Federated Deep Q-Learning and 5G load balancing

arXiv:2403.08813v1 Announce Type: cross
Abstract: Despite advances in cellular network technology, base station (BS) load balancing remains a persistent problem. Although centralized resource allocation methods can address the load balancing problem, it still remains an NP-hard problem. In this research, we study how federated deep Q learning can be used to inform each user equipment (UE) of the each BS's load conditions. Federated deep Q learning's load balancing enables intelligent UEs to independently select the best BS while also limiting …

abstract advances arxiv cellular cs.ai cs.lg cs.ma cs.ni network np-hard q-learning research study technology type