NOMA Inspired Integrated Sensing and Communication

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 unicast communication signal and sensing signal. In contrast to treating the sensing signal as the harmful interference to communication, in this work, multiple beams of the sensing signal are employed to convey multicast information following the concept of NOMA. Then, each communication user receives multiple multicast streams and one desired unicast stream, which are detected via successive interference cancellation (SIC). Based on the proposed framework, a multiple-objective optimization problem (MOOP) is formulated for designing the transmit beamforming, which characterizes the communication-sensing trade-off. For general the multiple-user scenario, the formulated MOOP is converted to a single-objective optimization problem (SOOP) via the e-constraint method. Then, a block coordinate descent (BCD) algorithm is proposed by employing fractional programming (FP) and successive convex approximation (SCA) to find a suboptimal solution. For the special single-user scenario, the globally optimal solution can be obtained by transforming the MOOP to a quadratic semidefinite program (QSDP). Moreover, it is rigorously proved that 1) in the multiple-user scenario, the proposed framework always outperform the sensing-interference-cancellation (SenIC) ISAC frameworks by further exploiting sensing signal for delivering information; 2) in the single-user scenario, the proposed framework achieves the same performance as the existing SenIC ISAC frameworks, which reveals that the sensing interference coordination is not required in this case. Numerical results verify the theoretical results and show that exploiting one beam of the sensing signal for delivering multicast information is sufficient for the proposed framework.