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Optimisation of a Propagation Model for Last Mile Connectivity with Low Altitude Platforms Using Machine Learning

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Optimisation of a Propagation Model for Last Mile Connectivity with Low Altitude Platforms Using Machine Learning Optimisation of a Propagation Model for Last Mile Connectivity with Low Altitude Platforms using Machine Learning A thesis submitted for the degree of Doctor of Philosophy By Faris Abdullah Almalki BSc, MSc College of Engineering Design and Physical Sciences Brunel University London December 2017 i Abstract Our 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. i Acknowledgements First and foremost, I would like to thank God Almighty for giving me the ability and strength to complete this thesis. It is my pleasure to thank great people who made this thesis possible. Predominantly, I would like to express my sincere gratitude to my principal supervisor Professor Marios Angelides for giving me this great opportunity to pursue my PhD; during which he provided an excellent research atmosphere and immense knowledge. I also would like to thank him for his patience, motivation, guidance, and experience that significantly added to my research skills. In addition to his continuous encouragement to engage with wider research community by attending international conferences, participating in scientific workshops, and submitting research work to respected journals. My thanks extended to my researcher development advisor, and annual panel review members: for their great mentor and valuable comments during the course of my PhD program. I would also like to thank the anonymous reviewers that spent considerable time reading and commenting on my published works. I acknowledge the contribution of full financial support given by the Royal Saudi Embassy and the Saudi Cultural Bureau in London, as well as Taif University back in the Kingdom of Saudi Arabia whom gave me a scholarship to pursue my PhD study, and funding me to present my work in three international conferences. I am in debt to my beloved wife the entrepreneur Bushra for her encouragement, and for being tremendously supportive during my PhD. My endless gratitude to my father Professor Abdullah for opening my eyes to the charm of science and for inculcating the love of research, and to my mother Ms Amani for her immeasurable care, love and prayers she gave me. Extended thanks to my brother Dr Fahad and sisters Aljoharah, Alanoud, Dr Alhanouf, and Almaha for their great support, constant encouragement and love that I have relied on during my studies. Last but certainly not least, thanks to my 4-year old daughter Judy who motivate me to be an awesome dad, and I always want to be successful and a great role model for her. During this work, many ideas, and laughs have been shared with my friend Abdullah Alotaibi, which will be memorable times. I wish the research work in the College of Engineering, Design and Physical Sciences at Brunel university London to continue and flourish many years to come. ii Author’s Declaration I hereby declare that this thesis is my own work and effort and that it has not been submitted anywhere for any award. Where other sources of information have been used, they have been acknowledged. Faris Abdullah Almalki December 2017 iii List of Publications and Participations in Students Conferences Journal • F. A. Almalki, M. C. Angelides, “Optimization of a Propagation Model for Last-Mile Connectivity using a Low Altitude Platform”, under consideration • S. Alsamhi, F. A. Almalki, M. C. Angelides, S. Gapta, O. Ma, "Tethered Balloon Technology for Emergency Communication and Disaster Relief Deployment", Springer Telecommunication Systems, forthcoming. Conferences Proceedings • J. Cole, F. A. Almalki, and P. R. Young, "Chipless RF Liquid Sensor," 2015 IEEE International Microwave and RF Conference (IMaRC), Hyderabad, India, December 2015 • F. A. Almalki, M. C. Angelides, “Considering Near Space Platforms to Close the Coverage Gap in Wireless Communications; the Case of the Kingdom of Saudi Arabia”, IEEE 2016 - Future Technologies Conference (FTC), San Francisco, US, December 2016 • F. A. Almalki, M. C. Angelides, “Empirical Evolution of a Propagation Model for Low Altitude Platforms”, IEEE Computing Conference 2017, London, UK, July 2017 • F. A. Almalki, M. C. Angelides, “Propagation Modelling and Performance Assessment of Aerial Platforms Deployed During Emergencies”, 12th IEEE International Conference for Internet Technology and Secured Transactions (ICITST-2017), Cambridge, UK, December 2017 Participation in conferences • "Chipless RF Sensors for wireless Gas and Liquids Monitoring", 8th Saudi Students Conference in the UK, Imperial College London, February 2015. • “Three Minute Thesis Competition” organized by the Saudi Cultural Bureau in London and the Saudi Scientific Society in the UK, Imperial College London, June 2015, Second prize. • "Provision of Wireless Services in KSA using High Altitude Platforms", 9th Saudi Students Conference in the UK, Birmingham University, February 2016. • “Three Minute Thesis Competition Finals” organized by the Brunel Graduate School, March 2017, People’s choice third prize. iv Table of Contents Abstract …………………………………………………………………………………………………………………………………………………………….…..i Acknowledgement ………………………………………………………………………………………………………………………………………..........ii Author’s Declaration ………………………………………………………………………………………………………………………………….…………iii List of Publications and Participations in Students Conferences …………………………………………………………....……………..iv Table of Contents …………………………………………………………………………………………………………………………………………….......v Table of Figures …………………………………………………………………………………………………………………………………………….…….vii Table of Tables…………………………………………………………………………………………………………………………………………….….…….ix List of Acronyms…………………………………………………………………………………………………………………………………………………….x Chapter 1 : Last Mile Connectivity ................................................................................................................................... 1 1.1 Channel Modelling for Last Mile Connectivity using LAP ........................................................................................ 1 1.1.1 Propagation Path Loss Models .............................................................................................................................. 2 1.1.2 Elevation Angle ....................................................................................................................................................... 8 1.1.3 LAP Altitude and Coverage Area ............................................................................................................................ 9 1.1.4 Power Consumption ............................................................................................................................................. 16 1.1.5 Operational Frequency and Interference ........................................................................................................... 19 1.1.6 Antenna Specifications......................................................................................................................................... 23 1.2 LAP Evolution Worldwide .......................................................................................................................................
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