On Normalized Least Mean Square Based Interference Cancellation Algorithm for Integrated Sensing and Communication Systems

Abstract: Integrated sensing and communication (ISAC) technology is a promising candidate for next-generation communication systems. However, severe co-site interference in existing ISAC systems limits the communication and sensing performance, posing significant challenges for ISAC interference management. In this work, we propose a novel interference management scheme based on the normalized least mean square (NLMS) algorithm, which mitigates the impact of co-site interference by reconstructing the interference from the local transmitter and canceling it from the received signal. Simulation results demonstrate that, compared to typical adaptive interference management schemes based on recursive least square (RLS) and stochastic gradient descent (SGD) algorithms, the proposed NLMS algorithm effectively cancels co-site interference and achieves a good balance between computational complexity and convergence performance.

Keywords: interference management; OFDM; 5G new radio; interference cancellation; radio frequency domain