Switch-On/Off Policies for Energy Harvesting Small Cells through Distributed Q-Learning

2017 IEEE Wireless Communications and Networking Conference Workshops, WCNCW 2017

Volumn , Issue , 2017, Pages

  Miozzo, Marco ^a   Giupponi, Lorenza ^a   Rossi, Michele ^b   Dini, Paolo ^a  

^a CENTRE TECNOLÒGIC DE TELECOMUNICACIONS DE CATALUNYA CTTC   (Spain)

^b UNIVERSITY OF PADOVA   (Italy)

Author keywords

[No Author keywords available]

Indexed keywords

ENERGY EFFICIENCY; ENERGY HARVESTING; ENERGY UTILIZATION; ENVIRONMENTAL IMPACT; MOBILE TELECOMMUNICATION SYSTEMS; MULTI AGENT SYSTEMS; NETWORK ARCHITECTURE; REINFORCEMENT LEARNING; SUSTAINABLE DEVELOPMENT; WIRELESS NETWORKS; WIRELESS TELECOMMUNICATION SYSTEMS;

ANCILLARY SERVICE; DISTRIBUTED Q-LEARNING; ELECTRICITY GRIDS; MASSIVE DEPLOYMENT; MOBILE OPERATORS; MULTI-AGENT Q-LEARNING; RENEWABLE ENERGIES; SWITCHING ALGORITHMS;

LEARNING ALGORITHMS;

EID: 85020204467     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/WCNCW.2017.7919075     Document Type: Conference Paper

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