Non-Orthogonal Multiple Access (NOMA) in Content Centric Mobile Networks

Abstract

As the demand for rich multimedia content is expected to increase drastically over the years, the capacity of the current mobile network will not be able to cope with the tremendous growing traffic. Both non-orthogonal multiple access (NOMA) and content centric mobile network (CCMN) have emerged as the promising technologies which potentially addresses the growing traffic dominated by high-quality multimedia content. In this thesis, various techniques are developed to improve the sum rate performance of NOMA in CCMN, particularly multicast and cache-aided networks. First, the performance of NOMA-based layered multicast system is enhanced by designing a resource allocation scheme which considers the joint optimization of power allocation and subgrouping. In addition, the performance is further improved by employing beamforming techniques at the expense of additional computational cost, which can hinder its practical implementation. Hence, three low-complexity suboptimal beamforming algorithms are designed. Simulation results show the effectiveness of the resource allocation scheme in enhancing the performance. Moreover, the proposed scheme offers robust delivery of basic quality video to all users. Furthermore, all the proposed beamforming techniques offer significant performance gain over single-antenna multicast system. This thesis also studies the performance of NOMA and coded multicasting as the delivery approaches in cache-aided network with the aim of discovering which technique performs better under different pairing scenarios. Finally, a hybrid delivery scheme along with its resource allocation is developed in order to further improve the performance. Numerical results show that NOMA outperforms coded multicasting when the paired users' channel gains are highly distinctive, while coded multicasting is preferred when the paired users have similar channel gains. In addition, the hybrid scheme offers improved sum rate performance over NOMA and coded multicasting.

Date of Award	1 Aug 2021
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Emad Alsusa (Supervisor) & Daniel Ka Chun So (Supervisor)