Coverage Analysis and Optimization of FIRES-Assisted NOMA and OMA Systems

2025-11-02

AI Summary

This paper investigates coverage optimization for a FIRES-aided two-user downlink NOMA/OMA system under spatially correlated Rician fading and phase control errors. We propose a bi-level joint optimization framework: the outer layer optimizes the geometric placement of reflective/transmissive elements to enable spatial repositioning, while the inner layer jointly optimizes power allocation and energy splitting to maximize energy efficiency, subject to strict successive interference cancellation (SIC) feasibility constraints. A closed-form analytical expression for the far-field line-of-sight (LoS) coverage boundary is derived, quantifying the system’s robustness against phase errors. Simulation results demonstrate that, under identical hardware budgets, FIRES significantly expands coverage compared to conventional STAR-RIS, with NOMA providing additional gains; theoretical boundaries align closely with numerical results. The core contribution lies in a geometry-resource co-optimization architecture and its coverage enhancement mechanism under non-ideal channel and control conditions.

Technology Category

• Planning, Routing, and Scheduling: Optimization of Spatio-temporal Systems
• Search and Optimization: Mixed Discrete/Continuous Search
• Constraint Satisfaction and Optimization: Distributed CSP/Optimization

Application Category

• Systems and Infrastructure for Web, Mobile and WoT: Energy management for devices in mobile Web and WoT environments
• Security and Privacy: Large-scale security measurements
• Search and Retrieval-Augmented AI: Vertical and domain-specific search

Abstract

Fluid integrated reflecting and emitting surfaces (FIRES) are investigated. In these metasurfaces, each subarea hosts an active element capable of simultaneous transmission and reflection, phase, and geometric positioning control within the subarea. We develop a coverage-centric system model for the two-user downlink scenario (one user per half-space) under spatially correlated Rician fading and imperfect phase control. First, we derive closed-form far-field line-of-sight (LoS) coverage bounds that reveal the effects of aperture size, base station (BS) distance, transmit power, energy-splitting (ES), and phase errors. Protocol-aware corollaries are then presented for both orthogonal multiple access (OMA) and non-orthogonal multiple access (NOMA), including conditions for successful successive interference cancellation (SIC). Second, we formulate coverage maximization as a bi-level optimization problem consisting of (i) an outer search over FIRES element positions, selecting one active preset per subarea under minimum-spacing constraints, and (ii) an inner resource allocation problem tailored to the multiple-access scheme, which is one-dimensional for OMA and a small convex program for NOMA. The proposed framework explicitly accounts for target rate constraints, ES conservation, power budgets, geometric placement limits, and decoding-order feasibility. Extensive simulations demonstrate that FIRES, by jointly exploiting geometric repositioning and passive energy control, substantially enlarges the coverage region compared with a conventional simultaneously transmitting and reflecting reconfigurable intelligent surface (STAR-RIS) under the same element budget. Furthermore, NOMA yields additional coverage gains when feasible. The analytical coverage bounds closely match the simulation results and quantify the robustness of FIRES to phase-control imperfections.

Problem

• Analyzing coverage bounds for FIRES-assisted wireless communication systems
• Optimizing element positioning and resource allocation for coverage maximization
• Comparing performance between NOMA and OMA under practical constraints

Innovation

• FIRES metasurfaces enable simultaneous transmission and reflection control
• Bi-level optimization combines geometric positioning and resource allocation
• Framework supports both NOMA and OMA with coverage maximization