CRAMÉR-RAO BOUND AND ANTENNA SELECTION OPTIMIZATION FOR DUAL RADAR-COMMUNICATION DESIGN

Xu，Zhaoyi1; Liu，Fan2; Petropulu，Athina1

10.1109/ICASSP43922.2022.9747651

2022

47th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

1520-6149

978-1-6654-0541-6

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

2022-May

5168-5172

23-27 May 2022

Singapore, Singapore

345 E 47TH ST, NEW YORK, NY 10017 USA

IEEE

We consider multi-input multi-output (MIMO) dual function radar communication (DFRC) systems, and design a transmit beamforming matrix that optimizes a weighted combination of the radar estimate Cramér-Rao bound (CRB) and the communication rate. A hybrid beamforming structure is considered, with fewer RF chains than antennas, to achieve the benefits of MIMO systems while maintaining low cost. However, such a structure may have a rank-deficient beamforming matrix, resulting in degraded estimation performance. We propose antenna selection as means to ensure a full-rank beamforming matrix, and also select the communication channels so that high communication rate can be achieved. A learning approach is employed to optimally select antennas and design the corresponding beamforming matrix. By leveraging a combination of softmax neural networks, the proposed solution is able to optimize the joint performance metric for a DFRC system.

antenna selection CRB DFRC MIMO

其他

英语

EI ; CPCI-S

National Sleep Foundation[ECCS-2033433];

Acoustics ; Computer Science ; Engineering

Acoustics ; Computer Science, Artificial Intelligence ; Engineering, Electrical & Electronic

WOS:000864187905092

20222312198933

2-s2.0-85131228092

Scopus

1.Dept. of Electrical and Computer Engineering,Rutgers University,United States
2.Dept. of Electrical and Electronic Engineering,Southern University of Science and Technology,China

Xu，Zhaoyi,Liu，Fan,Petropulu，Athina. CRAMÉR-RAO BOUND AND ANTENNA SELECTION OPTIMIZATION FOR DUAL RADAR-COMMUNICATION DESIGN[C]. 345 E 47TH ST, NEW YORK, NY 10017 USA:IEEE,2022:5168-5172.