APPLICATIONS OF CONVEX OPTIMIZATION IN NON-ORTHOGONAL MULTIPLE ACCESS SYSTEMS

Abstract

This thesis contributes to the application of convex optimization in non-orthogonal multiple access systems. In this work, various practical constraints, such as grouping based on their QoS requirements and imperfect channel station information have been taken into consideration. The joint design of beamforming and power allocation in the downlink of the NOMA MIMO multiuser system is investigated, where the users are grouped based on their QoS requirements. The SDR is adopted to approach and showed that the optimal solutions are always rank one using simulation results. Also, a SCA algorithm is proposed based on the AGM inequality to perform the joint design of the beamforming vectors and the power allocation coefficients. Then, the research addressed the worst-case robust beamforming design for the MISO-NOMA downlink systems by taking into account the norm-bounded channel uncertainties. The S-procedure is exploited to reformulate the original non-convex problem into SDP form by recasting the original non-convex constraints into LMI form. Finally, a jointly optimizing beamformer and relay power are investigated for FD/HD cooperative NOMA with several optimization techniques. The study covers both perfect channel state information and the bounded imperfect channel state information. The objective is to maximize the achievable sum-rate for users within the beam. However, the original problem formulation is not convex. Therefore, reformulating the original problem into SDP form is required then several algorithms are applied to find a solution for the optimization problem.

Date of Award	31 Dec 2021
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Emad Alsusa (Supervisor) & Zhiguo Ding (Supervisor)