Enhancing Disaster Communication: Multi-UAV Optimization for Efficient Coverage

Abstract

Unmanned Aerial Vehicles (UAVs) have attracted significant attention in disaster-stricken areas due to their inherent simplicity and easy deployment. This research centers on strategically allocating UAVs within disaster zones, aiming to determine the most suitable UAV for each user by considering the maximum Signal-to-Noise Ratio (SNR) between the UAV and user. Following this, an optimization problem is formulated to identify optimal UAV locations that maximize energy efficiency. Employing successive convex optimization, we introduce an iterative method to address the optimization problem. The study consists of two phases. In the initial phase, we focus on selecting and optimizing UAV locations to enhance energy efficiency. Subsequently, in the second phase, we integrate the Simultaneous Wireless Information and Power Transfer (SWIPT) technique to further elevate energy efficiency. The proposed method also optimizes UAV height, leading to an improved and expanded coverage area. The results underscore the superior performance of this holistic approach in achieving heightened energy efficiency and augmenting coverage capabilities.