NOMA Inspired Interference Cancellation for Integrated Sensing and Communication

A non-orthogonal multiple access (NOMA) inspired integrated sensing and communication (ISAC) system is investigated. A dual-functional base station (BS) serves multiple communication users while sensing multiple targets, by trans-mitting the non-orthogonal superposition of the communication and sensing signals. A NOMA inspired interference cancellation scheme is proposed, where part of the dedicated sensing signal is treated as the virtual communication signals to be mitigated at each communication user via successive interference cancellation (SIC). Based on this framework, the transmitted communication and sensing signals are jointly optimized to match the desired sensing beampattern, while satisfying the minimum rate requirement and the SIC condition at the communication users. Then, the formulated non-convex optimization problem is solved by invoking the successive convex approximation (SCA) to obtain a near-optimal solution. The numerical results show the proposed NOMA-inspired ISAC system can achieve better performance than the conventional ISAC system and comparable performance to the ideal ISAC system where all sensing interference is assumed to be removed unconditionally.

I. Introduction

The beyond fifth generation (B5G) and sixth generation (6G) wireless techniques are regarded as a key enabler for a host of emerging applications like unmanned aerial vehicles (UAVs), autonomous driving, virtual and augmented reality, Internet of Vehicles, and smart city [1], leading to a trend towards the convergence of multiple functions including com-munications, sensing, control, etc [2], [3]. Toward this trend, integrated sensing and communication (ISAC) is regarded as a promising technique in the B5G and 6G wireless networks and has received heated discussion recently [4]–[10]. The goal of ISAC is to merge the two functions in a single system and carry them out jointly and simultaneously, which can provide multiple benefits. On the one hand, through the dual usage of the hardware facilities and signals for both communication and sensing, it can enhance the spectral and energy efficiency and reduce the cost. On the other hand, thanks to such integration, the system can be further benefited from the mutual assistant, such as communication-aided sensing and sensing-aided communication [10].