Optimizing Energy-Efficient Non-Terrestrial Networks with HAPs and UAVs for Enhanced Connectivity in Rural and Disaster-Affected Areas

The increasing demand for reliable high-speed connectivity in remote and disaster-stricken areas presents significant challenges for traditional terrestrial networks. Non-Terrestrial Networks (NTNs), consisting of High Altitude Platforms (HAPs), Unmanned Aerial Vehicles (UAVs), and Ground Base Stations (GBSs), offer a promising solution for extending coverage and improving data rates. This paper presents an energy-efficient optimization framework for user association and power allocation in a multilayer NTN architecture. The proposed approach seeks to minimize the total power consumption while ensuring that all users meet their Quality of Service (QoS) requirements. We model the system using a three-layer architecture, where users are dynamically associated with HAPs, UAVs, or GBSs, depending on their location and data rate requirements. The optimization problem is formulated as a mixed-integer nonlinear programming (MINLP) problem, and we propose a convex approximation to address its complexity. Simulation results demonstrate that our framework significantly reduces power consumption while maintaining high data rates, making it suitable for use in energy-constrained environments such as rural and disaster-affected regions.