Energy Efficiency Optimization of FRIS-Assisted NOMA System
TL;DR
An alternating optimization (AO) framework is developed by integrating Dinkelbach’s method, first-order Taylor expansion, and a top- $M_{o}$ activation mechanism to maximize energy efficiency for a non-orthogonal multiple access (NOMA) system under predefined quality-of-service (QoS) constraints.
Abstract
Fluid reconfigurable intelligent surfaces (FRISs) have recently emerged as a promising extension of conventional reconfigurable intelligent surfaces (RISs), with the dynamic spatial control capability of fluid antenna systems (FASs). By replacing fixed reflecting elements with densely deployed, position-selective sub-elements capable of discrete phase adjustment, the FRIS provides additional spatial degrees of freedom (DoFs). Exploiting this advantage, we investigate the use of FRIS to maximize energy efficiency (EE) for a non-orthogonal multiple access (NOMA) system under predefined quality-of-service (QoS) constraints. The optimization problem is non-convex due to the fractional EE objective, coupled transmit power allocation, binary FRIS mask selection, and discrete phase shifts. To address this challenge, an alternating optimization (AO) framework is developed by integrating Dinkelbach’s method, first-order Taylor expansion, and a top- $M_{o}$ activation mechanism. Numerical results demonstrate that the proposed FRIS framework achieves substantial EE gains over conventional RIS-based benchmarks.