Joint Beamforming and Position Optimization for FIRES-NOMA Assisted Wireless Communication Systems

TL;DR

This paper introduces a FIRES-assisted NOMA system with movable elements, enhancing spatial control and system capacity through joint beamforming and position optimization, validated by simulations showing significant performance gains.

Contribution

It proposes a novel FIRES design with movable elements and develops an optimization framework for joint beamforming and positioning, improving capacity and reducing hardware costs.

Findings

Achieves up to 27% higher sum rate than conventional systems.

Requires about 50% fewer RIS elements for similar performance.

Demonstrates effective joint optimization of beamforming and element positions.

Abstract

To address the limitations of conventional reconfigurable intelligent surfaces (RIS) in spatial control capability, this paper proposes a fluid integrated reflecting and emitting surface (FIRES) assisted non-orthogonal multiple access (NOMA) multi-user communication system. In this system, each FIRES element can continuously and flexibly adjust its position in response to environmental variations, enabling simultaneous service to users in both transmission and reflection zones. This significantly enhances the system's spatial degrees of freedom (DoF) and service adaptability. To maximize the system's total sum rate, we formulate a non-convex optimization problem that jointly optimizes the base station beamforming, the transmission/reflection coefficients of the FIRES, and the element positions. An alternating optimization (AO) algorithm is developed, incorporating successive convex approximation (SCA), semi-definite relaxation (SDR), and majorization-minimization (MM) techniques. In particular, to address the complex channel coupling introduced by the coexistence of direct and FIRES paths, the MM framework is employed in the element position optimization subproblem, enabling an efficient iterative solution strategy. Simulation results validate that the proposed system achieves up to a 27% increase in total sum rate compared to conventional STAR-RIS systems and requires approximately 50% fewer RIS elements to attain the same performance, highlighting its effectiveness for cost-efficient large-scale deployment.