RIS-Assisted Downlink Pinching-Antenna Systems With NLOS Environments

Abstract

This paper investigates a reconfigurable intelligent surface (RIS)-assisted downlink pinching-antenna system (PASS) in the presence of non-line-of-sight (NLOS) users caused by unavoidable obstacles. An RIS is deployed to extend the coverage of the physically constrained PASS by establishing virtual line-of-sight (LOS) links. To improve system performance, we propose a zero-forcing (ZF) beamforming-based alternating optimization (AO) framework that minimizes the transmit power by jointly optimizing the RIS reflection coefficients and pinching-antenna (PA) activation positions. Specifically, the RIS reflection coefficients are optimized using the Riemannian conjugate gradient (RCG) method, while a novel projected gradient-based method is developed to efficiently optimize the PA activation positions. Simulation results demonstrate that the proposed AO framework outperforms baseline schemes in terms of both transmit power and computational efficiency under different system configurations including the rate requirements and RIS sizes.