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A Joint Radar-Communication Precoding Design Based on Cramér-Rao Bound Optimization

  • Fan Liu
  • , Ya Feng Liu
  • , Christos Masouros
  • , Ang Li
  • , Yonina C. Eldar
  • Southern University of Science and Technology
  • CAS - Academy of Mathematics and System Sciences
  • University College London
  • Weizmann Institute of Science

科研成果: 期刊稿件会议文章同行评审

23 引用 (Scopus)

摘要

This paper investigates joint radar-communication (JRC) transmission, where a JRC precoder is designed to simultaneously perform target sensing and information signaling. We minimize the Cramér-Rao Bound (CRB) for target estimation, while guaranteeing the per-user signal-to-interference-plus-noise ratio (SINR) in the downlink. While the formulated problem is non-convex in general, we propose an efficient successive convex approximation (SCA) method, which solves a second-order cone program (SOCP) subproblem at each iteration. Numerical results demonstrate the effectiveness of the proposed JRC precoding design, showing that the SCA algorithm is able to approach the convex relaxation bound, which significantly outperforms conventional benchmark solvers in terms of both complexity and performance.

源语言英语
期刊Proceedings of the IEEE Radar Conference
DOI
出版状态已出版 - 2022
活动2022 IEEE Radar Conference, RadarConf 2022 - New York City, 美国
期限: 21 3月 202225 3月 2022

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