Performance Analysis of Uplink Adaptive NOMA Depending on Channel Knowledge

TL;DR

This paper compares uplink NOMA and OMA performance under different channel knowledge scenarios, deriving closed-form expressions and proposing an adaptive strategy that optimally switches between them to maximize throughput.

Contribution

It introduces NOMA-Adaptive, a new strategy that dynamically chooses between NOMA and OMA based on channel information to improve performance.

Findings

NOMA-A outperforms traditional NOMA and OMA in simulations.

Closed-form throughput expressions are derived for both NOMA and OMA.

NOMA-A maximizes sum throughput and user activity probability.

Abstract

Non Orthogonal Multiple Access (NOMA) is a key technique to satisfy large users densities in future wireless networks. However, NOMA may provide poor performance compared to Orthogonal Multiple Access (OMA) due to inter-user interference. In this paper, we obtain closed-form expressions of the uplink NOMA and OMA throughputs when no Channel State Information at Transmitter (CSIT) is available, and of the average data rates assuming that instantaneous rates should be larger than a minimum threshold when full CSIT is available. Analytical comparisons of OMA and NOMA prove that there is no global dominant strategy valid in all situations. Based on this conclusion, we propose a new multiple-access (MA) strategy called NOMA-Adaptive (NOMA-A) that selects the best MA technique between OMA and NOMA. NOMA-A aims at maximizing the sum throughput in the no CSIT case, and the probability that both users are active in the full CSIT case. NOMA-A is shown to outperform the other strategies in terms of sum throughput and rate.