For a Multiple-Input Multiple-Output (MIMO)-Orthogonal Frequency-Division Multiplexing (OFDM) based dual-function radar and communication (DFRC), the problem of transmit/receive beamforming with the constraints of Quality of Server (QoS) and transmit power is studied in this paper. The degrees of freedom for system design are the transmit/receive beampatterns at the radar array, and the receive beampattern at the communication array. Firstly, we adopt Kullback-Leibler divergence (KLD) as design metrics and formulate the design problem as a KLD maximization problem with QoS and transmit power constraints. Secondly, we solve the original non-convex problem through the proposed alternating direction sequential relaxation programming (ADSRP) algorithm, which iteratively optimizes three subproblems: 1) dual-function transmit beamforming with the constraints of QoS and transmit power; 2) radar receive beamforming; and 3) communication receive beamforming. We analytical provide the monotonic improvement and bound of KLD, which guarantees the convergence of the ADSRP algorithm. Finally, simulation results are provided to evaluate the effects of different QoS requirements and peak-to-average-power ratio (PAPR) constraints in terms of power allocation scheme and radar detection performance, compared to the traditional radar system (TRS).

中文翻译：

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基于 MIMO-OFDM 的双功能雷达和通信的发射/接收波束成形


对于基于多输入多输出（MIMO）-正交频分复用（OFDM）的双功能雷达和通信（DFRC），在服务器质量（QoS）和发送约束下的发送/接收波束成形问题本文对功率进行了研究。系统设计的自由度是雷达阵列处的发射/接收波束图以及通信阵列处的接收波束图。首先，我们采用 Kullback-Leibler 散度（KLD）作为设计指标，并将设计问题表述为具有 QoS 和传输功率约束的 KLD 最大化问题。其次，我们通过提出的交替方向顺序松弛规划（ADSRP）算法解决了原始的非凸问题，该算法迭代优化了三个子问题：1）具有QoS和发射功率约束的双功能发射波束成形； 2）雷达接收波束形成； 3) 通信接收波束成形。分析给出了KLD的单调改进和有界，保证了ADSRP算法的收敛性。最后，提供仿真结果，以评估与传统雷达系统 (TRS) 相比，不同 QoS 要求和峰均功率比 (PAPR) 约束在功率分配方案和雷达检测性能方面的影响。