Downlink Asynchronous Non-Orthogonal Multiple Access with Quantizer Optimization

TL;DR

This paper investigates a two-user downlink ANOMA system with limited feedback, deriving bounds for max-min rate, and proposes a quantizer optimization to enhance performance over traditional methods, especially with low feedback.

Contribution

It introduces a quantizer optimization algorithm for ANOMA and NOMA, improving max-min rate performance under limited feedback conditions.

Findings

ANOMA can match or surpass NOMA in max-min rate with less feedback.

The optimized quantizer significantly outperforms uniform quantizers.

Performance gains are especially notable at low feedback rates.

Abstract

In this letter, we study a two-user downlink asynchronous non-orthogonal multiple access (ANOMA) with limited feedback. We employ the max-min criterion for the power allocation and derive the closed-form expressions for the upper and lower bounds of the max-min rate. It is demonstrated that ANOMA can achieve the same or even higher average maxmin rate with a lower feedback rate compared with NOMA. Moreover, we propose a quantizer optimization algorithm which applies to both NOMA and ANOMA. Simulation results show that the optimized quantizer significantly improves the average max-min rate compared with the conventional uniform quantizer, especially in the scenario with a low feedback rate.