Performance Analysis of IOS-Assisted NOMA System with Channel Correlation and Phase Errors

TL;DR

This paper analyzes the performance of IOS-assisted NOMA systems considering channel correlation and phase errors, deriving bounds and approximations for achievable rates, and comparing NOMA with OMA.

Contribution

It provides new analytical bounds and approximations for IOS-assisted NOMA performance under realistic channel and hardware imperfections.

Findings

Low-precision phase elements nearly match ideal performance.

Correlated and uncorrelated channels yield asymptotically similar rates.

IOS-assisted NOMA does not always outperform OMA depending on reconfigurability.

Abstract

In this paper, we investigate the performance of an intelligent omni-surface (IOS) assisted downlink non-orthogonal multiple access (NOMA) network with phase quantization errors and channel estimation errors, where the channels related to the IOS are spatially correlated. First, upper bounds on the average achievable rates of the two users are derived. Then, channel hardening is shown to occur in the proposed system, based on which we derive approximations of the average achievable rates of the two users. The analytical results illustrate that the proposed upper bound and approximation on the average achievable rates are asymptotically equivalent in the number of elements. Furthermore, it is proved that the asymptotic equivalence also holds for the average achievable rates with correlated and uncorrelated channels. Additionally, we extend the analysis by evaluating the average achievable rates for IOS assisted orthogonal multiple access (OMA) and IOS assisted multi-user NOMA scenarios. Simulation results corroborate the theoretical analysis and demonstrate that: i) low-precision elements with only two-bit phase adjustment can achieve the performance close to the ideal continuous phase shifting scheme; ii) The average achievable rates with correlated channels and uncorrelated channels are asymptotically equivalent in the number of elements; iii) IOS-assisted NOMA does not always perform better than OMA due to the reconfigurability of IOS in different time slots.