Enhancement of Intelligent and Reliable Wireless Communications for Space-Air-Ground Integrated Network

This dissertation represents comprehensive research in the domain of space-air-ground wireless communication systems, undertaken at the School of Engineering, University of Leicester. The study thoroughly examines the intricate aspects of advancing the intelligence and reliability of wireless communication links. It begins by assessing the technological applications of Unmanned Aerial Vehicles (UAVs), high altitude platforms (HAPs), Free Space Optical (FSO) communications, and satellite communications. The first part of research focuses on addressing the crucial challenges of line-of-sight (LOS) dependencies in FSO communication systems. An advanced model integrating reconfigurable intelligent surface (RIS) was developed to enable non-LOS communications, marking a significant advancement in the field. The system underwent rigorous performance testing, evaluating the asymptotic ergodic capacity and resilience against various environmental disruptions. A detailed analysis of fading coefficients, particularly emphasizing atmospheric turbulence and pointing error loss, was conducted. These coefficients were precisely modeled using Gamma-Gamma and Hoyt distribution fading, reflecting the complexities of atmospheric conditions and UAV operational instabilities. A comprehensive Monte Carlo simulation environment was utilized to confirm the alignment between theoretical predictions and simulation results, thus establishing the robustness of the model. The following study broadened to encompass further investigation into Free Space Optical (FSO) communications and the application of Unmanned Aerial Vehicles (UAVs), with a particular emphasis on optimization strategies. By using a UAV equipped with Reconfigurable Intelligent Surfaces (RIS), were instrumental in addressing the intricate challenges associated with atmospheric and pointing error losses. A novelty approach was adopted, employing Particle Swarm Optimization (PSO) to determine the most effective leading-angle of the RIS, thereby overcoming the pointing error loss. This was complemented by the adoption of Proximal Policy Optimization (PPO) for the refinement of UAV trajectory optimization. The efficiency of this methodology was corroborated through comprehensive simulations, which revealed a notable enhancement in the average capacity of the system. These findings represent a significant stride in the realm of FSO communication optimization. Subsequently, the research introduced a secure transmission framework for RIS-aided non-terrestrial networks. Based on a practical phase-dependent model, the framework employed full-duplex transmission schemes at relay nodes, significantly reducing long-range eavesdropping and enhancing inter-node security. A deep cascade correlation learning (DCCL) algorithm was used to navigate the complexities of non-convex optimization, optimizing the joint RIS reflection coefficient and relay selection processes. Simulation assessments showed a marked improvement in secrecy capacity, surpassing conventional methods and strengthening the security of communication channels. The concluding chapter of the research explores space-air-ground integrated networks (SAGIN), highlighting the need for a shift in current communication methodologies. To address the limitations of existing FSO communications, especially their susceptibility to atmospheric disruptions and high energy consumption, an RF/FSO hybrid model supported by high-altitude platforms (HAPS) equipped with RIS was proposed. This model aimed to improve signal reliability and continuity, assessed through outage probability as performance benchmarks. Comparative analyses demonstrated the model’s superiority over traditional communication payloads, with reduced processing delays and energy expenditure. In conclusion, this thesis offers an exhaustive exploration in the field of wireless communications for autonomous vehicles, blending practical challenges with innovative solutions. It introduces novel techniques using UAVs and HAPs as autonomous platforms, along with advanced communication technologies like FSO and RIS, enhancing the reliability and security of wireless systems. The study systematically builds upon enhancing the performance of wireless communication links and integrating different networks. The findings, substantiated through simulations and detailed analysis, show significant improvements over existing methods. This work represents a valuable contribution to the field, proposing practical advancements with substantial benefits for real-world applications.