Optimal base station sleeping in green cellular networks

A distributed cooperative framework based on game theory

Jianchao Zheng, Yueming Cai, Xianfu Chen, Rongpeng Li, Honggang Zhang

Research output: Contribution to journalArticleScientificpeer-review

47 Citations (Scopus)

Abstract

This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.
Original languageEnglish
Pages (from-to)4391-4406
JournalIEEE Transactions on Wireless Communications
Volume14
Issue number8
DOIs
Publication statusPublished - 2015
MoE publication typeA1 Journal article-refereed

Fingerprint

Game theory
Game Theory
Cellular Networks
Nash Equilibrium
Base stations
Game
Energy Saving
Traffic
Potential Games
Global Optimum
Self-organization
Energy Efficiency
Iterative Algorithm
Decentralized
Energy Consumption
Optimality
Theoretical Analysis
Energy conservation
Optimal Solution
Maximise

Keywords

  • base station sleeping
  • decentralized algorithm
  • distributed cooperation
  • energy efficiency
  • generalized Nash equilibrium
  • green cellular networks
  • potential game

Cite this

@article{a253ff1dae74498c8ca610e6f0ed54d7,
title = "Optimal base station sleeping in green cellular networks: A distributed cooperative framework based on game theory",
abstract = "This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.",
keywords = "base station sleeping, decentralized algorithm, distributed cooperation, energy efficiency, generalized Nash equilibrium, green cellular networks, potential game",
author = "Jianchao Zheng and Yueming Cai and Xianfu Chen and Rongpeng Li and Honggang Zhang",
note = "Project code: 101914",
year = "2015",
doi = "10.1109/TWC.2015.2420233",
language = "English",
volume = "14",
pages = "4391--4406",
journal = "IEEE Transactions on Wireless Communications",
issn = "1536-1276",
publisher = "Institute of Electrical and Electronic Engineers IEEE",
number = "8",

}

Optimal base station sleeping in green cellular networks : A distributed cooperative framework based on game theory. / Zheng, Jianchao; Cai, Yueming; Chen, Xianfu; Li, Rongpeng; Zhang, Honggang.

In: IEEE Transactions on Wireless Communications, Vol. 14, No. 8, 2015, p. 4391-4406.

Research output: Contribution to journalArticleScientificpeer-review

TY - JOUR

T1 - Optimal base station sleeping in green cellular networks

T2 - A distributed cooperative framework based on game theory

AU - Zheng, Jianchao

AU - Cai, Yueming

AU - Chen, Xianfu

AU - Li, Rongpeng

AU - Zhang, Honggang

N1 - Project code: 101914

PY - 2015

Y1 - 2015

N2 - This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.

AB - This paper proposes a distributed cooperative framework to improve the energy efficiency of green cellular networks. Based on the traffic load, neighboring base stations (BSs) cooperate to optimize the BS switching (sleeping) strategies so as to maximize the energy saving while guaranteeing users' minimal service requirements. The inter-BS cooperation is formulated following the principle of ecological self-organization. An interaction graph is defined to capture the network impact of the BS switching operation. Then, we formulate the problem of energy saving as a constrained graphical game, where each BS acts as a game player with the constraint of traffic load. The constrained graphical game is proved to be an exact constrained potential game. Furthermore, we prove the existence of a generalized Nash equilibrium (GNE), and the best GNE coincides with the optimal solution of total energy consumption minimization. Accordingly, we design a decentralized iterative algorithm to find the best GNE (i.e., the global optimum), where only local information exchange among the neighboring BSs is needed. Theoretical analysis and simulation results finally illustrate the convergence and optimality of the proposed algorithm.

KW - base station sleeping

KW - decentralized algorithm

KW - distributed cooperation

KW - energy efficiency

KW - generalized Nash equilibrium

KW - green cellular networks

KW - potential game

U2 - 10.1109/TWC.2015.2420233

DO - 10.1109/TWC.2015.2420233

M3 - Article

VL - 14

SP - 4391

EP - 4406

JO - IEEE Transactions on Wireless Communications

JF - IEEE Transactions on Wireless Communications

SN - 1536-1276

IS - 8

ER -