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Dynamic Functional Split Selection in Energy Harvesting Virtual Small Cells Using Temporal Difference Learning.

, , and . PIMRC, page 1813-1819. IEEE, (2018)

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How Much Does It Cost to Train a Machine Learning Model over Distributed Data Sources?, , , and . CoRR, (2022)Energy sustainability of next generation cellular networks through learning techniques.. Polytechnic University of Catalonia, Spain, (2018)Optimal Placement of Baseband Functions for Energy Harvesting Virtual Small Cells., , , and . VTC Fall, page 1-6. IEEE, (2018)An open source model for the simulation of LTE handover scenarios and algorithms in ns-3., , , and . MSWiM, page 289-298. ACM, (2013)Spectrum-aware channel and PHY layer modeling for ns3., and . VALUETOOLS, page 2. ICST/ACM, (2009)Design of a unified multimedia-aware framework for resource allocation in LTE femtocells., , , and . MOBIWAC, page 159-162. ACM, (2011)Switch-On/Off Policies for Energy Harvesting Small Cells through Distributed Q-Learning., , , and . WCNC Workshops, page 1-6. IEEE, (2017)A lightweight and accurate link abstraction model for the simulation of LTE networks in ns-3., , , , and . MSWiM, page 55-60. ACM, (2012)Small cells, wireless backhaul and renewable energy: a solution for disaster aftermath communications., , , , and . CogART, page 52. ACM, (2011)Distributed and Multi-Task Learning at the Edge for Energy Efficient Radio Access Networks., , , and . IEEE Access, (2021)