Reconfigurable Intelligent Surface Assisted NOMA Empowered Integrated Sensing and Communication
Reconfigurable Intelligent Surface Assisted NOMA Empowered Integrated Sensing and Communication
Jia-kuo Zuo,Yuanwei Liu
TLDR
An efficient joint optimization algorithm is proposed by invoking alternating optimization, successive convex approximation (SCA) and sequential rank-one constraint relaxation (SRCR) algorithm to maximize the minimum radar beampattern gain by jointly optimizing the active beamforming, power allocation coefficients and passive beamforming.
Abstract
This paper exploits the potential of reconfigurable intelligent surface (RIS) to improve radar sensing in a non-orthogonal multiple access (NOMA) empowered integrated sensing and communication (NOMA-ISAC) network. The objective is to maximize the minimum radar beampattern gain by jointly optimizing the active beamforming, power allocation coefficients and passive beamforming. To tackle the formulated non-convex problem, we propose an efficient joint optimization algorithm by invoking alternating optimization, successive convex approximation (SCA) and sequential rank-one constraint relaxation (SRCR) algorithm. Numerical results show that the proposed RIS assisted NOMA-ISAC system, with the aid of the proposed scheme, outperforms the RIS assisted ISAC system without NOMA.
