A Framework for Optimizing Multi-cell NOMA: Delivering Demand with Less Resource

TL;DR

This paper presents a comprehensive framework for optimizing multi-cell NOMA, focusing on user clustering and power allocation to improve resource efficiency while accounting for inter-cell interference.

Contribution

It introduces a general theoretical framework and algorithms for multi-cell NOMA optimization, extending prior work limited to single or dual base stations.

Findings

NOMA achieves significantly higher efficiency in multi-cell scenarios.

The proposed algorithms guarantee convergence to a global optimum for monotonic performance metrics.

Framework applicable to arbitrary network topologies.

Abstract

Non-orthogonal multiple access (NOMA) allows multiple users to simultaneously access the same time-frequency resource by using superposition coding and successive interference cancellation (SIC). Thus far, most papers on NOMA have focused on performance gain for one or sometimes two base stations. In this paper, we study multi-cell NOMA and provide a general framework for user clustering and power allocation, taking into account inter-cell interference, for optimizing resource allocation of NOMA in multi-cell networks of arbitrary topology. We provide a series of theoretical analysis, to algorithmically enable optimization approaches. The resulting algorithmic notion is very general. Namely, we prove that for any performance metric that monotonically increases in the cells' resource consumption, we have convergence guarantee for global optimum. We apply the framework with its algorithmic concept to a multi-cell scenario to demonstrate the gain of NOMA in achieving significantly higher efficiency.