Learning Based Dynamic Cluster Reconfiguration for UAV Mobility Management with 3D Beamforming

Autor:	Meer, Irshad A., Besser, Karl-Ludwig, Ozger, Mustafa, Schupke, Dominic, Poor, H. Vincent, Cavdar, Cicek
Rok vydání:	2024
Předmět:	Computer Science - Information Theory Electrical Engineering and Systems Science - Signal Processing
Zdroj:	2024 IEEE International Conference on Machine Learning for Communication and Networking (ICMLCN), May 2024
Druh dokumentu:	Working Paper
DOI:	10.1109/ICMLCN59089.2024.10625071
Popis:	In modern cell-less wireless networks, mobility management is undergoing a significant transformation, transitioning from single-link handover management to a more adaptable multi-connectivity cluster reconfiguration approach, including often conflicting objectives like energy-efficient power allocation and satisfying varying reliability requirements. In this work, we address the challenge of dynamic clustering and power allocation for unmanned aerial vehicle (UAV) communication in wireless interference networks. Our objective encompasses meeting varying reliability demands, minimizing power consumption, and reducing the frequency of cluster reconfiguration. To achieve these objectives, we introduce a novel approach based on reinforcement learning using a masked soft actor-critic algorithm, specifically tailored for dynamic clustering and power allocation. Comment: 6 pages, 4 figures
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/2402.00224 Zobrazit plný text záznamu View this record from Arxiv