الفهرس 
Massive MIMO and NOMA for 5G Systems and BeyondOnly 14 pages are availabe for public view
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Abstract
Abstract
The motivations for deploying energy and spectral-efficient network architectures are the high energy consumption and the need for more spectral resources in modern cellular networks. Also, the deployment of heterogeneous networks for densifying the existing networks enhances the capacity and the coverage. Spectrum allocation is very important for the in-band heterogeneous networks where different tiers operate at common frequencies. This work considers two network models. The first network model is the non-orthogonal multiple access (NOMA) supported heterogeneous network where the small base stations (SBs) reuse the resource blocks (RBs) of the above tier and communicate with small cell users (SCUs) through the NOMA technique. This work proposes resource allocation and power assignment solutions for optimizing the spectral efficiency (SE) of the SCUs while considering the issue of fairness. The other network model is the NOMA-based massive MIMO model. For this model, the energy efficiency (EE) optimization problem of the downlink is formulated and solved. The key method to solve the EE maximization problem is to decouple it into user pairing and efficient power allocation subproblems. This work studies the performance of three main pairing methods in NOMA-based networks: Hungarian, Gale-Shapley, and correlation-based approaches. Firstly, we provide a mathematical analysis for EE of downlink NOMA in a massive MIMO system for both line of sight (LOS) and non-line of sight (NLOS) channel models with perfect successive interference cancellation (SIC). Finally, the sequential convex programming (SCP) approach is used to tackle the power allocation problem. Simulation results of the heterogeneous network model show that the proposed cascaded resource allocation (CRA) algorithm based on the Hungarian algorithm for resource allocation outperforms the joint spectrum allocation and power control (JSAPCA-1) algorithm in terms of the spectral efficiency achieved by SCUs besides achieving a comparable level of interference experienced by macro cell users (MCUs). Also, simulation results of the NOMA-based scheme show that the Hungarian algorithm for pairing plus SCP for power allocation (Hungarian algorithm-SCP) achieves the highest EE among all the three pairing algorithms with identical performance to the joint user-resource block association with power allocation (joint user-RB PA) algorithm but with much lower computational complexity and outperforms NOMA SCP greedy algorithm (NOMA-SCP-GA).
In this thesis, a NOMA-supported heterogeneous network model, for short it is called the heterogeneous network model, is studied. The joint problem of power assignment and resource allocation for the SCUs in this network is modeled as a proportional fairness utility optimization problem of SE. The resource allocation Kuhn-Munkres (RAKM) algorithm is proposed where the spectrum allocation process is performed based on Hungarian algorithm. Hence, each SB is assigned the resource block that maximizes its spectral efficiency.
In this thesis, the proposed power assignment solution contains two phases where the SCUs are assigned initial power values in the first phase. Then, the assigned power is updated by sequential convex programming and calculations of signal to interference plus noise ratio (SINR) proceed till convergence in the second phase.
The integration of the two parts of the joint problem is performed in the CRA algorithm where the power control solution is obtained according to the RAKM algorithm output to be applied to the output of the Hungarian algorithm.
In this thesis, we solve the EE optimization problem for downlink NOMA-based massive MIMO system, for short it will be named NOMA-based scheme, through decoupling into user pairing subproblem and fair power assignment subproblem for the reduction of complexity. Firstly, energy-efficient user pairing is studied for three different beamforming methods: zero forcing (ZF) beamforming, Minimum mean squared error (MMSE) beamforming, and Maximum ratio (MR) beamforming. Then, we mathematically formulate max-min EE into a non-convex fractional programming problem which is transformed into a sequence of subtractive form, followed by SCP approach to obtain the optimal solution.
In this thesis, we consider the evaluation of three different user-pairing approaches. Results are compared to obtain the optimal user pairing approach to maximize EE for downlink NOMA. We show how the pairing decisions affect the performance of the NOMA-based scheme.
In this thesis, we propose a novel power allocation scheme based on SCP to iteratively update the power assignment vector that will eventually optimize EE for the NOMA-based scheme.
Keywords: Fifth generation (5G), heterogeneous network, user pairing, non-orthogonal multiple access (NOMA), massive multiple input multiple output (MIMO), Hungarian algorithm, Gale-Shapley algorithm, and matching theory.