Hybrid beam forming method for communication perception integrated system

Abstract

The invention discloses a hybrid beam forming method for a communication perception integrated system, and belongs to the technical field of wireless communication. According to the invention, the problem of poor communication security of the traditional ISAC system is solved. According to the method, the sensing signal is endowed with an artificial noise function, so that the eavesdropping process of a potential eavesdropper is effectively interfered on the premise of not reducing the sensing precision, safety communication in a communication sensing integrated system is realized, and the problem of information leakage possibly caused by the direction of a sensing beam is solved; by means of the hybrid beam forming design of communication signals and sensing signals, high-precision target sensing can be achieved in a communication sensing integrated system, meanwhile, safe communication with a cooperative target is guaranteed, by designing a dynamic sub-array division method, the mapping relation between an antenna and a radio frequency chain can be adjusted according to the change of the safety rate, and the communication sensing efficiency is improved. Airspace resources are effectively utilized; and bidirectional matching of the safety rate and the beam forming design is realized. The method can be applied to beam forming of a communication perception integrated system.

Description

Technical Field

[0001] The present invention belongs to the technical field of wireless communications, and in particular relates to a hybrid beamforming method for a communication-awareness integrated system. Background Art

[0002] With the rapid development of information technology, next-generation mobile communication systems must not only provide high-quality communication services but also demand high-precision environmental perception capabilities for emerging applications such as smart industry, autonomous driving, and smart cities. Therefore, the application of integrated communication and perception (ISAC) in future mobile communication networks is of great significance. Unlike traditional systems that separate communication and perception functions, ISAC systems significantly improve spectrum utilization, energy efficiency, and hardware efficiency by sharing signal, hardware, and algorithm resources. This enables a deep integration of communication and perception functions, creating mutually beneficial synergies.

[0003] On the other hand, the broadcast nature of wireless signals also exposes communication systems to potential information leakage risks, particularly in ISAC systems. To improve sensing performance, the system's transmit beam is often designed to partially align with the sensing target to enhance target detection. However, this beam's directionality also means that potential eavesdroppers within the sensing beam's coverage area could potentially receive the communication signal, potentially leaking confidential information. Therefore, traditional ISAC systems suffer from poor communication security.

[0004] Therefore, in order to balance secure communication and perception accuracy, it is necessary to propose an effective hybrid beamforming design method for the security issues of integrated communication and perception systems. Summary of the Invention

[0005] The purpose of the present invention is to solve the problem of poor communication security of traditional ISAC systems and to propose a hybrid beamforming method for communication and perception integrated systems.

[0006] The present invention provides a technical solution to solve the above technical problems: a hybrid beamforming method for a communication-awareness integrated system, the method specifically comprising the following steps:

[0007] Step 1: The number of antennas of the base station in the communication and perception integrated system is recorded as , the number of RF chains is recorded as ;

[0008] The signal transmitted by the base station of the communication and perception integrated system is designed to be , and represent communication signals and perception signals respectively, To simulate beamforming, Digital beamforming for communication beams, Digital beamforming for sensing beams;

[0009] Step 2: Set the base station The transmitting antennas are randomly divided into sub-arrays, each of which has antennas, with the goal of minimizing the transmission power ;

[0010] Then for the optimization problem Solve and get the simulated beamforming and digital beamforming 、 ;

[0011] Step 3: Set the maximum number of iterations to , and initialize the number of iterations ;

[0012] Step 4: According to 、 and Performing antenna subarray division and obtaining analog beamforming corresponding to the antenna subarray division result;

[0013] Step 5: Solve the digital beamforming based on the analog beamforming corresponding to the antenna subarray division result;

[0014] Step 6: Determine whether it is satisfied ;

[0015] If satisfied , then the result obtained from the last iteration is taken as the final beamforming result;

[0016] If not satisfied , then let , return to step 4.

[0017] Furthermore, the optimization problem for:

[0018]

[0019]

[0020]

[0021]

[0022]

[0023]

[0024] in, express The conjugate transpose of represents the trace of the matrix, Indicates the safe rate, Indicates the lower limit of the safe rate, , , express The conjugate transpose of express The conjugate transpose of represents the perceived MSE, represents the upper limit of the perception MSE, express and are all positive semidefinite matrices, represents the rank of the matrix, Represents the identity matrix.

[0025] Furthermore, the safety rate The calculation method is:

[0026]

[0027] in, Indicates the SINR at the legitimate user, represents the SINR at the eavesdropper;

[0028]

[0029]

[0030] in, represents the channel between the legitimate user and the base station, express The conjugate transpose of represents the channel between the eavesdropper and the base station, express The conjugate transpose of represents the noise variance of the channel between the legitimate user and the base station, represents the noise variance of the channel between the eavesdropper and the base station.

[0031] Furthermore, the perception MSE is:

[0032]

[0033] in, Indicates the number of sampling angles, Indicates the Sampling angles, represents the steering vector of the antenna array, express The conjugate transpose of represents the covariance matrix of the transmitted signal, represents an ideal square wave waveform, Indicates taking the absolute value;

[0034]

[0035]

[0036] in, represents the base of natural logarithms, represents the imaginary unit, represents the antenna spacing, is the wavelength, and the superscript T indicates the transpose of the matrix;

[0037]

[0038] in, represents the beam width, Indicates the target angular position.

[0039] Furthermore, the optimization problem Solve and get the simulated beamforming and digital beamforming 、 ; The specific process is:

[0040] Step 2.1: Establish an optimization problem for solving analog beamforming :

[0041]

[0042]

[0043]

[0044] in, Indicates the The beamforming vector corresponding to the RF chain, express The elements, Indicates the The channel between the sub-array corresponding to each RF chain and the legitimate user, represents a block diagonal matrix;

[0045] Step 22: Optimization Problem Solve and get the simulated beamforming ;

[0046] Steps 2 and 3: Based on analog beamforming Get digital beamforming and .

[0047] Furthermore, in step 22, the simulated beamforming Specifically:

[0048]

[0049] in, express angle.

[0050] Furthermore, in step 22, the simulated beamforming The process is:

[0051] Step 221: Define a set of quantized phase sets :

[0052]

[0053] in, Indicates the number of quantization bits;

[0054] Step 222: Establish an optimization problem for analog beamforming design :

[0055]

[0056]

[0057] Step 2, 2, 3. Use phase rotation method to optimize the problem Solve it and get:

[0058]

[0059] in, express The elements, express angle, Indicates rounding down. is the minimum resolution of the phase shifter.

[0060] Furthermore, the specific process of steps two and three is as follows:

[0061] Step 231: Equivalent channel between legitimate users and base station Defined as:

[0062]

[0063] Equivalent channel between the eavesdropper and the base station Defined as:

[0064]

[0065] Step 232: Initialize auxiliary variable values , the auxiliary variable values ​​satisfy: ;

[0066] Step 233: Initialize the number of iterations ;

[0067] Step 2, 3, and 4: Use SDR algorithm to constrain Scaling, the equivalent channel and Substituting into the expression of safe rate, we get the safe rate constraint:

[0068]

[0069]

[0070]

[0071]

[0072] in, express The conjugate transpose of express The conjugate transpose of

[0073] Taylor expansion is performed on the right-hand exponential term of the obtained non-convex safety rate constraint, and iterative fitting is performed to obtain:

[0074]

[0075]

[0076] Then solve the satisfaction of ;

[0077] Step 2, 3, 5, according to Get the first The safe rate constraint of the first iteration is then substituted into the CVX solver to obtain the Digital beamforming after iterative optimization and ;

[0078] Step 236: Determine whether the iteration stop condition is met:

[0079]

[0080] in, is the set threshold;

[0081] If the iteration stop condition is met, the digital beamforming obtained in the last iteration is and As an optimization problem The resulting digital beamforming and , that is, we get and ;

[0082] If the iteration stop condition is not met, then , return to steps 2, 3, and 4.

[0083] Furthermore, the specific process of step 4 is as follows:

[0084] Step 4.1. From all Select the transmitting antenna with the highest channel gain to the legitimate user. Root transmitting antenna, and the selected Transmit antennas are allocated to subarray sets, then the candidate antenna set contains the remaining Root transmitting antenna; and The subarray set is denoted as ;

[0085] Step 42: Initialization ;

[0086] Step 4.3: Select the first antenna from the candidate antenna set. Root transmitting antenna;

[0087] Step 4. Calculate the Simulated beamforming when a root transmit antenna is added to each subarray set ; Then according to Calculate the The transmitting antenna is added to the The safe rate increment obtained when the subarrays are collected is:

[0088]

[0089] in, Indicates that the The transmitting antenna is added to the Subarray Collection The safe rate increment after harvest, is a collection of subarrays Provides safe speed, Indicates that the The root transmitting antenna joins the subarray set The safe rate after that;

[0090] Select the subarray set that maximizes the safe rate increment :

[0091]

[0092] The first The root transmitting antenna is added to the selected subarray set to obtain the Each subarray set after iterations , and the The root transmitting antenna is deleted from the candidate antenna set;

[0093] Step 45: Determine whether the candidate antenna set is empty;

[0094] If the candidate antenna set is empty, the final subarray set partitioning result is obtained, and then the final analog beamforming result is obtained based on the final subarray set partitioning result, and then the digital beamforming result is obtained based on the analog beamforming result;

[0095] If the candidate antenna set is not empty, let , return to step 43.

[0096] Furthermore, in the step 44, the first Simulated beamforming when a root transmit antenna is added to each subarray set ; The specific process is:

[0097]

[0098] in, Indicates the Subarrays are added to After the transmitting antenna, the The channel between the sub-array and the legitimate user.

[0099] The beneficial effects of the present invention are:

[0100] The present invention proposes a secure hybrid beamforming method for a communication-perception integrated system. By giving the perception signal an artificial noise function, the eavesdropping process of potential eavesdroppers is effectively interfered with without reducing the perception accuracy, thereby realizing secure communication in the communication-perception integrated system and solving the problem of information leakage that may be caused by the direction of the perception beam. By introducing a hybrid beamforming architecture and optimizing the transmission power, the hardware cost and energy consumption of the system are effectively reduced, and both resource overhead and system performance are taken into account. Through the hybrid beamforming design of communication signals and perception signals, high-precision target perception can be achieved in the communication-perception integrated system while ensuring secure communication with cooperative targets. By designing a dynamic subarray partitioning method, the mapping relationship between the antenna and the RF chain can be adjusted according to the channel state information, effectively utilizing spatial resources and realizing two-way matching between the channel state information and the beamforming design. BRIEF DESCRIPTION OF THE DRAWINGS

[0101] Figure 1 A system model of a hybrid beamforming method for a communication-awareness integrated system according to the present invention;

[0102] Figure 2 This is a structural diagram of the dynamic subarray used in the present invention;

[0103] Figure 3 This is a flow chart of the dynamic subarray partitioning method of the present invention;

[0104] Figure 4 This is a graph showing the relationship between transmit power requirements and safe rate;

[0105] Figure 5 is the relationship between the transmit power requirement and the MSE of the perceived beam pattern;

[0106] Figure 6 This is a graph showing the relationship between transmit power requirements and the number of PS quantization bits.

[0107] Figure 7 This is a transmission beam pattern diagram that can be achieved by the present invention. DETAILED DESCRIPTION

[0108] Specific embodiment 1: This embodiment describes a hybrid beamforming method for a communication-awareness integrated system, the method specifically comprising the following steps:

[0109] Step 1: Figure 1 As shown in the figure, in the communication and perception integrated system, there is a legitimate user communicating with the base station, a target to be perceived, and a potential eavesdropper who attempts to steal the communication information between the base station and the legitimate user. Both the legitimate user and the eavesdropper in the system are single-antenna devices. The number of antennas of the base station in the communication and perception integrated system is denoted as , the number of RF chains is recorded as ;

[0110] The signal transmitted by the base station of the communication and perception integrated system is designed to be , and Represent independent communication signals and perception signals respectively, and satisfy and To achieve secure communication, At the same time, it also acts on the eavesdropper to realize the function of AN. By giving the perception signal the function of artificial noise (AN), while realizing the perception of the target, part of it is directed to the eavesdropper to interfere with the eavesdropping process. and can be used to perceive the target in the system, but only Can be used to carry confidential communication information. To simulate beamforming, Digital beamforming for communication beams, Digital beamforming for sensing beams;

[0111] The communication signal is , the dedicated perception signal is , It can be used to communicate with legitimate users and sense specific targets at the same time. It can only be used to sense specific targets and interfere with the eavesdropper's eavesdropping process;

[0112] Step 2: Set the base station The transmitting antennas are randomly divided into sub-arrays, each of which has antennas, with the goal of minimizing the transmission power ;

[0113] Then for the optimization problem Solve and get the simulated beamforming and digital beamforming 、 ;

[0114] Step 3: Set the maximum number of iterations to , and initialize the number of iterations ;

[0115] Step 4: According to 、 and Perform antenna subarray division (it should be noted that only in the first iteration, 、 and Using the calculation results in step 2, starting from the second iteration, the optimization results obtained in steps 4 and 5 of the previous iteration are used to obtain simulated beamforming corresponding to the antenna subarray division results;

[0116] Step 5: Solve the digital beamforming based on the analog beamforming corresponding to the antenna subarray division result and (The solution method is the same as steps 2 and 3);

[0117] Step 6: Determine whether it is satisfied ;

[0118] If satisfied , then the result obtained from the last iteration is taken as the final beamforming result;

[0119] If not satisfied , then let , return to step 4.

[0120] In the perception part, the echo signal reflected by the target received by the base station of the communication perception integrated system is:

[0121]

[0122] in, represents the round-trip channel coefficient related to path loss and RCS, Represents the additive white Gaussian noise at the receiver of the communication-sensing integrated system.

[0123] Specific implementation method 2: This implementation method is different from the specific implementation method 1 in that the optimization problem for:

[0124]

[0125]

[0126]

[0127]

[0128]

[0129]

[0130] in, express The conjugate transpose of represents the trace of the matrix, Indicates the safe rate, Indicates the lower limit of the safe rate, , , express The conjugate transpose of express The conjugate transpose of represents the perceived MSE, represents the upper limit of the perception MSE, express and are all positive semidefinite matrices, represents the rank of the matrix, Represents the identity matrix.

[0131] Other steps and parameters are the same as those in the first embodiment.

[0132] Specific embodiment 3: This embodiment differs from specific embodiment 2 in that the security rate is used to measure the security communication performance. The calculation method is:

[0133]

[0134] in, satisfy: ; Indicates the SINR at the legitimate user, represents the SINR at the eavesdropper;

[0135]

[0136]

[0137] in, represents the channel between the legitimate user and the base station, express The conjugate transpose of represents the channel between the eavesdropper and the base station, express The conjugate transpose of represents the noise variance of the channel between the legitimate user and the base station, represents the noise variance of the channel between the eavesdropper and the base station.

[0138] Other steps and parameters are the same as those in the second embodiment.

[0139] The extended Saleh-Valenzuela model is used to model the channels between legitimate users and the communication-aware integrated transmission base station, and between eavesdroppers and the communication-aware integrated transmission base station:

[0140]

[0141] in, Indicates the The channel gain of each path, Indicates the number of paths, Indicates the Angle of departure (AoD) of each path.

[0142] Specific embodiment 4: This embodiment differs from specific embodiment 3 in that, in order to effectively measure the beamforming design of the perception part, the MSE between the perception beam pattern and the ideal beam pattern is used as the performance indicator, where the perception beam pattern is defined as the transmission signal at the sampling angle The gain at , the perceptual MSE between the perceived beam pattern and the ideal beam pattern is:

[0143]

[0144] in, Indicates the number of sampling angles, Indicates the Sampling angles, represents the steering vector of the antenna array, express The conjugate transpose of represents the covariance matrix of the transmitted signal, represents an ideal square wave waveform, Indicates taking the absolute value;

[0145]

[0146]

[0147] in, represents the base of natural logarithms, represents the imaginary unit, represents the antenna spacing, is the wavelength, and the superscript T indicates the transpose of the matrix;

[0148]

[0149] in, represents the beam width, Indicates the target angular position.

[0150] Other steps and parameters are the same as those in the third embodiment.

[0151] Specific embodiment 5: This embodiment differs from specific embodiment 4 in that the semi-definite relaxation (SDR) and continuous convex approximation (SCA) algorithms are used to solve the non-convex optimization problem of the original design digital beamforming. Solve and get the simulated beamforming and digital beamforming 、 ; The specific process is:

[0152] Step 2.1: Establish an optimization problem for solving analog beamforming :

[0153]

[0154]

[0155]

[0156] in, Indicates the The beamforming vector corresponding to the RF chain, express The elements, Indicates the The channel between the sub-array corresponding to each RF chain and the legitimate user, represents a block diagonal matrix;

[0157] Step 22: Optimization Problem Solve and get the simulated beamforming ;

[0158] Steps 2 and 3: Based on analog beamforming Get digital beamforming and .

[0159] Other steps and parameters are the same as those in the fourth embodiment.

[0160]

[0161] express The Elements to elements.

[0162] This implementation decouples digital beamforming from hybrid beamforming. First, analog beamforming is performed with the goal of maximizing the gain provided by the transmit antenna array to legitimate users. The analog beamforming design process treats each subarray as a directional antenna and adjusts the phase of each subarray to enhance the received signal strength at the legitimate user. Then, based on the analog beamforming, the digital beamforming of the communication beam is designed with the goal of minimizing the transmit power and the constraints of secure communication performance and perception performance. Digital beamforming with perceptual / artificial noise beamforming .

[0163] Specific implementation method 6: This implementation method is different from the specific implementation method 5 in that the optimization problem The optimal solution is that the beam of each subarray is aligned with the direction of the legitimate user. In step 2, the simulated beamforming Specifically:

[0164]

[0165] in, express angle.

[0166] Other steps and parameters are the same as those in the fifth embodiment.

[0167] Specific embodiment seven: This embodiment differs from specific embodiment five in that in step 22, the simulated beamforming The process is:

[0168] Step 221: Define a set of quantized phase sets :

[0169]

[0170] in, Indicates the number of quantization bits (i.e., the number of binary bits used by a finite-resolution PS (phase shifter) to represent the phase state);

[0171] Step 222: Establish an optimization problem for analog beamforming design :

[0172]

[0173]

[0174] Step 2, 2, 3. Use phase rotation method to optimize the problem Solve it and get:

[0175]

[0176] in, express The elements, express angle, Indicates rounding down. is the minimum resolution of the phase shifter.

[0177] Other steps and parameters are the same as those in the fifth embodiment.

[0178] Specific embodiment eight: This embodiment differs from specific embodiment six or seven in that the specific processes of steps two and three are as follows:

[0179] Step 231: Equivalent channel between legitimate users and base station Defined as:

[0180]

[0181] Equivalent channel between the eavesdropper and the base station Defined as:

[0182]

[0183] Step 232: Initialize auxiliary variable values , the auxiliary variable values ​​satisfy: ;

[0184] Step 233: Initialize the number of iterations ;

[0185] Step 2, 3, and 4: Use SDR algorithm to constrain Scaling, the equivalent channel and Substitute the expression of safety rate, after simple mathematical derivation, and introduce a series of auxiliary variables , and obtain the safe rate constraint:

[0186]

[0187]

[0188]

[0189]

[0190] in, express The conjugate transpose of express The conjugate transpose of

[0191] Taylor expansion is performed on the exponential terms on the right side of the obtained non-convex safety rate constraint (i.e., the second and third inequalities above), and iterative fitting is performed to obtain:

[0192]

[0193]

[0194] Then solve the inequality obtained by fitting to satisfy of ;

[0195] Step 2, 3, 5, according to Get the first The safe rate constraint of the first iteration is then substituted into the CVX solver to obtain the Digital beamforming after iterative optimization and ;

[0196] Step 236: Determine whether the iteration stop condition is met:

[0197]

[0198] in, is the set threshold;

[0199] If the iteration stop condition is met, the digital beamforming obtained in the last iteration is and As an optimization problem The resulting digital beamforming and , that is, we get and ;

[0200] If the iteration stop condition is not met, then , return to steps 2, 3, and 4.

[0201] Other steps and parameters are the same as those in specific implementation manner six or seven.

[0202] Specific implementation method nine: Combination Figure 2 and Figure 3 This embodiment differs from the eighth embodiment in that the specific process of step four is as follows:

[0203] Step 4.1: The transmitting base station adopts a dynamic sub-array architecture and designs the sub-array division. In order to ensure that the antenna set in each sub-array is not empty, Select the transmitting antenna with the highest channel gain to the legitimate user. Root transmitting antenna, and the selected Transmit antennas are allocated to subarray sets, then the candidate antenna set contains the remaining Root transmitting antenna; and The subarray set is denoted as ;

[0204] Step 42: Initialization ;

[0205] Step 4.3: Select the first antenna from the candidate antenna set. Root transmitting antenna;

[0206] Step 4. Calculate the Simulated beamforming when a root transmit antenna is added to each subarray set ; Then according to Calculate the The transmitting antenna is added to the The safe rate increment obtained when the subarrays are collected is:

[0207] It should be noted that: For example, the initial security rate is calculated based on the analog and digital beamforming results obtained in step 2. When the first iteration adds the first transmitting antenna in the candidate antenna set to the first When there are a set of sub-arrays, according to And the digital beamforming result obtained in step 2 is calculated by adding the first transmitting antenna to the The safe rate when the subarrays are combined is calculated by subtracting the latter from the former to get the safe rate increment, and the new safe rate obtained by the subarray after adding the first transmitting antenna to the subarray is saved. For example, according to And the digital beamforming result obtained in step 2 is calculated by adding the second transmitting antenna to the first The safe rate when the subarray set is set, and the maximum safe rate increment brought by assigning the second antenna in the candidate antenna set is calculated. Then, the new safe rate obtained by adding the second transmitting antenna to the subarray is saved. And so on. It can be seen that the digital beamforming used for safe rate calculation remains unchanged in the same iteration process.

[0208]

[0209] in, Indicates that the The transmitting antenna is added to the Subarray Collection The safe rate increment after harvest, is a collection of subarrays Provides safe speed, Indicates that the The root transmitting antenna joins the subarray set The safe rate after that;

[0210] Select the subarray set that maximizes the safe rate increment :

[0211]

[0212] The first The root transmitting antenna is added to the selected subarray set to obtain the Each subarray set after iterations , and the The root transmitting antenna is deleted from the candidate antenna set;

[0213] Step 45: Determine whether the candidate antenna set is empty;

[0214] If the candidate antenna set is empty, a final subarray set partitioning result is obtained, and then a final analog beamforming result (calculated using the method of specific implementation method six) is obtained based on the final subarray set partitioning result, and then a digital beamforming result is obtained based on the analog beamforming result;

[0215] The analog beamforming results and digital beamforming results updated in the current iteration will be used in the next iteration process;

[0216] If the candidate antenna set is not empty, let , return to step 43.

[0217] Other steps and parameters are the same as those in the eighth embodiment.

[0218] Specific embodiment ten: This embodiment differs from the specific embodiment nine in that in step four, the first Simulated beamforming when a root transmit antenna is added to each subarray set ; The specific process is:

[0219]

[0220] in, Indicates the Subarrays are added to After the transmitting antenna, the The channel between the sub-array and the legitimate user.

[0221] Other steps and parameters are the same as those in the ninth embodiment.

[0222] It should be noted that for each antenna allocation process in the same iterative process, The value of remains unchanged and is always the optimization result of the previous iteration. Figure 2This is a diagram of the dynamic subarray structure used in the present invention. The dynamic subarray architecture can use a low-power switching network to achieve antenna selection, so that each RF chain can be connected to a different subarray, realizing flexible beamforming design. Since the subarray division speed is usually much slower than the channel change speed, the system does not need to frequently adjust the subarray division, making it efficient and feasible to implement a dynamic subarray architecture in a communication-aware integrated base station. The present invention dynamically adjusts the connection relationship between the antenna and the RF chain according to the CSI, which can more effectively utilize the spatial freedom provided by the hybrid beamforming architecture, so that the beamforming design and the channel state information are bidirectionally adapted.

[0223] Simulation studies:

[0224] The present invention proposes a secure hybrid beamforming method for a communication-aware integrated system, wherein the simulation parameters are selected as follows: carrier frequency is 28 GHz, path gain is 28 GHz, and the path gain is 28 GHz. Obeying a complex Gaussian distribution with a mean of 0 and a variance of 1, AoD obeys Uniform distribution on the number of paths , antenna spacing The noise variance at the communication and sensing integrated transmitting base station, legitimate user and eavesdropper receiver is 10 -3 .

[0225] The transformation problem was solved using the CVX toolbox, and Monte Carlo simulation was used to verify the performance of the proposed method. A method that did not use the perception signal as artificial noise, as well as a beamforming method that designed both the communication signal and the perception signal separately, were used as baselines for comparison with the proposed method.

[0226] Figure 4 is the relationship between the transmission power requirement and the safety rate, Figure 4 It can be seen that when the system's demand for a safe rate increases, the transmitter has to increase the transmission power to enhance the signal security. Compared with the baseline method, the method of the present invention can achieve the same safe rate at a lower transmission power. Figure 5 is the relationship between the transmit power requirement and the perceived beam pattern MSE, given by Figure 5 It can be seen that as the perception beam pattern error threshold gradually increases, the required transmission power of the system also decreases. Compared with the baseline method, the proposed method can achieve the same perception target accuracy at a lower transmission power; Figure 6 is the relationship between the transmit power requirement and the number of PS quantization bits, Figure 6It can be seen that when the number of PS quantization bits is low, the finite resolution PS requires higher transmission power than the infinite resolution PS case. As the number of quantization bits increases, the transmission power required by the finite resolution PS gradually decreases and approaches the infinite resolution PS case.

[0227] Figure 7 This is the transmission beam pattern diagram that can be achieved by the present invention. Figure 7 It can be seen that the transmitted beams are mainly directed to the angle of the sensing target. A peak appears at , indicating that the hybrid beamforming structure can achieve accurate perception performance in the communication and perception integrated system. Compared with the baseline method, the proposed method can achieve higher gain at the target location and has stronger target perception capability under the same conditions.

[0228] The above examples are merely illustrative of the calculation model and process of the present invention and are not intended to limit the embodiments of the present invention. Persons skilled in the art will readily appreciate that other variations or modifications based on the above description are possible. This list of embodiments is not exhaustive; however, any obvious variations or modifications derived from the technical solution of the present invention remain within the scope of protection of the present invention.

Claims

1. A hybrid beamforming method for a communication-awareness integrated system, characterized in that: The method specifically comprises the following steps: Step 1: The number of antennas of the base station in the communication and perception integrated system is recorded as , the number of RF chains is recorded as ; The signal transmitted by the base station of the communication and perception integrated system is designed to be , and represent communication signals and perception signals respectively, To simulate beamforming, Digital beamforming for communication beams, Digital beamforming for sensing beams; Step 2: Set the base station The transmitting antennas are randomly divided into sub-arrays, each of which has antennas, with the goal of minimizing the transmission power ; Then for the optimization problem Solve and get the simulated beamforming and digital beamforming 、 ; Step 3: Set the maximum number of iterations to , and initialize the number of iterations ; Step 4: According to 、 and Performing antenna subarray division and obtaining analog beamforming corresponding to the antenna subarray division result; Step 5: Solve the digital beamforming based on the analog beamforming corresponding to the antenna subarray division result; Step 6: Determine whether it is satisfied ; If satisfied , then the result obtained from the last iteration is taken as the final beamforming result; If not satisfied , then let , return to step 4.

2. The hybrid beamforming method for a communication-awareness integrated system according to claim 1, characterized in that: The optimization problem for: in, express The conjugate transpose of represents the trace of the matrix, Indicates the safe rate, Indicates the lower limit of the safe rate, , , express The conjugate transpose of express The conjugate transpose of represents the perceived MSE, represents the upper limit of the perception MSE, express and are all positive semidefinite matrices, represents the rank of the matrix, Represents the identity matrix.

3. The hybrid beamforming method for a communication-awareness integrated system according to claim 2, wherein: The safe rate The calculation method is: in, Indicates the SINR at the legitimate user, represents the SINR at the eavesdropper; in, represents the channel between the legitimate user and the base station, express The conjugate transpose of represents the channel between the eavesdropper and the base station, express The conjugate transpose of represents the noise variance of the channel between the legitimate user and the base station, represents the noise variance of the channel between the eavesdropper and the base station.

4. The hybrid beamforming method for a communication-awareness integrated system according to claim 3, characterized in that: The perception MSE is: in, Indicates the number of sampling angles, Indicates the Sampling angles, represents the steering vector of the antenna array, express The conjugate transpose of represents the covariance matrix of the transmitted signal, represents an ideal square wave waveform, Indicates taking the absolute value; in, represents the base of natural logarithms, represents the imaginary unit, represents the antenna spacing, is the wavelength, and the superscript T indicates the transpose of the matrix; in, represents the beam width, Indicates the target angular position.

5. The hybrid beamforming method for a communication-awareness integrated system according to claim 4, characterized in that: The optimization problem Solve and get the simulated beamforming and digital beamforming 、 ; The specific process is: Step 2.1: Establish an optimization problem for solving analog beamforming : in, Indicates the The beamforming vector corresponding to the RF chain, express The elements, Indicates the The channel between the sub-array corresponding to each RF chain and the legitimate user, represents a block diagonal matrix; Step 22: Optimization Problem Solve and get the simulated beamforming ; Steps 2 and 3: Based on analog beamforming Get digital beamforming and .

6. The hybrid beamforming method for a communication-awareness integrated system according to claim 5, characterized in that: In step 22, simulate beamforming Specifically: in, express angle.

7. The hybrid beamforming method for a communication-awareness integrated system according to claim 5, characterized in that: In step 22, simulate beamforming The process is: Step 221: Define a set of quantized phase sets : in, Indicates the number of quantization bits; Step 222: Establish an optimization problem for analog beamforming design : Step 2, 2, 3. Use phase rotation method to optimize the problem Solve it and get: in, express The elements, express angle, Indicates rounding down. is the minimum resolution of the phase shifter.

8. The hybrid beamforming method for a communication-awareness integrated system according to claim 6 or 7, characterized in that: The specific process of steps two and three is as follows: Step 231: Equivalent channel between legitimate users and base station Defined as: Equivalent channel between the eavesdropper and the base station Defined as: Step 232: Initialize auxiliary variable values , the auxiliary variable values ​​satisfy: ; Step 233: Initialize the number of iterations ; Step 2, 3, and 4: Use SDR algorithm to constrain Scaling, the equivalent channel and Substituting into the expression of safe rate, we get the safe rate constraint: in, express The conjugate transpose of express The conjugate transpose of Taylor expansion is performed on the right-hand exponential term of the obtained non-convex safety rate constraint, and iterative fitting is performed to obtain: Then solve the satisfaction of ; Step 2, 3, 5, according to Get the first The safe rate constraint of the first iteration is then substituted into the CVX solver to obtain the Digital beamforming after iterative optimization and ; Step 236: Determine whether the iteration stop condition is met: in, is the set threshold; If the iteration stop condition is met, the digital beamforming obtained in the last iteration is and As an optimization problem The resulting digital beamforming and , that is, we get and ; If the iteration stop condition is not met, then , return to steps 2, 3, and 4.

9. The hybrid beamforming method for a communication-awareness integrated system according to claim 8, characterized in that: The specific process of step 4 is as follows: Step 4.

1. From all Select the transmitting antenna with the highest channel gain to the legitimate user. Root transmitting antenna, and the selected Transmit antennas are allocated to subarray sets, then the candidate antenna set contains the remaining Root transmitting antenna; and The subarray set is denoted as ; Step 42: Initialization ; Step 4.3: Select the first antenna from the candidate antenna set. Root transmitting antenna; Step 4. Calculate the Simulated beamforming when a root transmit antenna is added to each subarray set ; Then according to Calculate the The transmitting antenna is added to the The safe rate increment obtained when the subarrays are collected is: in, Indicates that the The transmitting antenna is added to the Subarray Collection The safe rate increment after harvest, is a collection of subarrays Provides safe speed, Indicates that the The root transmitting antenna joins the subarray set The safe rate after that; Select the subarray set that maximizes the safe rate increment : The first The root transmitting antenna is added to the selected subarray set to obtain the Each subarray set after iterations , and the The root transmitting antenna is deleted from the candidate antenna set; Step 45: Determine whether the candidate antenna set is empty; If the candidate antenna set is empty, the final subarray set partitioning result is obtained, and then the final analog beamforming result is obtained based on the final subarray set partitioning result, and then the digital beamforming result is obtained based on the analog beamforming result; If the candidate antenna set is not empty, let , return to step 43.

10. The hybrid beamforming method for a communication-awareness integrated system according to claim 9, characterized in that: In the step 44, the first Simulated beamforming when a root transmit antenna is added to each subarray set ; The specific process is: in, Indicates the Subarrays are added to After the transmitting antenna, the The channel between the sub-array and the legitimate user.

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