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Publication Detail
Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming
  • Publication Type:
    Journal article
  • Publication Sub Type:
    Article
  • Authors:
    Liu F, Liu YF, Li A, Masouros C, Eldar YC
  • Publication date:
    2022
  • Journal:
    IEEE Transactions on Signal Processing
  • Status:
    Published
  • Print ISSN:
    1053-587X
Abstract
In this paper, we propose multi-input multi-output (MIMO) beamforming designs towards joint radar sensing and multi-user communications. We employ the Cramr-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 always be 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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