Optimal Throughput Fairness Trade-offs for Downlink Non-Orthogonal Multiple Access over Fading Channels

TL;DR

This paper investigates the optimal resource allocation strategies for downlink NOMA systems over fading channels, balancing throughput and fairness under various channel state information scenarios, and compares NOMA with OMA.

Contribution

It provides a comprehensive analysis of optimal power and resource allocation for downlink NOMA with full and partial CSIT, including delay-tolerant and delay-limited cases, and benchmarks against OMA.

Findings

NOMA outperforms OMA in sum-rate and throughput fairness.

Optimal policies depend on CSIT quality and delay constraints.

Trade-offs between sum-rate, user fairness, and outage are characterized.

Abstract

Recently, non-orthogonal multiple access (NOMA) has attracted considerable interest as one of the 5G-enabling techniques. However, users with better channel conditions in downlink communications intrinsically benefits from NOMA thanks to successive decoding, judicious designs are required to guarantee user fairness. In this paper, a two-user downlink NOMA system over fading channels is considered. For delay-tolerant transmission, the average sum-rate is maximized subject to both average and peak power constraints as well as a minimum average user rate constraint. The optimal resource allocation is obtained using Lagrangian dual decomposition under full channel state information at the transmitter (CSIT), while an effective power allocation policy under partial CSIT is also developed based on analytical results. In parallel, for delay-limited transmission, the sum of delay-limited throughput (DLT) is maximized subject to a maximum allowable user outage constraint under full CSIT, and the analysis for the sum of DLT is also performed under partial CSIT. Furthermore, an optimal orthogonal multiple access (OMA) scheme is also studied as a benchmark to prove the superiority of NOMA over OMA under full CSIT. Finally, the theoretical analysis is verified by simulations via different trade-offs for the average sum-rate (sum-DLT) versus the minimum (maximum) average user rate (outage) requirement.