Efficient Transceiver Design for MIMO Dual-Function Radar-Communication Systems

• Published in: IEEE transactions on signal processing Vol. 71; pp. 1 - 16
• Main Authors: Wen, Cai, Huang, Yan, Davidson, Timothy N.
• Format: Journal Article
• Language: English
• Published: New York IEEE 01.01.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Algorithms; Approximation; Communication; Communications systems; Complexity; Dual-function radar-communication (DRFC); integrated sensing and communications (ISAC); Interference; local approximation refinement; MIMO communication; MIMO radar; MU-MISO communication; Optimization; Precoding; Radar; Sensors; Signal processing algorithms; Signal to noise ratio; successive convex approximation; transceiver design; Transceivers; Waveforms
• ISSN: 1053-587X; 1941-0476
• DOI: 10.1109/TSP.2023.3275274

This paper considers jointly optimizing the transmitting (Tx) waveform and the receivers of a multiple-input multiple-output (MIMO) dual-function radar-communication (DFRC) system. The proposed approach incorporates the design of the (complex-valued) communication receiving (Rx) coefficients, in addition to the radar Rx filters. We address the problem of maximizing the minimum radar signal-to-interference-plus-noise ratio (SINR) subject to communication SINR, per-antenna power and peak-to-average-power ratio (PAPR) constraints. A successive convex approximation (SCA) algorithm is developed to find a good solution for the resultant nonconvex design problem. To accelerate that algorithm and to improve the solution quality, we further propose a local-approximation-refinement SCA (LAR- SCA) algorithm which possesses guaranteed convergence properties. In addition, a sub-block design technique is developed to reduce the design complexity in the case of long Tx sequences. Numerical results show that by incorporating the communication Rx coefficients into the joint design, the radar and communication capabilities of the DFRC system can be significantly enhanced over the state-of-the-art designs, while maintaining an efficient algorithm.