Interference and noise cancellation for joint communication radar (JCR) system based on contextual information

TL;DR

This paper proposes methods for interference and noise cancellation in joint communication-radar systems, enhancing spectrum coexistence and physical layer security through beamforming and autoencoder-based filtering.

Contribution

It introduces a novel autoencoder-based interference filter for unknown channels and analyzes beamforming for known channels to improve PLS in JCR systems.

Findings

Beamforming weights mitigate interference and enhance security with known channels.

Autoencoder effectively cancels interference with low RMSE at low SNR.

System maintains performance even under challenging noise conditions.

Abstract

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 response was known by the 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.