Terminal cooperation in next generation wireless networks: aerial and regional access networks

Throughout the years, progress of humankind has depended on the power of communication and over the decades, the ways of communication has witnessed mammoth changes. Specifically wireless communication in the last decade has completely revolutionized the way we communicate with each other. Smartphones have become an ubiquitous part of our life. With most operators throughout the world deploying fourth generation wireless communication systems, peculiar use cases and scenarios are being envisioned such as public safety networks, aerial networks, etc. to be addressed by the next generation wireless systems. Moreover, as urban areas are becoming saturated commercial network operators are looking for business cases to move towards the untapped regional areas. However, to deploy networks in regional areas economically, novel technologies and architectures need to be developed and investigated. In this thesis, we study the novel concept of terminal cooperation in the context of next generation wireless communication systems especially looking into aerial and regional access networks. In the first part of the thesis, we investigate the physical radio channel for device-to-device (D2D) communication which would help in enabling terminal cooperation in wireless networks. Specifically, we propose propagation model for D2D in rural areas using 922 MHz and 2466 MHz, a channel model for vehicular communications using 5.8 GHz and a propagation model for D2D using millimetre wave frequencies. In the second part of the thesis, we evaluate the coverage performance of aerial access networks using different technologies and develop algorithms to enhance the coverage using terminal cooperation in regional access networks. Specifically, we evaluate the performance of two different technologies, LTE and WiFi, in aerial access networks. We propose game-theoretic algorithms to enable terminal cooperation to enhance coverage in regional access networks and perform system level simulation to evaluate the proposed algorithms. In the last part of this thesis, we analyse and develop techniques to enhance energy efficiency in aerial access networks using terminal cooperation. Specifically, we propose a clustering algorithm called EECAN which improves the energy efficiency of the terrestrial nodes accessing the aerial base-station, a clustering algorithm based on Matern Hardcore Point Process which allows us to optimize cluster head spacing analytically and we further enhance this algorithm by including impairments introduced by the wireless channel. Throughout this thesis, we verify and validate our analytic results, algorithms and techniques with Monte-Carlo simulations of the considered scenarios. Most of the work presented in this thesis was published in-part or as a whole in conferences, journals, book-chapters, project reports or otherwise undergoing a review process. These publications and reports are highlighted in the course of the thesis. Lastly, we invite the reader to enjoy exploring this thesis and we hope that it will add more understanding to this promising new technology of terminal cooperation in aerial and regional access networks

Optimisation of a propagation model for last mile connectivity with low altitude platforms using machine learning

This thesis was submitted for the award of Doctor of Philosophy and was awarded by Brunel University LondonOur related research review on propagation models reveals six factors that are significant in last mile connectivity via LAP: path loss, elevation angle, LAP altitude, coverage area, power consumption, operation frequency, interference, and antenna type. These factors can help with monitoring system performance, network planning, coverage footprint, receivers’ line-of-sight, quality of service requirements, and data rates which may all vary in response to geomorphology characteristics. Several competing propagation models have been proposed over the years but whilst they collectively raise many shortcomings such as limited altitude up to few tens of meters, lack of cover across different environments, low perdition accuracy they also exhibit several advantages. Four propagation models, which are representatives of their types, have been selected since they exhibit advantages in relation to high altitude, wide coverage range, adaption across different terrains. In addition, all four have been extensively deployed in the past and as a result their correction factors have evolved over the years to yield extremely accurate results which makes the development and evaluation aspects of this research very precise. The four models are: ITU-R P.529-3, Okumura, Hata-Davidson, and ATG. The aim of this doctoral research is to design a new propagation model for last-mile connectivity using LAPs technology as an alternative to aerial base station that includes all six factors but does not exhibit any of the shortcomings of existing models. The new propagation model evolves from existing models using machine learning. The four models are first adapted to include the elevation angle alongside the multiple-input multiple-output diversity gain, our first novelty in propagation modelling. The four adapted models are then used as input in a Neural Network framework and their parameters are clustered in a Self-Organizing-Map using a minimax technique. The framework evolves an optimal propagation model that represents the main research contribution of this research. The optimal propagation model is deployed in two proof-of-concept applications, a wireless sensor network, and a cellular structure. The performance of the optimal model is evaluated and then validated against that of the four adapted models first in relation to predictions reported in the literature and then in the context of the two proof-of-concept applications. The predictions of the optimised model are significantly improved in comparison to those of the four adapted propagation models. Each of the two proof-of-concept applications also represent a research novelty.The Royal Saudi Embassy and the Saudi Cultural Bureau in London, and Taif University in the Kingdom of Saudi Arabia