Joint User Clustering and Multi-Dimensional Resource Allocation in Downlink MIMO-NOMA Networks

Abstract

In this paper, a novel joint design of user clustering and multi-dimensional resource allocation based on effective capacity (EC) is proposed for the multi-cell downlink multiple-input-multiple-output (MIMO) non-orthogonal multiple access (NOMA) networks. First, we propose a dynamic user clustering algorithm to divide users into a number of clusters, where all users in one cluster share a single beamforming vector. Then, we adopt zero-forcing beamforming (ZFBF) to significantly eliminate the inter-cluster interference. Finally, we design a joint optimization of channel allocation and power allocation, which aims to maximize the sum-EC of all users. The joint optimization is formulated as an NP-hard problem. To make the problem tractable, we divide the problem into two subproblems. Then, we propose an alternating optimization algorithm to obtain a suboptimal solution. The numerical results demonstrate that compared with traditional algorithms our proposed algorithm can achieve significant capacity gain and simultaneously have low-computational complexity.