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MIMO雷达通信一体化:波束图增益最大化波束成形设计

MIMO Dual-functional Radar-communication:Beampattern Gain Maximization Beamforming Design
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摘要 无线通信设备数量的骤增造成频谱资源日益稀缺,通信用频逐渐向更高频段扩展,从而导致通信与雷达频段出现越来越多的重叠,雷达通信一体化被视为解决频谱拥挤实现高效共生的潜在技术。该文考虑一个多输入多输出(MIMO)雷达通信一体化系统,在实现目标探测的同时进行多用户通信。首先,在满足多用户信干噪比和总功率约束的条件下,最大化目标方向的波束图增益。然后,针对一体化发射波束成形设计问题,提出基于半正定松弛(SDR)和优化最小化(MM)的两种波束成形设计方案,求解得到发射波束成形矢量。最后,仿真结果表明基于MM的方案复杂度更低,并且能够实现与基于SDR的方案几乎相同的波束图增益。此外,随着发射天线数量的增加,基于MM的方案相比于基于SDR的方案复杂度的降低程度变得更为显著。 Objective The rapid growth in the number of wireless communication devices has led to the expansion of frequency bands to higher frequencies,resulting in increased overlap between communication and radar systems.Dual-Functional Radar-Communication(DFRC),which shares spectrum resources on the same hardware platform,is an effective solution to address spectrum congestion.The integration of Multiple-Input Multiple-Output(MIMO)technology,which employs multi-antenna techniques,with DFRC is crucial for achieving both high-precision detection and large-capacity communication.Beamforming technology plays a key role in efficiently allocating resources between these two requirements,further enhancing the collaborative gain of DFRC systems.Beampattern gain,a critical performance metric for target detection,makes it essential to investigate beamforming designs that maximize this gain in MIMO DFRC systems.Methods An MIMO DFRC system is considered,which simultaneously achieves target detection and Multi-User(MU)communication.First,a beamforming problem is formulated to maximize the beampattern gain in the target direction,while satisfying MU Signal-to-Interference-plus-Noise Ratio(SINR)and total power constraints.To address this beamforming design problem,two methods based on Semidefinite Relaxation(SDR)and Majorization Minimization(MM)are proposed to solve for the transmit beamforming vectors.Specifically,the SDR-based method transforms the beamforming problem into a semidefinite programming problem by introducing auxiliary variables and relaxing the rank-one constraint.The MM-based method,on the other hand,uses the first-order Taylor expansion to construct a cost function from the objective function,transforms the SINR constraint into a second-order cone constraint,and iteratively solves the simplified problem.Results and Discussions The convergence curves of the SDR-based and MM-based beamforming design schemes are shown(Figure 2).The results indicate that the MM-based method can achieve almost the same beampattern gain as the SDR-based method.Under the same number of transmit antennas,a higher SINR threshold results in a smaller beampattern gain.This phenomenon reflects the performance trade-off between communication and radar in MIMO DFRC systems.Under the same SINR threshold,increasing the number of transmit antennas leads to a greater beampattern gain.This is because an increase in the number of transmit antennas provides additional degrees of freedom for the radar.The comparison of the single CVX running time of the SDR-based and MM-based methods under different numbers of transmit antennas is shown(Figure 3).The results demonstrate that the single CVX running time of the MM-based method is shorter than that of the SDR-based method for the same number of transmit antennas,and as the number of transmit antennas increases,the complexity reduction of the MM-based method becomes more significant than that of the SDR-based method.The variation curves of beampattern gain with SINR threshold for different numbers of transmit antennas in the MM-based and SDR-based methods are shown(Figure 4).The beampattern gain obtained by the MM-based method is slightly lower than that obtained by the SDR-based method.However,as the number of transmit antennas increases,the difference between the two methods gradually decreases.Moreover,the more transmit antennas there are,the greater the SINR achievable by the communication user.When the number of antennas is fixed,the relationship between beampattern gain and transmit SNR obtained by the radar using the MM-based method is presented(Figure 5).When the SINR threshold remains unchanged,the relationship between them is shown(Figure 6).The results illustrate that,compared with the radar-only scenario,the beampattern gain performance of MIMO DFRC systems is lower,and a larger SINR threshold results in a smaller beampattern gain.Additionally,within a certain range,when the transmit SNR is constant,beampattern gain is directly proportional to the number of transmit antennas.Conclusions This paper addresses the beamforming design problem for MIMO DFRC systems with the objective of maximizing beampattern gain.By jointly optimizing the communication and radar transmit beamforming vectors,the beampattern gain in the target direction is maximized while satisfying the SINR constraint for communication users and the total transmit power constraint.To solve this problem,the SDR-based and MM-based beamforming design methods are proposed.Simulation results demonstrate that the MM-based method offers lower complexity and achieves nearly the same beampattern gain as the SDR-based method.Moreover,as the number of transmit antennas increases,the complexity reduction of the MM-based method is more significant compared to the SDR-based method.
作者 张若愚 任红 陈光毅 林志 吴文 ZHANG Ruoyu;REN Hong;CHEN Guangyi;LIN Zhi;WU Wen(Key Laboratory of Near-Range RF Sensing ICs&Microsystems,Nanjing University of Science and Technology,Nanjing 210094,China;College of Electronic Engineering,National University of Defense Technology,Hefei 230037,China)
出处 《电子与信息学报》 北大核心 2025年第3期687-695,共9页 Journal of Electronics & Information Technology
基金 国家自然科学基金(62201266,62201592,62471477) 江苏省自然科学基金(BK20210335)。
关键词 雷达通信一体化 多输入多输出 波束成形 波束图增益 优化最小化 Dual-Functional Radar-Communication(DFRC) Multiple-Input Multiple-Output(MIMO)
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