A wideband system transceiving joint design method based on full-band space regulation

Abstract

This invention discloses a joint design method for broadband system transceivers based on full-band spatial domain control. The method includes: establishing a broadband system model; segmenting the full-band of the broadband system; constructing transmit and receive signal models for each sub-band; defining spatial domain characteristic indices for the transmit signal and corresponding receive beamforming vector of each sub-band; constructing corresponding performance constraints according to specific application requirements; constructing a joint optimization problem using the full-band transmit signal and corresponding receive beamforming vector as optimization variables; optimizing the consistency of the full-band spatial domain indices under specific performance constraints; and solving the joint optimization problem to obtain the joint design result of the transmit signal and receive beamforming vector. This invention can be widely applied to various wireless systems that require maintaining broadband spatial domain consistency, such as radar systems, communication systems, and integrated sensing systems, and can effectively solve the model mismatch problem of narrowband design methods in broadband scenarios.

Description

Technical Field

[0001] This invention relates to the field of broadband system design, and in particular to a method for the joint design of broadband system transceivers based on full-band spatial domain control. Background Technology

[0002] Broadband systems have been widely applied in numerous fields, including radar detection, wireless communication, integrated sensing and communication, navigation and positioning, and electronic warfare. Broadband signals offer advantages such as high resolution, large information capacity, and strong anti-interference capabilities, making them a key technological feature of modern wireless systems. In these broadband systems, the spatial processing capability of the antenna array is crucial to system performance. Beamforming technology, by adjusting the amplitude and phase of each element in the antenna array, enables the system to form a desired spatial response in a specific direction, thereby achieving signal enhancement, interference suppression, or target detection.

[0003] However, most existing spatial processing methods for broadband systems are based on the narrowband assumption, which assumes that the signal bandwidth is much smaller than the carrier frequency, thus ignoring the impact of frequency on spatial response. In practical broadband systems, when the relative bandwidth exceeds 1%, the propagation characteristics of different frequency components in the array differ significantly, causing the beam pattern to change with frequency, manifesting as beam broadening, pointing offset, and increased sidelobes. If the narrowband design method is still used, the spatial performance of the actual system will deviate significantly from the design expectations, resulting in beam distortion, gain loss, increased angle estimation errors, and decreased communication reliability. This model mismatch problem is particularly prominent in scenarios such as 5G-NR (relative bandwidth can reach 22.2%) and millimeter-wave radar (relative bandwidth often exceeds 1%), severely restricting the practical application of the system in broadband scenarios. In addition, most existing studies only consider unidirectional optimization at the transmitter or receiver, failing to fully utilize the freedom of joint transmitter-receiver design. Furthermore, most designs are tailored to specific application scenarios (such as radar or communication), lacking a unified design framework applicable to various broadband systems.

[0004] In conclusion, considering the importance of broadband modeling for practical broadband systems and the current lack of effective design schemes to maintain full-band spatial consistency, it is necessary to study a transceiver joint design method that can fully consider the characteristics of broadband signals in order to make up for the shortcomings of existing technologies. Summary of the Invention

[0005] Purpose of the Invention: Most existing spatial processing methods for broadband systems are based on the narrowband assumption, which assumes that the signal bandwidth is much smaller than the carrier frequency and that the frequency's influence on the spatial response is negligible. This leads to problems such as model mismatch and beamforming pattern distortion in practical broadband applications, resulting in a significant deviation between the system's spatial performance and design expectations. This invention provides a broadband system transceiver co-design method based on full-band spatial control, offering an effective transceiver co-design framework for broadband systems such as radar detection, wireless communication, sensing integration, navigation and positioning, and electronic countermeasures.

[0006] Technical solution: To achieve the above-mentioned objectives, the present invention adopts the following technical solution:

[0007] A method for joint design of broadband system transceiver based on full-band spatial control includes the following steps:

[0008] Establish a broadband system model, segment the entire frequency band of the broadband system, and construct the transmission and reception signal models for each sub-band;

[0009] For each sub-band, define the spatial characteristics indexes for the transmitted signal and the corresponding received beamforming vector; and construct corresponding performance constraints according to specific application requirements.

[0010] Using the full-band transmitted signal and the corresponding received beamforming vector as optimization variables, a joint optimization problem is constructed to optimize the consistency of the full-band spatial domain indicators under specific performance constraints.

[0011] Solving the joint optimization problem yields the joint design results of the transmitted signal and the received beamforming vector.

[0012] Furthermore, a broadband system model is established, the entire frequency band of the broadband system is segmented, and the transmit and receive signal models for each sub-band are constructed, including:

[0013] Assume the carrier frequency of the broadband system is The full bandwidth of the broadband system is divided into Sub-band, the first The center frequency of each sub-band is Assuming the first The first sub-band The number of signal transmission points is ;

[0014] Assuming the broadband system has One transmitting antenna and The receiving antenna, for the first Each sub-band defines the space-frequency beam steering vector at the transmitting and receiving ends. and , respectively defined as and ,in Indicates direction, Represents the sub-band index, defining the first... Sub-band receive beamforming vector Then in The received signal in this sub-band of the direction is ,in .

[0015] Furthermore, for each sub-band's transmitted signal and corresponding received beamforming vector, spatial domain characteristic indices are defined, including:

[0016] No. The spatial-frequency beam pattern of each sub-band is as follows:

[0017]

[0018] Define the ideal beam pattern The ideal beam pattern is set according to specific application requirements, including any of the following: having a prominent peak in the desired detection direction, or having narrow beam characteristics to meet measurement accuracy requirements, or having wide beam characteristics to expand the detection range, or forming a beam notch in a specific direction to avoid interference.

[0019] Define a metric for spatial consistency by summing the errors between the beam pattern and the ideal beam pattern in each sub-band:

[0020] .

[0021] Furthermore, based on specific application requirements, corresponding performance constraints are constructed. The performance constraints are used to ensure the system's performance under specified tasks. Their specific form depends on the system's functional positioning and application scenario. When the system needs to ensure communication functions, the performance constraints include any of the following: signal-to-interference-plus-noise ratio (SINR) constraints, bit error rate (BER) constraints, mutual information constraints, or symbol-by-symbol constraints based on the geometric distribution of signals on the constellation diagram. When the system needs to ensure sensing functions, the performance constraints include any of the following: radar ambiguity function constraints, Cramer-Rao lower bound constraints, detection probability constraints, or parameter estimation accuracy constraints.

[0022] Furthermore, with full-band transmission signals and the corresponding receive beamforming vector To optimize the variables, a joint optimization problem is constructed, under specific performance constraints. Below, to optimize the consistency of spatial indicators across the entire frequency band, the joint optimization problem is defined as:

[0023]

[0024] in, Its function is to extract the first frequency band signal from the full-band signal. The signal is in a sub-band, and the second constraint limits the total power of the transmitted signal. The first constraint represents the preset total power value of the transmitted signal; the second constraint represents the power limit of the received beamforming vector.

[0025] Furthermore, by solving the joint optimization problem, the transmitted signal is obtained. With the received beamforming vector The solution method for the joint optimization problem is determined according to its specific form, including any of the following: using an alternating optimization method to decompose the original problem into several sub-problems and solve them alternately, or integrating multiple optimization variables into one variable and solving it using a convex approximation method.

[0026] This invention also provides a broadband system transceiver joint design system based on full-band spatial domain modulation, comprising:

[0027] The system model building module is used to build a broadband system model, divide the full frequency band of the broadband system into segments, and build the transmit and receive signal models for each sub-band.

[0028] The constraint construction module is used to define spatial domain characteristic indicators for the transmitted signal and the corresponding received beamforming vector of each sub-band; and to construct corresponding performance constraints according to specific application requirements.

[0029] The optimization problem establishment module is used to construct a joint optimization problem with the full-band transmitted signal and the corresponding received beamforming vector as optimization variables, and optimize the consistency of the full-band spatial domain indicators under specific performance constraints.

[0030] The problem-solving module is used to solve the joint optimization problem and obtain the joint design results of the transmitted signal and the received beamforming vector.

[0031] The present invention also provides an electronic device, characterized in that it includes: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, and the programs, when executed by the processors, implement the broadband system transceiver joint design method based on full-band spatial domain modulation as described above.

[0032] The present invention also provides a computer-readable storage medium having a computer program stored thereon, characterized in that, when the computer program is executed by a processor, it implements the broadband system transceiver joint design method based on full-band spatial domain control as described above.

[0033] The present invention also provides a computer program product, including a computer program, characterized in that, when the computer program is executed by a processor, it implements the broadband system transceiver joint design method based on full-band spatial domain control as described above.

[0034] Compared with the prior art, the present invention has the following advantages: (1) It adopts broadband signal modeling, which breaks through the limitations of the traditional narrowband assumption. The full frequency band is divided into several sub-bands, and the transmitted signal and the corresponding received beamforming vector of each sub-band are jointly designed. The differences in the propagation characteristics of different frequency components in the array are fully considered, which can accurately reflect the physical characteristics of the large bandwidth signals of broadband systems such as 5G-NR and millimeter-wave radar, and fundamentally avoid the spatial performance loss caused by model mismatch. (2) The full frequency band transmitted signal and the received beamforming vector of each sub-band are designed in a collaborative manner. Independent beamforming vectors are designed for different sub-bands at the receiving end, which makes full use of the degree of freedom of the joint design of transmitting and receiving. With the consistency of the spatial index of the full frequency band as the optimization goal, joint optimization is carried out under the performance constraints of specific application requirements to eliminate the distortion effect of broadband effect on beamforming, and improve the spatial performance of each sub-band while ensuring the specific performance of the system. (3) It has broad application adaptability, and has established a unified broadband system transceiver joint design framework. It does not depend on specific application scenarios or signal standards, and can be flexibly adapted to various broadband systems such as radar detection, wireless communication, integrated sensing, navigation and positioning, and electronic countermeasures. It has good versatility and scalability. Attached Figure Description

[0035] Figure 1 This is a flowchart illustrating the overall process of the method of the present invention.

[0036] Figure 2 This is a detailed flowchart of an embodiment of the present invention.

[0037] Figure 3 This represents the beam pattern of all sub-bands under the traditional narrowband model.

[0038] Figure 4 This is the beam pattern of all sub-bands under the broadband model proposed in this invention.

[0039] Figure 5 For communication constraints The distribution of communication signals on the constellation diagram.

[0040] Figure 6 For communication constraints The distribution of communication signals on the constellation diagram.

[0041] Figure 7 For different signal and channel models, the objective function value varies with communication constraints. A changing curve.

[0042] Figure 8 For different signal and channel models, the symbol error rate varies with communication constraints. A changing curve. Detailed Implementation

[0043] To provide a clearer understanding of the features and advantages of the technical solution of the present invention, the composition and implementation of the specific solution are described below in conjunction with the accompanying drawings.

[0044] Example 1

[0045] like Figure 1 As shown, this embodiment discloses a broadband system transceiver joint design method based on full-band spatial domain control, the main steps of which include:

[0046] S101, Establish a broadband system model, segment the entire frequency band of the broadband system, and construct the transmission and reception signal models for each sub-band;

[0047] Assume the carrier frequency of the broadband system is The full bandwidth of the broadband system is divided into... Sub-band, the first The center frequency of each sub-band is For multi-carrier systems such as Orthogonal Frequency Division Multiplexing (OFDM), the system itself has frequency band divisions, with each sub-band corresponding to a subcarrier or sub-band. Overlap between sub-bands is allowed but orthogonality must be maintained. For broadband systems without naturally divided frequency bands, the sub-bands are artificially defined frequency band divisions. Assume the... The first sub-band The number of signal transmission points is .

[0048] Assuming the broadband system has One transmitting antenna and The receiving antenna. For the first... Each sub-band defines the space-frequency beam steering vector at the transmitting and receiving ends. and , respectively defined as and ,in Indicates direction, This represents the sub-band index. Define the first... Sub-band receive beamforming vector Then in The received signal in this sub-band of the direction is ,in .

[0049] S102, for the transmitted signal and the corresponding received beamforming vector of each sub-band, define the spatial domain characteristics index; construct the corresponding performance constraints according to specific application requirements;

[0050] No. The spatial-frequency beam pattern of each sub-band is as follows:

[0051]

[0052] Define the ideal beam pattern The ideal beam pattern is set according to specific application requirements, including but not limited to: having a prominent peak in the desired detection direction, or having narrow beam characteristics to meet measurement accuracy requirements, or having wide beam characteristics to expand the detection range, or forming a beam notch in a specific direction to avoid interference.

[0053] Define a metric for spatial consistency by summing the errors between the beam pattern and the ideal beam pattern in each sub-band:

[0054]

[0055] Develop corresponding performance constraints based on specific application requirements. The performance constraints are used to ensure the system's performance under specific tasks, and their specific form depends on the system's functional positioning and application scenario. When the system needs to ensure communication functions, the performance constraints include, but are not limited to, constraints on the signal-to-interference-plus-noise ratio (SIR) of the received signal, bit error rate (BER) constraints, mutual information constraints, or symbol-by-symbol constraints based on the geometric distribution of the signal on the constellation diagram. When the system needs to ensure sensing functions, the performance constraints include, but are not limited to, radar ambiguity function constraints, Cramer-Rao lower bound constraints, detection probability constraints, or parameter estimation accuracy constraints.

[0056] S103 uses the full-band transmitted signal and the corresponding received beamforming vector as optimization variables to construct a joint optimization problem, and optimizes the consistency of the full-band spatial domain indicators under specific performance constraints.

[0057] Transmit signals in the full frequency band and the corresponding receive beamforming vector To optimize the variables, a joint optimization problem is constructed, under specific performance constraints. Next, optimize the consistency of spatial indicators across the entire frequency band. The joint optimization problem is defined as:

[0058]

[0059] in, Its function is to extract the first frequency band signal from the full-band signal. The signal is in a sub-band. The second constraint limits the total power of the transmitted signal, and the third constraint represents the power limit for received beamforming.

[0060] S104, Solve the joint optimization problem to obtain the joint design results of the transmitted signal and the received beamforming vector.

[0061] Solve the joint optimization problem to obtain the transmitted signal. With the received beamforming vector The joint design results. The solution method for the joint optimization problem is determined according to its specific form, including but not limited to: using an alternating optimization method to decompose the original problem into several subproblems and solve them alternately, or integrating multiple optimization variables into one variable and solving it using a convex approximation method.

[0062] This embodiment provides a joint design method for broadband system transceivers based on full-band spatial domain modulation. Addressing the model mismatch problem caused by the common narrowband assumptions in existing broadband system design methods, this method establishes an accurate broadband system model, divides the full band into several sub-bands, and constructs a joint optimization problem using the transmitted signal of the full band and the received beamforming vectors of each sub-band as optimization variables. Under the performance constraints of specific application requirements, the consistency of full-band spatial domain indicators is optimized, achieving collaborative design of the broadband system transceiver end. This invention fully considers the significant differences in the propagation characteristics of different frequency components of the broadband signal in the array, and uses a broadband signal model to replace the traditional narrowband assumption. This solves the technical problems caused by model mismatch in practical systems, such as beam pattern distortion, increased angle estimation errors, and decreased communication reliability, making the system design more aligned with actual needs.

[0063] Example 2

[0064] This embodiment describes in detail the steps of a broadband system transceiver joint design method based on full-band spatial domain modulation for an integrated communication and sensing system. Figure 2 A detailed flowchart of the method is shown, including the following steps.

[0065] Step 201: Construct a radar transmission signal model and, based on beamforming at the radar receiver, construct the beam pattern of each sub-band signal as a radar performance indicator.

[0066] Step 202: Construct a communication signal receiving model, and based on the geometric positions of the received signal point and the correct reference point on the constellation diagram, define the ratio of intra-class and inter-class distances to quantify communication quality indicators.

[0067] Step 203: Construct a joint optimization problem to optimize the frequency domain transmitted signal and the radar received beamforming vector. Under the constraints of communication quality indicators and system hardware requirements, minimize the gap between the beam pattern of each frequency band and the ideal beam pattern.

[0068] Step 204: Use the Feasible Point Pursuit-Continuous Convex Approximation (FPP-SCA) algorithm to obtain a feasible solution to the optimization problem, which will serve as the starting point for subsequent optimizations.

[0069] Step 205: Add auxiliary variables to decompose the multivariate coupled optimization problem into multiple univariate subproblems and perform alternating optimization (AO). During the AO process, the continuous convex approximation algorithm (SCA) is used to update the transmitted waveform.

[0070] Step 206: During the AO process, update the received beamforming vector using the KKT condition and scalar bisection method.

[0071] Step 207: During the AO process, update the auxiliary variables using the closed-form solution.

[0072] The method described above achieves collaborative design of integrated inductive transceivers in broadband scenarios by jointly optimizing the frequency domain transmit waveform and the sub-band receive beamforming vector. The detailed steps are as follows:

[0073] In step 201, a radar transmitted signal model is constructed, and based on beamforming at the radar receiver, beam patterns for each sub-band signal are built as radar performance indicators. Consider a radar with... One transmitting antenna and A sensing-integrated base station with multiple receiving antennas; the base station transmits signals in a MIMO-OFDM manner, and has a total of... With subcarriers, at the Nyquist sampling rate, one OFDM symbol has _____ subcarriers_. There are 10 time sampling points. The discrete baseband transmitted signal is... After discrete Fourier transform, the frequency domain form of the transmitted signal is:

[0074]

[0075] For the space-frequency beam steering vectors at the transmitting and receiving ends and , respectively defined as and ,in Indicates direction, Represents the subcarrier index. Define the first... Sub-band receive beamforming vector Then the radar space-time beam pattern is:

[0076]

[0077] in, .

[0078] In step 202, a communication received signal model is constructed, and based on the geometric positions of the received signal point and the correct reference point on the constellation diagram, the ratio of intra-class and inter-class distances is defined to quantify the communication quality index. This is based on the time-domain transmitted signal. Frequency domain transmitted signals can also be defined as

[0079]

[0080] in, The discrete Fourier transform matrix is ​​defined as follows: .

[0081] The frequency domain representation of the communication channel is as follows Then, the noise-free received communication signal can be expressed in the frequency domain as: Based on the geometric positions of the received communication signal and the correct reference signal on the constellation diagram, the intra-class distance (WCD) and inter-class distance (BCD) are defined. The intra-class distance (WCD) is the sum of the squared distances from all communication symbols to the correct decoding position, defined as... Inter-class distance (BCD) is the sum of the squared distances from all communication symbols to all error decoding locations, defined as follows: .in For correct transmission symbols, This represents the set of all possible transmission symbols. Based on this, the ratio of intra-class to inter-class distances is... .

[0082] In step 203, a joint optimization problem is constructed to optimize the frequency domain transmitted signal. With radar receiving beamforming vector In terms of communication quality indicators Under the constraints of system hardware requirements, minimize the sum of the differences between the beam patterns of each frequency band and the ideal beam pattern. The joint optimization problem is defined as follows:

[0083]

[0084] The second constraint limits the total power of the transmitted signal, while the third constraint represents the power limit for received beamforming. As an ideal radiation pattern, a narrow beam with high gain is formed in the 0-degree direction.

[0085] In step 204, the feasible solution to the optimization problem is obtained using the Feasible Point Pursuit-Continuous Convex Approximation (FPP-SCA) algorithm, which serves as the starting point for subsequent optimizations. In each iteration of FPP-SCA, the communication quality index is... The constraints are approximated using a convex approximation, based on the results of the previous iteration. The first-order Taylor expansion at a given point is its convex approximation. For ease of subsequent derivation, we define...

[0086] ,

[0087]

[0088] Based on the above definitions, communication quality indicators The convex approximation constraint can be equivalently expressed as:

[0089]

[0090] Introducing slack variables Then FPP-SCA The problem to be solved in the next iteration is:

[0091]

[0092] This convex problem can be solved using the interior-point method. The solution is found when the absolute value of the difference between the objective function values ​​of two consecutive iterations is less than or equal to a certain proportion of the absolute value of the objective function value of the current iteration, and the slack variables... If the value is less than or equal to 0, then stop the iteration.

[0093] In step 205, add auxiliary variables. The multivariate coupled optimization problem is decomposed into multiple univariate subproblems, and alternating optimization (AO) is performed. In the first... In the next AO iteration, regarding the frequency domain transmitted signal The subproblems are:

[0094]

[0095] The continuous convex approximation algorithm (SCA) is used for iterative solution to finally update the transmitted waveform. In the SCA's... In this iteration, the optimization subproblem is:

[0096]

[0097] in, This is the solution obtained in the previous SCA iteration. , The subproblems in SCA iteration are convex problems and can be solved using the interior-point method. SCA iteration stops when the absolute value of the difference between the objective function values ​​of two consecutive iterations is less than or equal to a certain proportion of the absolute value of the objective function value of the current iteration.

[0098] In step 206, the received beamforming vector is updated using the KKT conditions and the scalar bisection method. In the AO iteration, regarding the ... Sub-band receive beamforming vector The subproblems are:

[0099]

[0100] According to the KKT conditions, we can obtain... The closed-form solution is

[0101]

[0102] in, , , Satisfy the equation

[0103] It can be calculated using the scalar bisection method. And thus obtain The solution.

[0104] In step 207, the auxiliary variable is updated using the closed-form solution. In the next AO iteration, the auxiliary variable is updated to .

[0105] In step 208, the iteration of alternating optimization stops when the convergence condition is met. The convergence condition is that the absolute value of the difference between the objective function values ​​of two consecutive iterations is less than or equal to a certain proportion of the absolute value of the current objective function value.

[0106] Example 3

[0107] This embodiment describes in detail the steps of a broadband system transceiver joint design method based on full-band spatial consistency for radar systems. It includes the following steps:

[0108] Step 301: Construct a radar transmitted signal model and, based on the beamforming at the radar receiver, construct the beam pattern of each sub-band signal as a radar airspace performance indicator.

[0109] Step 302: Construct radar waveform similarity constraints to ensure that the broadband radar transmitted waveform has good time-domain characteristics.

[0110] Step 303: Construct a joint optimization problem and perform joint optimization on the transmitted signal and received beamforming vectors on all subcarriers.

[0111] Step 304: Add auxiliary variables to decompose the multivariate coupled optimization problem into multiple univariate subproblems and perform alternating optimization (AO). During the AO process, the interior point method is used to update the transmitted waveform.

[0112] Step 305: During the AO process, the received beamforming vector is updated using the KKT condition and the scalar bisection method.

[0113] Step 306: During the AO process, update the auxiliary variables using the closed-form solution.

[0114] The method described above achieves collaborative design of integrated inductive transceivers in broadband scenarios by jointly optimizing the frequency domain transmit waveform and the sub-band receive beamforming vector. The specific implementation method is as follows:

[0115] In step 301, a radar transmitted signal model is constructed, and based on beamforming at the radar receiver, beam patterns for each sub-band signal are built as radar performance indicators. Consider a radar with... One transmitting antenna and A sensing-integrated base station with multiple receiving antennas; the base station transmits signals in a MIMO-OFDM manner, and has a total of... With subcarriers, at the Nyquist sampling rate, one OFDM symbol has _____ subcarriers_. There are 10 time sampling points. The discrete baseband transmitted signal is... After discrete Fourier transform, the frequency domain form of the transmitted signal is:

[0116]

[0117] For the space-frequency beam steering vectors at the transmitting and receiving ends and , respectively defined as and ,in Indicates direction, Represents the subcarrier index. Define the first... Sub-band receive beamforming vector Then the radar space-time beam pattern is:

[0118]

[0119] in, .

[0120] In step 302, radar waveform similarity constraints are constructed to ensure that the broadband radar transmitted waveform has good time-domain characteristics. To ensure that the broadband radar transmitted waveform achieves good range resolution, low sidelobes, and an engineering-feasible waveform structure, this embodiment pre-constructs a reference radar waveform. The reference radar waveform can be a waveform that meets predetermined radar performance requirements, such as: a reference waveform with low autocorrelation sidelobes; a reference waveform that meets constant mode or near-constant mode constraints; or a reference waveform that meets a preset spectrum template.

[0121] To ensure that the optimized transmitted signal retains the target beam directivity while also preserving the excellent radar characteristics of the reference radar waveform, this embodiment defines a radar waveform similarity metric as follows: .when When the deviation between the designed waveform and the reference radar waveform does not exceed a preset threshold, it indicates that the deviation is within the preset threshold. .

[0122] In step 303, the transmitted signals and received beamforming vectors on all subcarriers are jointly optimized. The optimization objective is to make the actual beam pattern of each subcarrier in the spatial direction as close as possible to the preset ideal beam pattern, while constraining the deviation between the designed transmitted waveform and the reference radar waveform, and satisfying the constraints on total transmitted power and received beamforming vector. Therefore, the optimization problem can be formulated as follows:

[0123]

[0124] in, Indicates the ideal beam pattern in the direction The first constraint is the amplitude at the given location, the second constraint is the total transmit power constraint, and the third constraint is the power constraint of the receive beamforming vector.

[0125] In step 304, auxiliary variables are added. The multivariate coupled optimization problem is decomposed into multiple univariate subproblems, and then subjected to alternating optimization (AO). and As the starting point for alternating iterations. In the... In the next AO iteration, regarding the frequency domain transmitted signal The subproblems are:

[0126]

[0127] This problem is a convex problem, which can be solved directly using the interior point method.

[0128] In step 305, the received beamforming vector is updated using the KKT conditions and the scalar bisection method. In the AO iteration, regarding the ... Sub-band receive beamforming vector The subproblems are:

[0129]

[0130] According to the KKT conditions, we can obtain... The closed-form solution is

[0131]

[0132] in, , , Satisfy the equation

[0133] It can be calculated using the scalar bisection method. And thus obtain The solution.

[0134] In step 306, the auxiliary variable is updated using the closed-form solution. In the next AO iteration, the auxiliary variable is updated to .

[0135] In step 307, the iteration of alternating optimization stops when the convergence condition is met. The convergence condition is that the absolute value of the difference between the objective function values ​​of two consecutive iterations is less than or equal to a certain proportion of the absolute value of the current objective function value.

[0136] To verify the performance of the proposed method, this invention conducted 100 Monte Carlo simulation experiments on a communication-sensing integrated system. Figure 3 This represents the beam pattern of all sub-bands under the traditional narrowband model. Figure 4 This shows the beam pattern of all sub-bands under the broadband model proposed in this invention. It can be seen that, compared to the design under the traditional narrowband assumption, the broadband model design method proposed in this invention can effectively avoid beam pattern broadening in the broadband caused by model mismatch, achieving better beam directivity. Figure 5 For communication constraints The distribution of communication signals on the constellation diagram. Figure 6 For communication constraints The distribution of communication signals on the constellation diagram is shown below. It can be seen that reducing the ratio of intra-class to inter-class distances in the design allows the communication signals to be closer to the correct decoding position on the constellation diagram, and further away from areas that could lead to incorrect decoding, thus ensuring communication reliability. Figure 7 For different signal and channel models, the objective function value varies with communication constraints. The changing curve shows that as communication constraints are relaxed, optimization yields a lower objective function value, resulting in better beam directivity. Figure 8 For different signal and channel models, the symbol error rate varies with communication constraints. The changing curve. It can be seen that, with... The reduction in the number of symbols means that the communication signal is closer to the area that is correctly decoded on the constellation diagram, resulting in a lower symbol error rate in communication.

[0137] Based on the same technical concept, the present invention also provides a broadband system transceiver joint design system based on full-band spatial domain control, comprising:

[0138] The system model building module is used to build a broadband system model, divide the full frequency band of the broadband system into segments, and build the transmit and receive signal models for each sub-band.

[0139] The constraint construction module is used to define spatial domain characteristic indicators for the transmitted signal and the corresponding received beamforming vector of each sub-band; and to construct corresponding performance constraints according to specific application requirements.

[0140] The optimization problem establishment module is used to construct a joint optimization problem with the full-band transmitted signal and the corresponding received beamforming vector as optimization variables, and optimize the consistency of the full-band spatial domain indicators under specific performance constraints.

[0141] The problem-solving module is used to solve the joint optimization problem and obtain the joint design results of the transmitted signal and the received beamforming vector.

[0142] The functions of each module can be specifically implemented according to the methods in the above method embodiments. The specific implementation process can be referred to the relevant descriptions in the above method embodiments, which will not be repeated here.

[0143] The present invention also provides an electronic device, comprising: one or more processors; a memory; and one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, wherein when the programs are executed by the processors, they implement the broadband system transceiver joint design method based on full-band spatial domain modulation as described above.

[0144] The present invention also provides a computer-readable storage medium having a computer program stored thereon, wherein the computer program, when executed by a processor, implements the broadband system transceiver joint design method based on full-band spatial domain control as described above.

Claims

1. A method for joint design of wideband system transmission and reception based on full-band spatial regulation, characterized in that, Includes the following steps: Establish a broadband system model, segment the entire frequency band of the broadband system, and construct the transmission and reception signal models for each sub-band; For each sub-band, define the spatial characteristics indexes for the transmitted signal and the corresponding received beamforming vector; and construct corresponding performance constraints according to specific application requirements. Using the full-band transmitted signal and the corresponding received beamforming vector as optimization variables, a joint optimization problem is constructed to optimize the consistency of the full-band spatial domain indicators under specific performance constraints. Solving the joint optimization problem yields the joint design results of the transmitted signal and the received beamforming vector.

2. The method of claim 1, wherein, Establish a broadband system model, segment the entire frequency band of the broadband system, and construct the transmit and receive signal models for each sub-band, including: Assume that the carrier frequency of a wideband system is The full frequency band of the wideband system is divided into sub-bands, the center frequency of the th sub-band is , and assume that the th signal point on the th sub-band is ; Assume a wideband system has transmit antennas and receive antennas, for the th sub-band, the transmit and receive spatial-frequency beam steering vectors and are defined as and , respectively, where denotes the direction, denotes the sub-band index, and the receive beamforming vector of the th sub-band is defined as , then the received signal of the sub-band in the direction is , where .

3. The method of claim 2, wherein, For each sub-band's transmitted signal and corresponding received beamforming vector, spatial domain characteristics are defined, including: No. The spatial-frequency beam pattern of each sub-band is as follows: Define the ideal beam pattern The ideal beam pattern is set according to specific application requirements, including any of the following: having a prominent peak in the desired detection direction, or having narrow beam characteristics to meet measurement accuracy requirements, or having wide beam characteristics to expand the detection range, or forming a beam notch in a specified direction to avoid interference. Define a metric for spatial consistency by summing the errors between the beam pattern and the ideal beam pattern in each sub-band: 。 4. The method according to claim 3, characterized in that, Develop corresponding performance constraints based on specific application requirements. The performance constraints are used to ensure the system's performance under specific tasks. Their specific form depends on the system's functional positioning and application scenario. When the system needs to ensure communication functions, the performance constraints include any of the following: signal-to-interference-plus-noise ratio (SINR) constraints, bit error rate (BER) constraints, mutual information constraints, or symbol-by-symbol constraints based on the geometric distribution of signals on the constellation diagram. When the system needs to ensure sensing functions, the performance constraints include any of the following: radar ambiguity function constraints, Cramer-Rao lower bound constraints, detection probability constraints, or parameter estimation accuracy constraints.

5. The method according to claim 4, characterized in that, Transmit signals in the full frequency band and the corresponding receive beamforming vector To optimize the variables, a joint optimization problem is constructed, under specific performance constraints. Below, to optimize the consistency of spatial indicators across the entire frequency band, the joint optimization problem is defined as: in, Its function is to extract the first frequency band signal from the full-band signal. The signal is in a sub-band, and the second constraint limits the total power of the transmitted signal. The first constraint is the preset total power value of the transmitted signal; the second constraint represents the power limit for the received beamforming.

6. The method according to claim 5, characterized in that, Solve the joint optimization problem to obtain the transmitted signal. With the received beamforming vector The solution method for the joint optimization problem is determined according to its specific form, including any of the following: using an alternating optimization method to decompose the original problem into several sub-problems and solve them alternately, or integrating multiple optimization variables into one variable and solving it using a convex approximation method.

7. A broadband system transceiver joint design system based on full-band spatial domain control, characterized in that, include: The system model building module is used to build a broadband system model, divide the full frequency band of the broadband system into segments, and build the transmit and receive signal models for each sub-band. The constraint construction module is used to define spatial domain characteristic indicators for the transmitted signal and the corresponding received beamforming vector of each sub-band; and to construct corresponding performance constraints according to specific application requirements. The optimization problem establishment module is used to construct a joint optimization problem with the full-band transmitted signal and the corresponding received beamforming vector as optimization variables, and optimize the consistency of the full-band spatial domain indicators under specific performance constraints. The problem-solving module is used to solve the joint optimization problem and obtain the joint design results of the transmitted signal and the received beamforming vector.

8. An electronic device, characterized in that, include: One or more processors; Memory; And one or more programs, wherein the one or more programs are stored in the memory and configured to be executed by the one or more processors, wherein when the programs are executed by the processors, they implement the broadband system transceiver joint design method based on full-band spatial domain modulation as described in any one of claims 1-6.

9. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the computer program is executed by the processor, it implements the broadband system transceiver joint design method based on full-band spatial domain control as described in any one of claims 1-6.

10. A computer program product, comprising a computer program, characterized in that, When the computer program is executed by the processor, it implements the broadband system transceiver joint design method based on full-band spatial domain control as described in any one of claims 1-6.

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