Reconfigurable Intelligent Surface Enabled Over-the-Air Uplink Non-orthogonal Multiple Access

TL;DR

This paper explores the use of active and passive reconfigurable intelligent surfaces (RIS) to enable over-the-air non-orthogonal multiple access (NOMA) in uplink wireless systems, allowing users with identical power levels to share resources efficiently.

Contribution

It introduces a hybrid RIS system that partitions active and passive elements to facilitate NOMA without requiring power disparity at the user end.

Findings

Achieves virtual NOMA with identical user transmit powers.

Provides outage probability and error analysis for the proposed system.

Validates results through computer simulations.

Abstract

Innovative reconfigurable intelligent surface (RIS) technologies are rising and recognized as promising candidates to enhance 6G and beyond wireless communication systems. RISs acquire the ability to manipulate electromagnetic signals, thus, offering a degree of control over the wireless channel and the potential for many more benefits. Furthermore, active RIS designs have recently been introduced to combat the critical double fading problem and other impairments passive RIS designs may possess. In this paper, the potential and flexibility of active RIS technology are exploited for uplink systems to achieve virtual non-orthogonal multiple access (NOMA) through power disparity over-the-air rather than controlling transmit powers at the user side. Specifically, users with identical transmit power, path loss, and distance can communicate with a base station sharing time and frequency resources in a NOMA fashion with the aid of the proposed hybrid RIS system. Here, the RIS is partitioned into active and passive parts and the distinctive partitions serve different users aligning their phases accordingly while introducing a power difference to the users' signals to enable NOMA. First, the end-to-end system model is presented considering two users. Furthermore, outage probability calculations and theoretical error probability analysis are discussed and reinforced with computer simulation results.