TY - JOUR
T1 - A low-complexity MIMO dual function radar communication system via one-bit sampling
AU - Zhu, Siyu
AU - Xi, Feng
AU - Chen, Shengyao
AU - Nehorai, Arye
N1 - Funding Information:
Siyu Zhu, Feng Xi, and Shengyao Chen are with the Department of Electronic Engineering, Nanjing University of Science and Technology, Nanjing 210094 China (email: karina-yu@qq.com, xifeng@njust.edu.cn, chen-shengyao@njust.edu.cn). A. Nehorai is with the Department of Electrical and Systems Engineering, Washington University in St. Louis, St. Louis, MO 63130 USA (e-mail: nehorai@wustl.edu). This work was supported in part by the National Natural Science Foundation of China under grant No. 61571228.
Publisher Copyright:
© 2021 IEEE
PY - 2021
Y1 - 2021
N2 - Dual-function radar-communication (DFRC) system is flexible to be applied in a variety of scenarios. However, it is challenging to implement a low-cost low-complexity DFRC system due to the dynamic cooperation between radar sensing and communication tasks. In this paper, we propose to implement a low-complexity multiple input multiple output DFRC (MIMO-DFRC) system relying on the generalized spatial modulation (GSM) and the low-resolution sampling. To deal with the induced quantization distortion and dynamic antenna allocation, we formulate the radar sensing problem as an atomic norm-based convex problem, which can be solved by off-the-shelf solvers. Simulation results demonstrate that the proposed MIMO-DFRC system can achieve delay and azimuth estimation with accuracy as low as about 10% of the resolution grids while employing 1-bit sampling.
AB - Dual-function radar-communication (DFRC) system is flexible to be applied in a variety of scenarios. However, it is challenging to implement a low-cost low-complexity DFRC system due to the dynamic cooperation between radar sensing and communication tasks. In this paper, we propose to implement a low-complexity multiple input multiple output DFRC (MIMO-DFRC) system relying on the generalized spatial modulation (GSM) and the low-resolution sampling. To deal with the induced quantization distortion and dynamic antenna allocation, we formulate the radar sensing problem as an atomic norm-based convex problem, which can be solved by off-the-shelf solvers. Simulation results demonstrate that the proposed MIMO-DFRC system can achieve delay and azimuth estimation with accuracy as low as about 10% of the resolution grids while employing 1-bit sampling.
KW - 1-bit sampling
KW - Dual function radar communication
KW - MIMO radar
UR - http://www.scopus.com/inward/record.url?scp=85115167237&partnerID=8YFLogxK
U2 - 10.1109/ICASSP39728.2021.9414051
DO - 10.1109/ICASSP39728.2021.9414051
M3 - Conference article
AN - SCOPUS:85115167237
SN - 0736-7791
VL - 2021-June
SP - 8223
EP - 8227
JO - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
JF - ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
T2 - 2021 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2021
Y2 - 6 June 2021 through 11 June 2021
ER -