Resource and Location Optimization with GA in UAV-Supported Multicellular Networks: A Comparison of Greedy and Local Search ?IHA Destekli Çok Hücreli A?glarda GA ile Kaynak ve Konum Optimizasyonu: Greedy ve Yerel Arama Karşilaştirmasi
34th Signal Processing and Communications Applications Conference, SIU 2026, İstanbul, Turkey, 7 - 10 July 2026, (Full Text)
- Publication Type: Conference Paper / Full Text
- Doi Number: 10.1109/siu71813.2026.11636397
- City: İstanbul
- Country: Turkey
- Keywords: 3GPP channel model, genetic algorithm, greedy algorithm, location optimization, multi-cell networks, resource allocation, UAV
- Yıldız Technical University Affiliated: Yes
Abstract
In this study, subband assignment to base stations (BS) and simultaneous optimization of the three-dimensional positions of unmanned aerial vehicles (UAVs) in a multi-cell network supported by UAVs were performed using a genetic algorithm (GA). The aim of the optimization is to maximize a total speed metric that prioritizes edge users (UEs) (based on max-min fairness) at the cell edge. The proposed GA was compared with improved greedy and greedy+local lookup methods. Simulations for different cell radii show that the GA outperforms both methods in terms of total speed and max-min fairness; it improves service quality, especially in large cells, by more effectively directing edge users to UAVs.