I.3.7. Engineering
Saeed Khosroabadi; Hussein Aad Alaboodi
Abstract
In the context of advancing sixth-generation (6G) communication networks, ensuring high-quality user coverage across varying geographic landscapes remains a paramount objective. Terrestrial base stations conventionally provide this coverage; however, they are susceptible to disruption due to adverse ...
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In the context of advancing sixth-generation (6G) communication networks, ensuring high-quality user coverage across varying geographic landscapes remains a paramount objective. Terrestrial base stations conventionally provide this coverage; however, they are susceptible to disruption due to adverse environmental conditions. Consequently, the integration of airborne mobile stations is pivotal for continued user coverage support. Among the viable solutions for terrestrial station augmentation, the deployment of drone base stations (DBS) emerges as the optimal substitute. Nonetheless, the establishment of a drone-based infrastructure presents challenges in terms of time and cost efficiency. Thus, the strategic positioning of DBSs, aimed at maximizing user coverage while simultaneously minimizing path loss and the number of drones required, is essential to achieving efficient and high-quality service provisioning. This study introduces a novel and optimized DBS placement strategy utilizing the Marine Predators Algorithm (MPA)—a recent metaheuristic renowned for its potent resistance to entrapment in local optima. Through simulation, we demonstrate that our proposed methodology distinctly surpasses analogous approaches with regards to optimization of path loss and user coverage. Simulation outcomes reveal average path losses of 71.75 dB for the Gray Wolf Optimization (GWO), 75.78 dB for the Weighted Time-Based Non-Orthogonal Multiple Access (TW-NOMA), and a significantly reduced 56.13 dB for our proposed MPA-based method, thereby indicating a substantial decrease of at least 15 dB in path loss compared to current techniques.
