Maximizing the energy efficiency using M-PSO in multi-hop UAV-IRS network for improved post-disaster emergency communication services

Natural disasters often damage the ground infrastructure, leading to communication failures that hamper emergency response efforts. Solutions dependent on ground-based infrastructure suffer from severe limitations in these scenarios owing to fixed positions, limited energy sources, and limited coverage. Existing methodologies, often relying on terrestrial relay points or fixed infrastructure, face challenges in adjusting to rapidly changing conditions in disaster areas, leading to ineffective energy consumption and limited communication range. To address this challenge, this work proposes a novel approach that employs Unmanned Aerial Vehicles (UAVs) alongside Intelligent Reflecting Surface (IRS) to deal with the connectivity challenges and provide energy-efficient communication services for Ground Users (GUs). The proposed framework includes a multi-hop communication model in which UAV-IRS units function as mobile relays, establishing strong connections between the affected area nodes and a temporary base station. We propose a Modified Particle Swarm Optimization (M-PSO) technique that optimally adjusts UAV placement and transmit power while the IRS phase shifts are independently optimized using Gradient Descent (GD) to enhance energy efficiency. Simulation results indicate that our setup significantly enhances communication capabilities in a disaster-stricken region, outperforming conventional methods for enhancing coverage and energy efficiency, thereby providing a resilient alternative for emergency communication in disaster-affected regions.