Massive Connection Aware Effective Rate Optimization in NOMA Based Small Cell Networks

Abstract

NOMA based small cell network is a promising framework to support massive connection and high throughput. In this paper, massive connection requirement is taken into account in a downlink NOMA based small cell network, where the locations of small cell base stations and UEs are modeled by stochastic geometry. To evaluate the performance of the network, we adopt effective rate as a novel metric for overhead as well as validation reasons. In addition, an effective rate maximization problem by jointly optimize power allocation (PA) and QoS requirements is formulated. We propose to decouple the original problem into power allocation random initialization subproblem and effective rate enhancement subproblem, in order to develop a suboptimal resource allocation algorithm. Finally, the effectiveness and convergence of the proposed algorithm are confirmed by numerical results. We show that: 1) optimal solutions prefer to assign higher target SINR requirements to some UEs with worse channel condition from a perspective of whole UE cluster; 2) the random PA initialization has significant effect on the performance of the algorithm.