NDLI: TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

Content Provider	IEEE Xplore Digital Library
Author	Rongpeng Li Zhifeng Zhao Xianfu Chen Palicot, J. Honggang Zhang
Copyright Year	2002
Abstract	Recent works have validated the possibility of improving energy efficiency in radio access networks (RANs), achieved by dynamically turning on/off some base stations (BSs). In this paper, we extend the research over BS switching operations, which should match up with traffic load variations. Instead of depending on the dynamic traffic loads which are still quite challenging to precisely forecast, we firstly formulate the traffic variations as a Markov decision process. Afterwards, in order to foresightedly minimize the energy consumption of RANs, we design a reinforcement learning framework based BS switching operation scheme. Furthermore, to speed up the ongoing learning process, a transfer actor-critic algorithm (TACT), which utilizes the transferred learning expertise in historical periods or neighboring regions, is proposed and provably converges. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and show that the proposed TACT algorithm contributes to a performance jump start and demonstrates the feasibility of significant energy efficiency improvement at the expense of tolerable delay performance.
Starting Page	2000
Ending Page	2011
Page Count	12
File Size	1800878
File Format	PDF
ISSN	15361276
Volume Number	13
Issue Number	4
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-01-01
Publisher Place	U.S.A.
Access Restriction	One Nation One Subscription (ONOS)
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Switches Energy consumption Radio access networks Algorithm design and analysis Learning (artificial intelligence) Heuristic algorithms actor-critic algorithm base stations sleeping mode green communications energy saving reinforcement learning transfer learning
Content Type	Text
Resource Type	Article
Subject	Applied Mathematics Electrical and Electronic Engineering Computer Science Applications

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

1TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

A Transfer Games Actor–Critic Learning Framework for Anti-Jamming in Multi-Channel Cognitive Radio Networks

Reinforcement learning approach to dynamic activation of base station resources in wireless networks

Base station switching based dynamic energy saving algorithm for cellular networks

Green cellular networking

Low consumption home femto base stations

A Novel Energy Saving Scheme Based on Base Stations Dynamic Configuration in Green Cellular Networks

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

Similar Documents

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

1TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks

A Transfer Games Actor–Critic Learning Framework for Anti-Jamming in Multi-Channel Cognitive Radio Networks

Reinforcement learning approach to dynamic activation of base station resources in wireless networks

Base station switching based dynamic energy saving algorithm for cellular networks

Green cellular networking

Low consumption home femto base stations

A Novel Energy Saving Scheme Based on Base Stations Dynamic Configuration in Green Cellular Networks

TACT: A Transfer Actor-Critic Learning Framework for Energy Saving in Cellular Radio Access Networks