Exploiting Sensing Signal in ISAC: A NOMA Inspired Scheme

TL;DR

This paper introduces a NOMA-inspired ISAC framework that leverages sensing signals to transmit additional information, optimizing the trade-off between communication and sensing performance, and demonstrating superior or equivalent results compared to existing methods.

Contribution

It proposes a novel NOMA-inspired ISAC scheme that exploits sensing signals for extra information transmission and develops optimization algorithms for different user scenarios.

Findings

Outperforms state-of-the-art SenIC ISAC frameworks in multi-user scenarios.

Achieves the same performance as SenIC in single-user scenarios.

Provides effective algorithms for optimizing the trade-off between communication and sensing.

Abstract

A non-orthogonal multiple access (NOMA)-inspired integrated sensing and communication (ISAC) framework is proposed, where a dual-functional base station (BS) transmits the composite communication and sensing signals. In contrast to treating the sensing signal as a harmful interference to communication, in this work, multiple beams of the sensing signal are exploited to convey extra information streams based on the concept of NOMA. Then, each communication user detects the extra information streams and the existing legacy information streams with the aid of successive interference cancellation (SIC). Based on the proposed framework, a multiple-objective optimization problem (MOOP) is formulated to characterize the trade-off between the communication throughput and sensing beampattern accuracy. For the general multiple-user scenario, the formulated MOOP is firstly converted to a single-objective optimization problem via the e-constraint method. Then, a double-layer block coordinate descent (BCD) algorithm is proposed by employing fractional programming and successive convex approximation to find a high-quality sub-optimal solution. For the special single-user scenario, the globally optimal solution can be obtained by transforming the MOOP into a convex quadratic semidefinite program. Moreover, it is rigorously proved that 1) in the multiple-user scenario, the proposed NOMA-inspired ISAC framework always outperforms the state-of-the-art sensing-interference-cancellation (SenIC) ISAC frameworks by further exploiting sensing signals for delivering extra information streams; 2) in the special single-user scenario, the proposed NOMA-inspired ISAC framework achieves the same performance as the existing SenIC ISAC frameworks, which reveals that the coordination of sensing interference is not necessarily required in this case. Numerical results verify the theoretical results.