2525718
doi
10.1109/PIMRC.2018.8580970
oai:zenodo.org:2525718
user-eu
Miozzo, Marco
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Dini, Paolo
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
Dynamic Functional Split Selection in Energy Harvesting Virtual Small Cells Using Temporal Difference Learning
Temesgene, Dagnachew, A.
Centre Tecnològic de Telecomunicacions de Catalunya (CTTC)
info:eu-repo/semantics/openAccess
Creative Commons Attribution 4.0 International
https://creativecommons.org/licenses/by/4.0/legalcode
energy harvesting
virtual small cells
functional split
CRAN
Reinforcement learning
SARSA
Q-learning
temporal difference
<p>Flexible functional split in Cloud Radio Access Network (CRAN) is a promising approach to overcome the capacity and latency challenges in the fronthaul. In such architecture, the baseband processing takes place partially at local base stations and the remaining processes are executed at the central cloud. On the other hand, we have seen a recent trend of powering base stations with ambient energy sources to achieve both environmental sustainability and profit advantages. As the base stations become smaller and deployed in densified manner, it is evident that baseband processing power consumption has a huge share in the total base station power consumption breakdown. Given that such base stations are powered by energy harvesting sources, energy availability conditions the decision on where to place each baseband function in the system. This work focuses on applying reinforcement learning techniques, in particular Q-learning and SARSA, for optimal placement of baseband functional split options in virtualized small cells that are solely powered by energy harvesting sources. In addition, a comparison of such online optimization solution with respect to offline performance bounds is provided.</p>
grant TEC2017-88373-R (5G-REFINE). © 2018 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Zenodo
2018-09-09
info:eu-repo/semantics/conferencePaper
2525717
user-eu
award_title=Sustainable CellulAr networks harVEstiNG ambient Energy; award_number=675891; award_identifiers_scheme=url; award_identifiers_identifier=https://cordis.europa.eu/projects/675891; funder_id=00k4n6c32; funder_name=European Commission;
1579540015.307614
224251
md5:8e3d0e4c033fa2124bebfdef668a1638
https://zenodo.org/records/2525718/files/Dynamic Functional Split Selection in Energy Harvesting.pdf
public