title: Beamforming and optimisation of RIS-assisted UAV communication systems
Creators: name: Abualhayja’a, Mohammad Omar Tawfiq
Publisher: name: University of Glasgow
Year: 2024

description: With the rapid development of wireless technologies, unmanned aerial vehicles (UAVs) are expected to play an increasingly significant role in future mobile networks. Thanks to their low cost, small size, high mobility, and deployment flexibility. UAVs are becoming an attractive solution for various wireless communication applications. UAVs can be utilised as aerial communication platforms for enhancing the coverage, capacity, and energy efficiency of wireless networks. However, to effectively utilise the UAV technology in wireless networks, various technical challenges related to communication links reliability, UAV placement, and trajectory planning need to be addressed. Reconfigurable intelligent surfaces (RISs) may be integrated into UAV networks to overcome some of the UAV communications key challenges, and at the same time, enhance the overall performance of the network in terms of spectrum and energy efficiency. This is due to the ability of the RISs to turn the wireless environment into a controlled entity by shaping and fully manipulating its EM responses. To this end, the main goal of this thesis is to provide an analytical framework for analysing, designing, and optimising RISassisted UAV communication systems. In this context, this thesis first begins by investigating the fundamental characteristics of UAV technology, major paradigms for UAV integration into wireless networks and their potential applications, and addresses open problems and challenges in UAV communications. It then examines RIS technology within the emerging concept of smart radio environments (SRE), its structure and applications, and sheds light on the potential RIS-assisted UAV system scenarios. The main theme of the first two contributions centres around the performance evaluation of RIS-assisted UAV communication systems. In the first contribution, RIS-assisted UAV communication systems are studied and analysed through the development of a comprehensive mathematical framework for communication systems performance evaluation. Three different system scenarios are considered to assess the impact of RIS on UAV communications. This framework includes the derivation of accurate closed-form approximations for signal-to-noise ratio (SNR) distributions for the proposed systems, as well as analytical expressions for outage probabilities and average bit-error-rate (BER). The findings demonstrate that RIS can significantly enhance the performance of UAV communication systems by ensuring reliable connections, particularly in complex and dynamic environments where maintaining line-of-sight (LoS) connections may not always be feasible or optimal. Since power efficiency is a critical aspect of green communication, aimed at reducing the carbon footprint of telecommunication networks, the second contribution explores the integration of RIS into wireless networks as a novel passive technology to enhance energy efficiency. A comprehensive optimisation framework is developed to minimise the total power consumption of RIS-assisted communication systems by optimising the number of RIS elements and their phase shifts while adhering to essential communication constraints. Simulation results provide valuable insights into the intricate dynamics of RIS-assisted communications system design by illustrating the impact of control circuit components, control boards, and dynamic power dissipation factors. Results also highlight the significant advantages of RIS deployment in terms of power efficiency, especially at higher data rates. Additionally, the study emphasises the importance of considering alternative relay techniques when customising wireless communication systems to meet specific rate requirements and operating conditions. Finally, the third contribution proposes an application scenario for integrated RIS-assisted UAV communications, specifically focusing on an RIS-assisted UAV Internet of Things (IoT) data collection framework. This framework is optimised to maximise performance in terms of the number of served IoT devices and their data rates. The proposed algorithm presents a promising approach to address the growing demand for efficient data collection in IoT networks. Simulation results reveal the potential of RIS-assisted UAV solutions in meeting the increasing demands of wireless IoT networks. By coordinating the RIS phase shift matrix and UAV trajectory planning, the framework achieves significant enhancements in the number of served IoT devices and the achievable data rates.