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Optimized Base Station Sleeping and Renewable Energy Procurement Scheme Using PSO

Author

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  • Qiang Wang

    (Guangdong University of Technology, Guangzhou, China)

  • Hai-Lin Liu

    (Guangdong University of Technology, Guangzhou, China)

Abstract

Energy efficiency of the wireless networks has drawn more and more attentions due to the requirement of the green communication. The base station sleeping strategy and resource allocation can effectively improve the energy efficiency for the wireless networks. Meanwhile, renewable energy is important to decrease the carbon emission. In this paper, the authors propose a joint BS sleeping strategy, resource allocation and renewable energy procurement scheme to maximize the profit of the network operators and minimize the carbon emission. Then, a joint optimization problem is formulated, which is a mixed integer programming problem. To solve it, they adopt the bi-velocity discrete particle swarm optimization (BVDPSO) algorithm to optimize the BS sleeping strategy. When the BS sleeping strategy is fixed, the authors propose an optimal algorithm based on Lagrange dual domain method to optimize the power allocation, subcarrier assignment and energy procurement. Numerical results illustrate the effectiveness of their proposed scheme and algorithm.

Suggested Citation

  • Qiang Wang & Hai-Lin Liu, 2017. "Optimized Base Station Sleeping and Renewable Energy Procurement Scheme Using PSO," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 8(1), pages 54-73, January.
    • Handle: RePEc:igg:jsir00:v:8:y:2017:i:1:p:54-73
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    Cited by:

    1. Fazli Wahid & Rozaida Ghazali & Lokman Hakim Ismail & Ali M. Algarwi Aseere, 2023. "An Optimal Neural Network for Hourly and Daily Energy Consumption Prediction in Buildings," International Journal of Swarm Intelligence Research (IJSIR), IGI Global, vol. 14(1), pages 1-13, January.

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