Joint Element and Power Optimization in NOMA-RIS-Assisted Indoor Near-Field Communications

Abstract

Reconfigurable intelligent surfaces (RIS) equipped with extremely large aperture arrays (ELAA) are emerging as a key technology for enhancing beamforming gain, spatial multiplexing, and angular resolution in sixth-generation (6G) wireless networks. When combined with non-orthogonal multiple access (NOMA), RIS can further improve spectral efficiency, system throughput, and energy efficiency. However, most existing studies on RIS-aided NOMA assume far-field propagation, where the incident wavefronts are approximately planar. In contrast, RIS-ELAA systems operating at millimeter wave (mmWave) experience spherical wavefronts in the radiative near-field regions. Also, it creates spatial non-stationarity and distance-dependent phase curvature. These effects invalidate the conventional monotonic path-loss assumption and make fairness-oriented NOMA design more challenging. This paper proposes a joint element and power optimization (JEPO) algorithm for near-field RIS-ELAA-assisted indoor NOMA systems, in which the RIS is dynamically partitioned into user-specific subarrays performing near-field phase synthesis toward the near user (NU) and far user (FU). The reversed far-to-near successive interference cancellation (SIC) ordering, governed by an effective FU channel gain greater than an effective NU channel gain, is formally established, and a closed-form optimal power allocation is derived by reducing the max-min fairness condition to a scalar quadratic in the target signal-to-interference-plus-noise ratio (SINR), eliminating iterative power search. Simulation results confirm that JEPO consistently outperforms four baseline schemes across transmit power, NU distance, angular separation, and RIS aperture size, with the largest gain observed at θNU≈40∘ where fixed-partition baselines collapse to near-zero fairness while JEPO maintains robust performance.