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Co-Design for Overlaid MIMO Radar and Downlink MISO Communication Systems via Cramér–Rao Bound Minimization

机译:通过Cramér–Rao限界最小化实现重叠MIMO雷达和下行MISO通信系统的协同设计

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This paper considers the problem of co-existence of collocated multiple-input multiple-output (MIMO) radar and downlink multiple-input single-output (MISO) communication systems, which share the same frequency band. As the interference caused by the communication systems would degrade the accuracy of radar target localization, we formulate the co-design of radar waveform and communication transmit weights by minimizing the Cramr-Rao Bound (CRB) of direction-of-arrival (DOA) estimation, subject to a set of constraints accounting for the worst-case signal-to-noise-plus-interference ratio (SINR), similarity and energy. However, the objective is nonconvex and all variables are coupled together in the SINR constraints, the formulated problem is thus NP-hard. Towards that end, a decentralized block successive upper-bound minimization (D-BSUM) method based on the decomposition theory is developed. More specifically, at each iteration of this algorithm, the radar waveform is obtained with the aid of the alternating direction method of multipliers (ADMM) algorithm, and communication weights are obtained by exploiting the semidefinite programs (SDP). It is also proved that the proposed SDP-based method gives a rank-one solution. Numerical simulations are conducted to evaluate the effectiveness of the proposed algorithm.
机译:本文考虑了共享相同频带的并置多输入多输出(MIMO)雷达与下行链路多输入单输出(MISO)通信系统并存的问题。由于通信系统造成的干扰会降低雷达目标定位的精度,因此我们通过最小化到达方向(DOA)估计的Cramr-Rao边界(CRB)来制定雷达波形和通信发射权重的共同设计受到一系列约束,这些约束考虑了最坏情况下的信噪比(SINR),相似性和能量。但是,目标是非凸的,并且所有变量在SINR约束中耦合在一起,因此提出的问题是NP-困难的。为此,开发了基于分解理论的分散块连续上限最小化(D-BSUM)方法。更具体地说,在该算法的每次迭代中,借助于乘法器的交替方向方法(ADMM)算法获得雷达波形,并通过利用半定程序(SDP)获得通信权重。还证明了所提出的基于SDP的方法给出了排名第一的解决方案。进行数值模拟以评估所提出算法的有效性。

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