波束赋形
多输入多输出
雷达
计算机科学
放松(心理学)
克拉姆-饶行
信噪比(成像)
公制(单位)
算法
数学优化
半定规划
数学
上下界
估计理论
电信
工程类
社会心理学
数学分析
运营管理
心理学
作者
Fan Liu,Ya-Feng Liu,Ang Li,Christos Masouros,Yonina C. Eldar
标识
DOI:10.1109/tsp.2021.3135692
摘要
In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramér-Rao bound (CRB) as a performance metric of target estimation, under both point and extended target scenarios. We then propose minimizing the CRB of radar sensing while guaranteeing a pre-defined level of signal-to-interference-plus-noise ratio (SINR) for each communication user. For the single-user scenario, we derive a closed form for the optimal solution for both cases of point and extended targets. For the multi-user scenario, we show that both problems can be relaxed into semidefinite programming by using the semidefinite relaxation approach, and prove that the global optimum can be generally obtained. Finally, we demonstrate numerically that the globally optimal solutions are reachable via the proposed methods, which provide significant gains in target estimation performance over state-of-the-art benchmarks.
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