Please use this identifier to cite or link to this item: http://bura.brunel.ac.uk/handle/2438/17865
Title: Planning a C-RAN deployment for the next generation cellular networks
Authors: Al-Zubaedi, Wesam Hamid Abdulhussein
Advisors: Al-Raweshidy, H
Zobaa, A
Keywords: Fronthaul;5G;Cloud Radio Access Network
Issue Date: 2019
Publisher: Brunel University London
Abstract: Over the next decade, it is expected that demand for high data rates will increase dramatically by increasing the connection of smart devices and the introduction of new applications and services. This will lead to increase the complexity of the management and operation of current network. Therefore, Cloud Radio Access Network (C-RAN) architecture has been innovated as one of the Fifth Generation (5G) solutions to simplify the management and control of the future mobile network. This thesis is focused on power consumption model and analysis, saving energy and load balancing in C-RAN. Moreover, this thesis is introduced an approach to solve the network planning issue of the next generation of the cellular network. A new power consumption model for C-RAN architecture is proposed based on the virtualisation of a Base Band Unit (BBU). A parametrised and minimised linear power model is provided, which covers the individual aspects in a C-RAN system that are relevant to power consumption. Moreover, in this work, an Orchestra Server (OS) is proposed in the BBU pool that hosts an intelligent algorithm to optimise the configuration of the BBUs to the proper Remote Radio Heads (RRHs) in varying traffic load. The scheme is based on the New Minimum Bin Slack (NMBS) algorithm, which aims to find a set of users that fits into the BBU capacity, with load balancing among them as much as possible. Moreover, a technique is proposed for the network deployment problem which aims to satisfy C-RAN planning by optimizing placement and minimum required number of the BBU pool in the network. The Quasi-Newton Method (QNM) algorithm is proposed to find the optimal BBU pool location in the proposed network. Minimum required number of the BBU pool for the proposed network is determined with respect to the fronthaul size limitations. The Particle Swarm Optimization (PSO) algorithm has been applied for the proposed network to group the RRHs into multiple sub-networks with fair RRHs distributions. Moreover, this work is showed the RRHs coverage area is very considerable value in determining the size of fronthual link and BBU pool position. Furthermore, an approach for allocating existing 4G installed network radio access nodes to multiple BBU pools, which is proposed to deploy 5G C-RAN and improve the offered Network Quality of Service (NQoS). The proposed approach involves performing four sequent algorithms starting with i) radio access node clustering based on the PSO algorithm then, ii) model selection Bayesian Information Criterion (BIC) through iii) a measure of spread technique then ends by, iv) Voronoi tessellation, which is used to consider a Dynamic C-RAN (DC-RAN) operation, that adaptively adjusts the main RRH coverage range according to the traffic load required as well as providing energy saving.
Description: This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University London
URI: http://bura.brunel.ac.uk/handle/2438/17865
Appears in Collections:Electronic and Computer Engineering
Dept of Electronic and Computer Engineering Theses

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