaesthesia system comprises: The combined communication signal vector is obtained according to a channel matrix from the multiple base stations to the smart reflective surface system and a channel matrix from the smart reflective surface system to the multiple user equipments, wherein the downlink communication signals received by the multiple user equipments are determined according to the position information of the multiple user equipments relative to the smart reflective surface system and the position information of the multiple base stations; Obtaining the combined perception signal vector according to direct-view channel matrices from the multiple base stations to the multiple user equipments and a weight matrix of a target group reflection surface, wherein the target group reflection surface is used to characterize reflection parameters of the multiple user equipments at different positions corresponding to the multiple base stations; The distance information from the multiple base stations to the multiple user equipments and between the multiple base stations is obtained according to the target perception information, and the uncontrollable multipath phase is obtained in combination with the weight matrix of the target group reflection surface.

4. The interference suppression method according to claim 2, characterized in that: The obtaining the reflection weight vector according to the combined communication signal vector, the combined perception signal vector and the uncontrollable multipath phase includes: Obtaining an optimization problem expression according to the combined communication signal vector, the combined perception signal vector, and the uncontrollable multipath phase, wherein the optimization problem expression includes an optimization formula and a constraint formula, wherein the optimization formula is used to minimize the total power of the received signal, and the constraint formula is used to maintain the signal amplitude and align the controllable path phase with the uncontrollable path phase; The optimization problem expression is solved by constructing an objective function to obtain the reflection weight vector, and the objective function is used to characterize the Lagrangian function.

5. The interference suppression method according to claim 1, characterized in that: The multiple base stations use the same frequency band signal to provide communication services and perception services to the multiple user equipments in the form of space division multiplexing.

6. The interference suppression method according to claim 1, characterized in that: The intelligent reflecting surface system is deployed in the middle of the multiple base stations. The multiple reflecting units of the intelligent reflecting surface system have independent weight control capabilities. The reflection mode of the intelligent reflecting surface system supports parallel services for the multiple user equipments and the multiple base stations.

7. An interference suppression device, characterized in that: Applied to an intelligent reflective surface system, the intelligent reflective surface system is arranged in a synaesthesia system, the synaesthesia system includes a plurality of base stations and a plurality of user equipments, the plurality of base stations and the plurality of user equipments communicate and sense in a non-cooperative manner, the intelligent reflective surface system includes a plurality of reflection units, and the device includes: A location sensing module, configured to sense the locations of the plurality of base stations and the plurality of user equipments to obtain target sensing information, wherein the target sensing information includes the location information of the plurality of base stations and the plurality of user equipments; A weight determination module, configured to determine a reflection weight vector according to the target perception information, wherein the reflection weight vector is obtained while minimizing the signal interference of the synaesthesia system and satisfying a multipath phase constraint, wherein the reflection weight vector is used to characterize the setting parameters corresponding to the multiple reflection units, and the multipath phase constraint is used to characterize the constraint condition generated by the signal phases received by the multiple base stations and the multiple user equipments being affected by the signal phases on multiple propagation paths; A weight deployment module is used to deploy the reflection weight vector to the multiple reflection units.

8. An intelligent reflective surface system, comprising a plurality of reflective units, a memory, a processor, and a computer program stored in the memory and running on the processor, characterized in that: When the processor executes the computer program, the interference suppression method according to any one of claims 1 to 6 is implemented.

9. A non-transitory computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the interference suppression method according to any one of claims 1 to 6 is implemented.

10. A computer program product, comprising a computer program, characterized in that When the computer program is executed by a processor, the interference suppression method according to any one of claims 1 to 6 is implemented.

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