Downlink Non-Orthogonal Multiple Access (NOMA) in Poisson Networks

Abstract

A network model is considered, where Poisson distributed base stations transmit to N power-domain nonorthogonal multiple access (NOMA) users (TIEs) each that employ successive interference cancellation (SIC) for decoding. We propose three models for the clustering of NOMA TIEs and consider two different ordering techniques for the NOMA TIEs: mean signal power-based and instantaneous signal-to-intercell-interference-and-noise-ratio-based. For each technique, we present a signal-to-interference-and-noise ratio analysis for the coverage of the typical TIE. We plot the rate region for the two-user case and show that neither ordering technique is consistently superior to the other. We propose two efficient algorithms for finding a feasible resource allocation that maximize the cell sum rate R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tot</sub> , for general N, constrained to: 1) a minimum throughput T for each TIE, 2) identical throughput for all TIEs. We show the existence of: 1) an optimum N that maximizes the constrained R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tot</sub> given a set of network parameters and 2) a critical SIC level necessary for NOMA to outperform orthogonal multiple access. The results highlight the importance in choosing the network parameters N, the constraints, and the ordering technique to balance the R <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">tot</sub> and fairness requirements. We also show that interference-aware TIE clustering can significantly improve performance.