Joint User Pairing and CRB Optimization for NOMA-aided Integrated Sensing and Communication.

Integrated sensing and communication (ISAC) is a promising paradigm to efficiently utilize the radio resources and hardware for both sensing and communication in the future Internet of Things (IoT). In this paper, we investigate a non-orthogonal multiple access (NOMA)-aided ISAC system in which the ISAC base station (BS) serves multiple pairs of NOMA users with the same spectrum resources while performing target estimation by utilizing the superimposed signal. To investigate this problem, we formulate a joint optimization of the user pairing and the beamforming vectors for all NOMA users, with the objective of minimizing the Cramer-Rao bound (CRB) for sensing. Despite that the formulated problem is strictly non-convex, we adopt the successive convex approximation and semidefinite relaxation to transform the problem into a tractable form and propose an efficient algorithm for solving it. Numerical results demonstrate the performance gains achieved by our NOMA-aided ISAC with the user pairing scheme in the aspects of sensing performance, spectral efficiency for transmission and energy efficiency for transmission.