Energy Efficiency Maximization for UAV-Assisted Full-Duplex NOMA System: User Clustering and Resource Allocation

Abstract

In this paper, the problem of energy efficiency maximization of an unmanned-aerial-vehicle (UAV)-assisted full-duplex non-orthogonal-multiple-access (FD-NOMA) system is investigated. In order to reduce the interference among users in the considered system, we first propose a novel and less complex adaptive-geometric distribution (AGD) which adaptively maintain equal cluster size and allocate resource optimally among the users. Later, we formulate an optimization problem of energy efficiency maximization subject to the transmit power budget at the UAV for downlink (DL) users and for each uplink (UL) user and UAV placement. To transform the non-convex problem into convex one, we decouple the original optimization problem into different sub-problems in which the problems of power allocation and UAV placement are alternatively solved using Dinkelbach's algorithm with successive convex approximation (SCA) and particle swarm optimization (PSO), respectively. Later, the unified solution for optimal power allocation and UAV placement is proposed based on block-coordinate descent (BCD) algorithm. Extensive simulation results validate the superiority of the proposed AGD clustering based proposed algorithm for UAV-assisted FD-NOMA system over the conventional clustering and other orthogonal schemes.