Design and Analysis of Energy Efficient Network for B5G Communications

Abstract

This thesis report focused on the design and analysis of the Energy Efficient (EE) network newlinefor beyond 5G (B5G) communications. In particular, we have designed massive newlinemultiple-input-multiple-output (MIMO) non-orthogonal multiple access (NOMA) heterogeneous newlinenetworks (HetNet) to optimize the EE for the Internet of Things (IoT). newlineLater, we designed and analyzed the EE for Intelligent Transportation System (ITS) newlineand IoT network by using Intelligent Reflecting Surfaces (IRS). The major contributions newlineof this thesis are described as follows. newlineFirst, we designed an energy-efficient MIMO-NOMA-aided IoT network to support newlinethe massive number of distributed users and IoT devices with seamless data transfer newlineand maintain connectivity between them. Massive MIMO has been identified as a newlinesuitable technology to implement the energy-efficient IoT network for B5G communications newlinedue to its distinct characteristics with a large number of antennas. However, newlineproviding fast data transfer and maintaining hyper-connectivity between the IoT devices newlinein B5G communications will bring the challenge of energy deficiency. Hence, we newlineconsidered a massive MIMO-NOMA-aided IoT network considering imperfect channel newlinestate information and practical power consumption at the transmitter. The far newlineusers of the base stations are selected to investigate the power consumption and quality newlineof service. Then, calculate the power consumption which is a non-convex function newlineand non-deterministic polynomial problem. The above problem is solved by applying newlinefractional programming properties, which converted the polynomial problem into newlinethe difference of convex function. And then we employed the successive convex approximation newlinetechnique to represent the non-convex to convex function. The Effective newlineiterative-based branch and the reduced bound process are utilized to solve the problem. newlineFrom numerical results, we observed that our implemented approach surpasses newlinex newlineprevious standard algorithms on the basis of convergence, energy efficiency, and user newlinefairness. newline