Abstract
| Original language | English |
|---|---|
| Title of host publication | Proceedings of Globecom 2012 |
| Publisher | Institute of Electrical and Electronic Engineers IEEE |
| Pages | 1556-1561 |
| ISBN (Electronic) | 978-1-4673-0921-9 |
| ISBN (Print) | 978-1-4673-0920-2 |
| DOIs | |
| Publication status | Published - 2012 |
| MoE publication type | A4 Article in a conference publication |
| Event | IEEE Global Communications Conference, GLOBECOM 2012 - Anaheim, CA, United States Duration: 3 Dec 2012 → 7 Dec 2012 |
Conference
| Conference | IEEE Global Communications Conference, GLOBECOM 2012 |
|---|---|
| Abbreviated title | GLOBECOM 2012 |
| Country | United States |
| City | Anaheim, CA |
| Period | 3/12/12 → 7/12/12 |
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Energy saving through a learning framework in greener cellular radio access networks. / Li, R.; Zhao, Z.; Chen, Xianfu; Zhang, H.
Proceedings of Globecom 2012. Institute of Electrical and Electronic Engineers IEEE, 2012. p. 1556-1561.Research output: Chapter in Book/Report/Conference proceeding › Conference article in proceedings › Scientific › peer-review
TY - GEN
T1 - Energy saving through a learning framework in greener cellular radio access networks
AU - Li, R.
AU - Zhao, Z.
AU - Chen, Xianfu
AU - Zhang, H.
N1 - Project code: 43135
PY - 2012
Y1 - 2012
N2 - Recent works have validated the possibility of energy efficiency improvement in radio access networks (RAN), depending on dynamically turn on/off some base stations (BSs). In this paper, we extend the research over BS switching operation, matching up with traffic load variations. However, instead of depending on the predicted traffic loads, which is still quite challenging to precisely forecast, we formulate the traffic variation as a Markov decision process (MDP). Afterwards, in order to foresightedly minimize the energy consumption of RAN, we adopt the actor-critic method and design a reinforcement learning framework based BS switching operation scheme. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and prove the feasibility of significant energy efficiency improvement.
AB - Recent works have validated the possibility of energy efficiency improvement in radio access networks (RAN), depending on dynamically turn on/off some base stations (BSs). In this paper, we extend the research over BS switching operation, matching up with traffic load variations. However, instead of depending on the predicted traffic loads, which is still quite challenging to precisely forecast, we formulate the traffic variation as a Markov decision process (MDP). Afterwards, in order to foresightedly minimize the energy consumption of RAN, we adopt the actor-critic method and design a reinforcement learning framework based BS switching operation scheme. In the end, we evaluate our proposed scheme by extensive simulations under various practical configurations and prove the feasibility of significant energy efficiency improvement.
U2 - 10.1109/GLOCOM.2012.6503335
DO - 10.1109/GLOCOM.2012.6503335
M3 - Conference article in proceedings
SN - 978-1-4673-0920-2
SP - 1556
EP - 1561
BT - Proceedings of Globecom 2012
PB - Institute of Electrical and Electronic Engineers IEEE
ER -