Segmented channel estimation-based interference elimination method for flux-inductance integrated system

Abstract

The invention discloses a method for eliminating interference of a communication and sensing integrated system based on segmented channel estimation, which comprises the following steps of: establishing a channel model and a data transmission model of a non-cellular cooperative communication and sensing integrated system, sending uplink pilot frequency through all users, and estimating a data transmission channel between the users and an access point (AP) by a central processing unit (CPU); a target detection signal is sent through all downlink access points (AP), all uplink access points (AP) jointly receive signals, and a central processing unit (CPU) detects whether a sensing target is in a scene or not; downlink pilot frequencies are sent through all downlink access points (AP), and a central processing unit (CPU) obtains estimation of a cross link interference channel between the access points (AP); the system simultaneously performs uplink and downlink communication and senses the moving direction and speed of a target, and performs interference elimination processing on received communication and sensing signals based on a channel estimation result. According to the invention, system interference can be effectively and directly suppressed, and communication and sensing performance is improved.

Description

Technical Field

[0001] The invention belongs to the technical field of cooperative synaesthesia integration of non-cellular large-scale MIMO systems, and in particular relates to a synaesthesia integration system interference elimination method based on segmented channel estimation. Background Art

[0002] ISAC technology can significantly improve the system spectrum efficiency and reduce the implementation cost while integrating communication and perception functions by sharing spectrum resources and reusing hardware architecture. It is very suitable for emerging technologies such as Internet of Vehicles and drones. The collaborative ISAC system based on non-cellular massive MIMO is a powerful supporting architecture for realizing the 6G intelligent connection of all things. In the non-cellular massive MIMO system, multiple access nodes AP are connected to a central processing unit CPU, which operates all access nodes to serve all user devices through coherent transmission and reception, and completes the perception of targets in the scene through the collaborative transmission and reception of perception signals by downlink access nodes and uplink access nodes.

[0003] However, there are many highly coupled and difficult-to-handle interferences in the cooperative synaesthesia integration system based on non-cellular massive MIMO, including: cross-link interference between uplink users and downlink users, cross-link interference between downlink access nodes and uplink access nodes, and interference between communication signals and perception signals. The interference suppression schemes in the existing cooperative synaesthesia integration technology all indirectly eliminate the influence of various interferences through resource scheduling optimization algorithms such as power allocation, precoding design, and receiver design. No scheme has been proposed to directly eliminate interference from a mechanism perspective. Therefore, it is necessary to design an effective synaesthesia integration interference suppression scheme from the perspective of direct interference elimination. Summary of the invention

[0004] The purpose of the present invention is to provide a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation, so as to solve the problem that there is no direct interference elimination solution in the prior art, and to effectively and directly suppress system interference and improve communication and perception performance.

[0005] To achieve the above object, the present invention adopts the following technical solutions:

[0006] A method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation comprises the following steps:

[0007] Step 1, establish a channel model and a data transmission model of the non-cellular cooperative interawareness integrated system, by sending uplink pilots by all users, the central processing unit CPU estimates the data transmission channel between the user and the access node AP, wherein the access node AP includes an uplink access node AP and a downlink access node AP;

[0008] Step 2: Send a target detection signal through all downlink access nodes AP, all uplink access nodes AP jointly receive the signal and transmit it to the central processing unit CPU, and the central processing unit CPU detects whether the perceived target is in the scene;

[0009] Step 3: Send downlink pilots through all downlink access nodes AP, and the central processing unit CPU obtains an estimate of the cross-link interference channel between the access nodes AP by combining the pilots received by all uplink access nodes AP and the target detection result obtained in step 2;

[0010] Step 4: The non-cellular cooperative interaceptive integrated system simultaneously performs uplink and downlink communications and perception of the target's moving direction and speed, and based on the channel estimation results obtained in steps 1 and 3, performs interference elimination processing on the received communication and perception signals respectively.

[0011] The step 1 specifically includes:

[0012] Step 101, in a non-cellular cooperative synaesthesia integrated system, a regional scene model managed by a central processing unit CPU is established; wherein M access nodes AP and K users are distributed; and M access nodes AP have M ul work in uplink mode, and the remaining M dl works in downlink mode; K users include K ul uplink demand users and K dl Downlink demand users; each access node AP is equipped with N antennas and connected to the central processing unit CPU through the fronthaul link; at the same time, there is a target with uncertain position in the scene. The non-cellular cooperative interawareness integrated system needs to simultaneously complete the uplink communication of the uplink demand users, the downlink communication of the downlink demand users, and the perception of the target's moving direction and speed;

[0013] Using the fast fading channel model, the channel condition in each coherent time block remains unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with N rows and 1 column in, represents the large-scale fading coefficient between the kth user and the mth access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of N represents the identity matrix with N rows and columns;

[0014] In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,N ul ], i is any integer in the set [1,M dl ], the direct channel without target reflection between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of ;

[0015] The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Respectively represent the path loss coefficient and radar cross section coefficient; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vector from the uth uplink access node AP and the ith downlink access node AP to the target, with a superscript symbol (·) H Indicates the conjugate transpose operation of the matrix; since the existence of the target is unknown to the CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and is recorded as

[0016] Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ p Indicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Matrix of columns For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get

[0017]

[0018] Among them, ρ p represents the pilot transmission power of the user, represents the set of serial numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k'th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a zero mean and a variance of The complex Gaussian distribution of

[0019] According to the minimum mean square error (MMSE) channel estimation method, the channel estimation from the kth user to the mth access node AP in this coherent time block is obtained.

[0020]

[0021] in, It means taking the mean of the values ​​in brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k'th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the kth user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

[0022] The step 2 specifically includes:

[0023] Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s The number of symbols occupied by the second stage is shown in the table; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive signals and detect the presence of the perceived target;

[0024] Let t be the set [1,τs ] is any integer in the range of , in the tth time slot of this phase, the uth uplink access node AP receives the N rows and 1 column target detection signal Expressed as

[0025]

[0026] in, is the N-row and 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the u-th uplink access node AP in the t-th time slot of the second phase, which obeys symbol represents a value with zero mean and a correlation coefficient of A multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise;

[0027] Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Respectively represent the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, the vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA A multivariate cyclically symmetric complex Gaussian distribution of It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix; the target reflection channel between all access nodes AP After vectorization, the vertical connection follows the distribution symbol It means that the mean is And the variance matrix R ATA A multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes AP known to all central processing units CPU The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel vectorization between all access nodes AP;

[0028] The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as

[0029]

[0030] in

[0031]

[0032]

[0033]

[0034] exp(·) represents exponential function operation, det(·) represents determinant operation on matrix, and ||·|| represents Euclidean norm operation on vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Respectively represent the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of

[0035] Set the comparison pre-threshold Λ det,Th , when the CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the CPU calculates that Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol

[0036] The step 3 specifically includes:

[0037] Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τs +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τ dp The number of symbols occupied by the third stage of the table; and when δ T =0 When δ T =1

[0038] At this stage, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; let n be any integer in the set [1, N], and the pilot sent by the nth antenna of the i-th downlink access node AP is denoted as The downlink pilot signal received by the uth uplink access node AP Expressed as

[0039]

[0040] Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP, is the additive Gaussian white noise matrix of the uth uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0041] Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in the coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as

[0042]

[0043] in, means taking the mean of the values ​​in the brackets, Cov9·,·) means taking the covariance matrix operation of the vectors in the brackets, At the same time, because the CPU cannot know that the target has a symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ T Replace with get That is, the channel estimation from the nth antenna of the i-th downlink access node AP to the u-th access node AP obtained by the central processing unit CPU in the third stage.

[0044] The step 4 specifically includes:

[0045] Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and senses the target moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal including a downlink communication signal and a sensing signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node;

[0046] The received signal of the lth downlink user is expressed as:

[0047]

[0048] in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l'th downlink user, Represents the communication signal to the l'th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the k-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user;

[0049] According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated;

[0050] Step 402: The received signal of the i-th uplink access node AP is expressed as

[0051]

[0052] in, Represents the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, represents the noise received by the uth uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in

[0053]

[0054] in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP;

[0055] The signal of the jth uplink user received by the central processing unit CPU is expressed as:

[0056]

[0057] Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j' represents the transmit power of the j'th uplink user, represents the channel estimation from the j'th uplink user to the uth uplink access node AP, represents the communication signal of the j'th uplink user;

[0058] represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmission power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user;

[0059] Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference;

[0060] According to the expected signal and interference signal of the jth uplink user received by the central processing unit CPU, a high-precision uplink communication signal can be demodulated;

[0061] Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as:

[0062]

[0063] in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference. represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference;

[0064] Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal;

[0065] Indicates the residual downlink communication signal interference after interference elimination;

[0066] A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

[0067] Beneficial effect: The invention discloses a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation, which has the following advantages: in view of the numerous complex interference problems in the cellular-free collaborative synaesthesia integrated system, the advantages of high concentration and high coverage of the cellular-free architecture are fully utilized, and the communication and perception performance of the system are greatly improved by using direct interference elimination technology. The invention first establishes a model of channel, transmission signal and interference according to the system scenario. Then, the estimated channel and estimated error channel of data transmission between the user and the access node AP after sending the uplink pilot are derived. Then, a target detection inequality is established to detect whether there is a perception target in the scene, and the estimated channel and estimated error channel of cross-link interference between APs after sending the downlink pilot are derived. Finally, an interference elimination method and a sequential processing order based on the estimated channel are proposed when full-duplex communication and target perception are carried out simultaneously. Compared with the existing indirect interference suppression scheme based on resource scheduling, the method proposed in the invention can directly eliminate interference, which is not only suitable for multiple demand scenarios under the cellular-free synaesthesia integrated architecture, but also can be combined with the existing indirect interference suppression scheme to further improve the system performance, which is of great significance to the actual deployment of 6G synaesthesia integration. BRIEF DESCRIPTION OF THE DRAWINGS

[0068] Figure 1 It is an overall flow chart of the interference elimination method of the synaesthesia integrated system based on segmented channel estimation;

[0069] Figure 2 This is a comparison chart of the accuracy of the second-stage target detection algorithm;

[0070] Figure 3 It is a comparison chart of communication performance when different interference elimination schemes are adopted. DETAILED DESCRIPTION

[0071] The present invention will be further explained below in conjunction with the accompanying drawings.

[0072] In order to better understand the purpose, structure and function of the present invention, the following further describes in detail the interference elimination method of the synaesthesia integration system based on segmented channel estimation of the present invention in conjunction with the accompanying drawings.

[0073] Assume a non-cellular distributed massive MIMO interawareness integration scenario, where there are M = 10 half-duplex APs, of which the number of uplink access node APs is M ul =5, the number of downlink access nodes AP is M dl =5, each access node AP is equipped with N = 4 antennas, and there are K = 8 users in the scenario, of which the number of users with uplink requirements is K ul =4, the number of users with downlink demand is K dl=4. All access nodes AP and users are randomly distributed in an area with a radius of R = 100m. The maximum uplink transmission power of each user is ρ UE =100mW, the maximum downlink transmission power of each access node AP is ρ AP =2W. The path loss index of the channel between the access node AP and the user is set to α = 3.7. Each coherence time block lasts for 200 symbols, where τ p =5,τ s =10,τ dp =20.

[0074] Based on the non-cellular distributed massive MIMO synaesthesia integration scenario provided above, a synaesthesia integration system interference elimination method based on segmented channel estimation in this embodiment includes the following steps:

[0075] Step 1, establish a channel model and a data transmission model of the non-cellular cooperative interawareness integrated system, by sending uplink pilots by all users, the central processing unit CPU estimates the data transmission channel between the user and the access node AP, wherein the access node AP includes an uplink access node AP and a downlink access node AP;

[0076] Step 1 specifically includes:

[0077] Step 101, in a non-cellular cooperative synaesthesia integrated system, a regional scene model managed by a central processing unit CPU is established; wherein M access nodes AP and K users are distributed; and M access nodes AP have M ul work in uplink mode, and the remaining M dl works in downlink mode; K users include K ul uplink demand users and K dl Downlink demand users; each access node AP is equipped with N antennas and connected to the central processing unit CPU through the fronthaul link; at the same time, there is a target with uncertain position in the scene. The non-cellular cooperative interawareness integrated system needs to simultaneously complete the uplink communication of the uplink demand users, the downlink communication of the downlink demand users, and the perception of the target's moving direction and speed;

[0078] Using the fast fading channel model, the channel condition in each coherent time block remains unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with n rows and 1 column in, represents the large-scale fading coefficient between the kth user and the mth access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of N represents the identity matrix with N rows and columns;

[0079] In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,M ul ], i is any integer in the set [1,M dl ], the direct channel without target reflection between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of ;

[0080] The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Respectively represent the path loss coefficient and radar cross section coefficient; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vector from the uth uplink access node AP and the ith downlink access node AP to the target, with a superscript symbol (·) H Indicates the conjugate transpose operation of the matrix; since the existence of the target is unknown to the CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and is recorded as

[0081] Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ pIndicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Matrix of columns For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get

[0082]

[0083] Among them, ρ p represents the pilot transmission power of the user, represents the set of serial numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k'th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a zero mean and a variance of The complex Gaussian distribution of

[0084] According to the minimum mean square error (MMSE) channel estimation method, the channel estimation from the kth user to the mth access node AP in this coherent time block is obtained.

[0085]

[0086] in, It means taking the mean of the values ​​in brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k'th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the kth user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

[0087] Step 2: Send a target detection signal through all downlink access nodes AP, all uplink access nodes AP jointly receive the signal and transmit it to the central processing unit CPU, and the central processing unit CPU detects whether the perceived target is in the scene;

[0088] Step 2 specifically includes:

[0089] Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s The number of symbols occupied by the second stage is shown in the table; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive signals and detect the presence of the perceived target;

[0090] Let t be the set [1,τ s ] is any integer in the range of , in the tth time slot of this phase, the uth uplink access node AP receives the N rows and 1 column target detection signal Expressed as

[0091]

[0092] in, is the N-row and 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the u-th uplink access node AP in the t-th time slot of the second phase, which obeys symbol represents a value with zero mean and a correlation coefficient of A multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise;

[0093] Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Respectively represent the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, the vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA A multivariate cyclically symmetric complex Gaussian distribution of

[0094] It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix; the target reflection channel between all access nodes AP After vectorization, the vertical connection follows the distribution symbol It means that the mean is And the variance matrix R ATA A multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes AP known to all central processing units CPU The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel vectorization between all access nodes AP;

[0095] The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as

[0096]

[0097] in

[0098]

[0099]

[0100]

[0101] exp(·) represents exponential function operation, det(·) represents determinant operation on matrix, and ||·|| represents Euclidean norm operation on vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Respectively represent the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of

[0102] Set the comparison pre-threshold Λ det,Th, when the CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the CPU calculates that Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol

[0103] Step 3: Send downlink pilots through all downlink access nodes AP, and the central processing unit CPU obtains an estimate of the cross-link interference channel between the access nodes AP by combining the pilots received by all uplink access nodes AP and the target detection result obtained in step 2;

[0104] Step 3 specifically includes:

[0105] Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τ s +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τ dp The number of symbols occupied by the third stage of the table; and when δ T =0 When δ T =1

[0106] At this stage, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; let n be any integer in the set [1, N], and the pilot sent by the nth antenna of the i-th downlink access node AP is denoted as The downlink pilot signal received by the uth uplink access node AP Expressed as

[0107]

[0108] Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the uth downlink access node AP to the ith access node AP, is the additive Gaussian white noise matrix of the i-th uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of

[0109] Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in the coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as

[0110]

[0111] in, means taking the mean of the values ​​in the brackets, Cov(·,·) means taking the covariance matrix operation of the vectors in the brackets, At the same time, because the CPU cannot know that the target has a symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ T Replace with get That is, the channel estimation from the nth antenna of the i-th downlink access node AP to the u-th access node AP obtained by the central processing unit CPU in the third stage.

[0112] Step 4: The system simultaneously performs uplink and downlink communications and senses the target's moving direction and speed, and based on the channel estimation results obtained in steps 1 and 3, performs interference elimination processing on the received communication and sensing signals respectively;

[0113] Step 4 specifically includes:

[0114] Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and senses the target moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal including a downlink communication signal and a sensing signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node;

[0115] The received signal of the lth downlink user is expressed as:

[0116]

[0117] in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l'th downlink user, Represents the communication signal to the l'th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the k-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user;

[0118] According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated;

[0119] Step 402: The received signal of the uth uplink access node AP is expressed as

[0120]

[0121] in, Represents the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, represents the noise received by the uth uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in

[0122]

[0123] in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP;

[0124] The signal of the jth uplink user received by the central processing unit CPU is expressed as:

[0125]

[0126] Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j' represents the transmit power of the j'th uplink user, represents the channel estimation from the j'th uplink user to the uth uplink access node AP, represents the communication signal of the j'th uplink user; represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmission power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user;

[0127] Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference;

[0128] According to the expected signal and interference signal of the jth uplink user received by the central processing unit CPU, a high-precision uplink communication signal can be demodulated;

[0129] Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as:

[0130]

[0131] in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference. represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference;

[0132] Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal;

[0133] Indicates the residual downlink communication signal interference after interference elimination;

[0134] A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

[0135] Figure 1 It is an overall flow chart of a method for eliminating interference of a synaesthesia integrated system based on segmented channel estimation of the present invention.

[0136] Figure 2 This is a comparison chart of the accuracy of the second-stage target detection algorithm, showing the accuracy of the MAPRT target detector in the stage symbol number τ s and the detector threshold Λ det,Th The false alarm probability P when taking different values fa , Missed detection probability P md And the correct detection probability P d It reveals that increasing τ s More detection support data can be provided, which improves the accuracy of detection, but the gains gradually decrease. s =10 to 20, the accuracy gain is significantly less than the gain from 5 to 10. det,Th The value of P also seriously affects fa and P md For our simulations, we set Λ det,Th =250, thus a detection probability of 0.925 can be obtained.

[0137] Figure 3 is a comparison chart of communication performance when different interference elimination schemes are used, comparing the T =1) and does not exist (δ T=0), the improvement of spectrum efficiency after adopting different interference elimination strategies. T =1) and w / o(δ T =0) respectively represent the uplink and rate when the interference elimination scheme is not adopted when there is / is not a target in the scene; w / e withδ T (δ T =1) and w / e withδ T (δ T =0) respectively represent the uplink and rate when the ideal interference elimination scheme is adopted when there is / is not a target in the scene, that is, the target detection error is not considered; w / e with represents the system uplink sum rate when the interference elimination solution provided by this example is adopted; w / c represents the system uplink sum rate when the ideal interference elimination solution is adopted. w / o(δ T =1) and w / o(δ T = 0) clearly shows the performance degradation caused by the target reflection channel. Taking into account the impact of target detection error, the uplink sum rate can still reach 95% of w / c. This proves that the proposed interference management mechanism can effectively and directly suppress interference.

[0138] In summary, the present invention proposes a method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation for the interference suppression problem in a non-cellular large-scale MIMO system cooperative synaesthesia integrated scenario. The present invention first establishes a model of channel, transmission signal and interference according to the system scenario. Then, the estimated channel and estimated error channel of data transmission between the user and the access node AP after sending the uplink pilot are derived. Then, the target detection inequality is established to detect whether there is a perception target in the scenario, and the estimated channel and estimated error channel of the cross-link interference between APs after sending the downlink pilot are derived. Finally, an interference elimination method based on the estimated channel and the sequential processing order when full-duplex communication and target perception are carried out simultaneously are proposed. Compared with the existing indirect interference suppression scheme based on resource scheduling, the method proposed in the present invention can directly eliminate interference, which is not only suitable for multiple demand scenarios under the non-cellular synaesthesia integrated architecture, but also can be combined with the existing indirect interference suppression scheme to further improve the system performance, which is of great significance to the actual deployment of 6G synaesthesia integration.

[0139] The above is only a preferred embodiment of the present invention. It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principle of the present invention. These improvements and modifications should also be regarded as the scope of protection of the present invention.

Claims

1. A method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation, characterized in that: The following steps are involved: Step 1, establish a channel model and a data transmission model of the non-cellular cooperative interawareness integrated system, by sending uplink pilots by all users, the central processing unit CPU estimates the data transmission channel between the user and the access node AP, wherein the access node AP includes an uplink access node AP and a downlink access node AP; Step 2: Send a target detection signal through all downlink access nodes AP, all uplink access nodes AP jointly receive the signal and transmit it to the central processing unit CPU, and the central processing unit CPU detects whether the perceived target is in the scene; Step 3: Send downlink pilots through all downlink access nodes AP, and the central processing unit CPU obtains an estimate of the cross-link interference channel between the access nodes AP by combining the pilots received by all uplink access nodes AP and the target detection result obtained in step 2; Step 4: The non-cellular cooperative interaceptive integrated system simultaneously performs uplink and downlink communications and perception of the target's moving direction and speed, and based on the channel estimation results obtained in steps 1 and 3, performs interference elimination processing on the received communication and perception signals respectively.

2. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 1 specifically includes: Step 101, in a non-cellular cooperative synaesthesia integrated system, a regional scene model managed by a central processing unit CPU is established; wherein M access nodes AP and K users are distributed; and M access nodes AP have M ul work in uplink mode, and the remaining M dl works in downlink mode; K users include K ul uplink demand users and K dl Downlink demand users; each access node AP is equipped with N antennas and connected to the central processing unit CPU through the fronthaul link; at the same time, there is a target with uncertain position in the scene. The non-cellular cooperative interawareness integrated system needs to simultaneously complete the uplink communication of the uplink demand users, the downlink communication of the downlink demand users, and the perception of the target's moving direction and speed; Using the fast fading channel model, the channel condition in each coherent time block remains unchanged, and the channel in the non-cellular cooperative synaesthesia integrated system scenario is modeled: let k be any integer in the set [1, K], m be any integer in the set [1, M], and the channel vector from the kth user to the mth access node AP is recorded as a vector with N rows and 1 column in, represents the large-scale fading coefficient between the kth user and the mth access node AP, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of N represents the identity matrix with N rows and columns; In the same way, let j be the set [1,K ul ], l is any integer in the set [1,K dl ], the channel from the jth uplink user to the lth downlink user is recorded as a complex number Let u be the set [1,N ul ], i is any integer in the set [1,M dl ], the direct channel without target reflection between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix in, represents the large-scale fading coefficient, express The small-scale fast fading matrix, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of ; The existence of the target will cause a channel reflected by the target to exist between the uplink access node AP and the downlink access node AP. The target reflection channel between the u-th uplink access node AP and the i-th downlink access node AP is recorded as an N-row N-column complex matrix Among them, θ RCS and Respectively represent the path loss coefficient and radar cross section coefficient; a ul,u and a dl,i is a vector with N rows and 1 column, representing the steering vectors from the uth uplink access node AP and the ith downlink access node AP to the target, with superscript symbol (·) H Indicates the conjugate transpose operation of the matrix; since the existence of the target is unknown to the CPU, the target existence symbol δ is established T To indicate whether the target appears in the scene, δ T =0 means it does not exist, δ T =1 means existence; since the position of the target is unknown, the CPU obtains the prior target reflection channel through prior knowledge and is recorded as Step 102, the first τ in each coherent time block p symbols are used to estimate the data transmission channel between the user and the access node AP, τ p Indicates the number of symbols occupied in the first stage; in this stage, K users randomly select pilot signals to send, and the uplink pilot signal received by the mth access node AP is represented by an N-line τ p Matrix of columns For channel estimation from the kth user to the mth access node AP, we need to first Multiply by the pilot signal sent by the kth user get Among them, ρ p represents the pilot transmission power of the user, represents the set of serial numbers of users using the same pilot as the k-th user and does not include k, represents the channel from the k'th user to the mth access node AP, is the additive Gaussian white noise matrix from the kth user to the mth access node AP, which has a zero mean and a variance of The complex Gaussian distribution of According to the minimum mean square error (MMSE) channel estimation method, the channel estimation from the kth user to the mth access node AP in this coherent time block is obtained. in, It means taking the mean of the values ​​in brackets. yes The equivalent large-scale fading coefficient of represents the large-scale fading coefficient of the channel between the kth user and the mth access node AP, represents the large-scale fading coefficient of the channel between the k'th user and the mth access node AP, represents the set of serial numbers of users using the same pilot as the kth user, express The small-scale fast fading vector, which has a mean of 0 and a correlation matrix of I N The multivariate cyclically symmetric complex Gaussian distribution of The channel estimation error is recorded as represents the channel estimation error vector from the kth user to the mth access node AP.

3. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 2 specifically includes: Step 201, in each coherent time block (τ p +1)~(τ p +τ s ) symbols are used to detect whether the perceived target is in the scene, τ s The number of symbols occupied by the second stage is shown in the table; in this stage, all downlink access nodes AP send target detection signals, and all uplink access nodes AP jointly receive signals and detect the presence of the perceived target; Let t be the set [1,τ s ] is any integer in the range of , in the tth time slot of this phase, the uth uplink access node AP receives the N rows and 1 column target detection signal Expressed as in, is the N-row and 1-column detection signal sent by the i-th downlink access node AP in the t-th time slot of the second phase, is the additive white noise received by the u-th uplink access node AP in the t-th time slot of the second phase, which obeys symbol represents a value with zero mean and a correlation coefficient of A multivariate cyclically symmetric complex Gaussian distribution of is the variance of the channel noise; Step 202: ul The signals received by the uplink access nodes AP in the tth time slot are vertically linked to obtain M ul A vector with N rows and 1 column Represents the signal received by the central processing unit CPU in the tth time slot, where and Represents the 1st and Mth ul The uplink access node AP receives the target detection signal in the tth time slot, and the superscript symbol (·) T Indicates the transposition operation of the matrix; direct channels between all access nodes AP After vectorization, the vertical connection follows the distribution symbol Represents a matrix with zero mean and variance R AA A multivariate cyclically symmetric complex Gaussian distribution of It is a direct channel between all access nodes AP The variance matrix of the distribution after vectorization, diag{·} represents the diagonal matrix established with the vector in the brackets as the diagonal, represents the large-scale fading coefficient of the direct channel between the ath uplink access node AP and the bth downlink access node AP, Indicates that both rows and columns are N 2 The identity matrix of all access nodes AP target reflection channel After vectorization, the vertical connection follows the distribution symbol It means that the mean is And the variance matrix R ATA A multivariate cyclically symmetric complex Gaussian distribution of It is the target reflection a priori channel between access nodes AP known to all central processing units CPU The vector connected vertically after vectorization, R ATA is the variance matrix of the distribution obeyed by the target reflection channel vectorization between all access nodes AP; The maximum a posteriori ratio test (MAPRT) is used to use this stage τ s The signal received by the CPU in each time slot is used to detect whether the target exists. The maximum a posteriori ratio test target detection formula Λ is expressed as in exp(·) represents exponential function operation, det(·) represents determinant operation on matrix, and ||·|| represents Euclidean norm operation on vector; It is the aggregate signal of the sensing signals sent by all downlink access nodes AP in the tth time slot. and Represents the 1st and Mth dl The detection signal sent by the downlink access node AP in the tth time slot of the second phase is: represents the Kronecker product, Indicates that both rows and columns are M ul The identity matrix of Set the comparison pre-threshold Λ det,Th , when the CPU calculates Λ≥Λ det,Th When the CPU thinks that the target exists in the scene, the target has an estimated symbol When the CPU calculates that Λ<Λ det,Th When the CPU thinks that the target does not exist in the scene, the target has an estimated symbol 4. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 3 specifically includes: Step 301, in each coherent time block (τ p +τ s +1)~(τ p +τ s +τ dp ) symbols are used to estimate the cross-link interference channel between access nodes AP τ dp The number of symbols occupied by the third stage of the table; and when δ T =0 When δ T =1 At this stage, all antennas of all downlink access nodes AP send mutually orthogonal downlink pilots; let n be any integer in the set [1, N], and the pilot sent by the nth antenna of the i-th downlink access node AP is denoted as The downlink pilot signal received by the uth uplink access node AP Expressed as Among them, ρ dp is the transmit power of the downlink pilot, represents the channel vector from the nth antenna of the uth downlink access node AP to the ith access node AP, is the additive Gaussian white noise matrix of the i-th uplink access node AP at this stage, which has a mean of 0 and a variance of The complex Gaussian distribution of Step 302: Obtain the channel estimation vector from the nth antenna of the i-th downlink access node AP to the u-th access node AP in the coherent time block according to the minimum mean square error (MMSE) channel estimation method. Expressed as in, means taking the mean of the values ​​in the brackets, Cov(·,·) means taking the covariance matrix operation of the vectors in the brackets, At the same time, because the CPU cannot know that the target has a symbol δ T , the target existence estimation symbol can only be obtained through the second stage Therefore, it is necessary to δ T Replace with get That is, the channel estimation from the nth antenna of the i-th downlink access node AP to the u-th access node AP obtained by the central processing unit CPU in the third stage.

5. The method for eliminating interference in a synaesthesia integrated system based on segmented channel estimation according to claim 1, characterized in that: The step 4 specifically includes: Step 401: The non-cellular cooperative synaesthesia integrated system simultaneously performs uplink and downlink communications and senses the target moving direction and speed. At this time, each downlink access node AP sends a synaesthesia integrated signal including a downlink communication signal and a sensing signal. The signal sent by the i-th downlink access node is in, represents the communication precoding vector of the i-th downlink access node to the l-th downlink user, represents the communication signal to the lth downlink user; represents the perceptual precoding vector of the i-th downlink access node, represents the perception signal of the i-th downlink access node; The received signal of the lth downlink user is expressed as: in, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the lth downlink user to the i-th downlink access node AP; Indicates the communication interference of other downlink users, represents the communication precoding vector of the i-th downlink access node to the l'th downlink user, Represents the communication signal to the l'th downlink user; represents the interference caused by the channel estimation error between the user and the access node AP, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP, represents the communication precoding vector of the i-th downlink access node to the j-th downlink user, represents the communication signal for the kth downlink user; Indicates the interference caused by the perceived signal, represents the channel estimation error from the lth downlink user to the i-th downlink access node AP; represents the cross-link interference, ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; represents the noise interference of the lth downlink user; According to the desired signal and interference signal received by the lth downlink user, a high-precision downlink communication signal can be demodulated; Step 402: The received signal of the uth uplink access node AP is expressed as in, Represents the transmission signal of all uplink users, Indicates the communication signal of all downlink access nodes AP, represents the noise received by the uth uplink access node AP at this stage; the estimated channel between access nodes AP obtained in the third stage is eliminated Cross-link interference in in is the cross-link interference estimation channel matrix from the u-th uplink access node AP to the i-th downlink access node AP, and They represent the channel estimation from the 1st antenna of the i-th downlink access node AP to the u-th access node AP and the channel estimation from the Nth antenna of the i-th downlink access node AP to the u-th access node AP respectively; ρ ul,j represents the transmit power of the jth uplink user, represents the communication signal of the jth uplink user; is the cross-link interference channel matrix from the u-th uplink access node AP to the i-th downlink access node AP; The signal of the jth uplink user received by the central processing unit CPU is expressed as: Among them, v uj represents the maximum ratio combining receiver vector of the jth uplink user’s signal received by the uth uplink access node AP, represents the communication signal that the lth downlink user expects to obtain, represents the channel estimation from the jth uplink user to the uth uplink access node AP; represents the communication interference of other downlink users, ρ ul,j' represents the transmit power of the j'th uplink user, represents the channel estimation from the j'th uplink user to the uth uplink access node AP, represents the communication signal of the j'th uplink user; represents the interference caused by the channel estimation error between the user and the access node AP, ρ ul,k represents the transmission power of the kth uplink user, represents the channel estimation error from the kth uplink user to the uth uplink access node AP, represents the communication signal of the kth uplink user; Indicates the interference caused by the perceived signal, is the cross-link interference estimation channel error matrix from the u-th uplink access node AP to the i-th downlink access node AP; Indicates cross-link interference; Indicates noise interference; According to the expected signal and interference signal of the jth uplink user received by the central processing unit CPU, a high-precision uplink communication signal can be demodulated; Step 403: The signal received by the uth uplink access node AP When performing sensory signal detection, it is reformulated as: in, represents the perception signal that the u-th uplink access node AP expects to obtain; Indicates uplink communication signal interference. represents the channel vector from the kth uplink user to the uth uplink access node AP; Indicates downlink communication signal interference; Based on the decoding of the uplink and downlink communication signals in steps 401 and 402, After communication interference elimination, it is expressed as in, Indicates the residual uplink communication signal interference after interference elimination. is the decoding error of the u-th uplink user signal; Indicates the residual downlink communication signal interference after interference elimination; A high-precision perception signal can be demodulated based on the perception expectation signal and the perception interference signal received by the central processing unit CPU.

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