TY - JOUR
T1 - Interference and Noise Cancellation for Joint Communication Radar (JCR) System Based on Contextual Information
AU - Nnamani, Christantus O.
AU - Sellathurai, Mathini
N1 - Funding Information:
This work was supported in part by U.K. EPSRC under Grant EP/P009670/1 and Grant EP/T021063/1, and in part by the Petroleum Technology Development Fund under Grant PTDF/ED/PHD/NCO/1352/18.
Publisher Copyright:
© 2020 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper examines the separation of wireless communication and radar signals, thereby guaranteeing cohabitation and acting as a panacea to spectrum sensing. First, considering that the channel impulse responses were known by legitimate receivers (communication and radar), we showed that the optimizing beamforming weights mitigate the interference caused by signals and improve the physical layer security (PLS) of the system. Furthermore, when the channel responses were unknown, we designed an interference filter as a low-complex noise and interference cancellation autoencoder. By mitigating the interference on the legitimate users, the PLS was guaranteed. Results showed that even for a low signal-to-noise ratio, the autoencoder produces low root-mean-square error (RMSE) values.
AB - This paper examines the separation of wireless communication and radar signals, thereby guaranteeing cohabitation and acting as a panacea to spectrum sensing. First, considering that the channel impulse responses were known by legitimate receivers (communication and radar), we showed that the optimizing beamforming weights mitigate the interference caused by signals and improve the physical layer security (PLS) of the system. Furthermore, when the channel responses were unknown, we designed an interference filter as a low-complex noise and interference cancellation autoencoder. By mitigating the interference on the legitimate users, the PLS was guaranteed. Results showed that even for a low signal-to-noise ratio, the autoencoder produces low root-mean-square error (RMSE) values.
KW - Radar
KW - autoencoder
KW - contextual information
KW - joint communication and radar
KW - physical layer security
KW - wireless communication
UR - http://www.scopus.com/inward/record.url?scp=85167830543&partnerID=8YFLogxK
U2 - 10.1109/ojcoms.2023.3303248
DO - 10.1109/ojcoms.2023.3303248
M3 - Article
SN - 2644-125X
VL - 4
SP - 1855
EP - 1865
JO - IEEE Open Journal of the Communications Society
JF - IEEE Open Journal of the Communications Society
ER -