Title
Cramér-Rao Bound Optimization for Joint Radar-Communication Beamforming
Abstract
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.
Year
DOI
Venue
2022
10.1109/TSP.2021.3135692
IEEE Transactions on Signal Processing
Keywords
DocType
Volume
Dual-functional radar-communication,joint beamforming,Cramér-Rao bound,semidefinite relaxation,successive convex approximation
Journal
70
ISSN
Citations 
PageRank 
1053-587X
9
0.48
References 
Authors
0
5
Name
Order
Citations
PageRank
Fan Liu1283.14
Y. F. Liu245430.59
Ang Li390.82
Christos Masouros4126394.92
Y. C. Eldar56399458.37