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Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency

Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency

Qiang Wang, Hai-Lin Liu
Copyright: © 2018 |Pages: 22
ISBN13: 9781522551348|ISBN10: 1522551344|EISBN13: 9781522551355
DOI: 10.4018/978-1-5225-5134-8.ch014
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MLA

Wang, Qiang, and Hai-Lin Liu. "Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency." Critical Developments and Applications of Swarm Intelligence, edited by Yuhui Shi, IGI Global, 2018, pp. 357-378. https://doi.org/10.4018/978-1-5225-5134-8.ch014

APA

Wang, Q. & Liu, H. (2018). Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency. In Y. Shi (Ed.), Critical Developments and Applications of Swarm Intelligence (pp. 357-378). IGI Global. https://doi.org/10.4018/978-1-5225-5134-8.ch014

Chicago

Wang, Qiang, and Hai-Lin Liu. "Optimized Base Station Sleeping and Smart Grid Energy Procurement Scheme to Improve Energy Efficiency." In Critical Developments and Applications of Swarm Intelligence, edited by Yuhui Shi, 357-378. Hershey, PA: IGI Global, 2018. https://doi.org/10.4018/978-1-5225-5134-8.ch014

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Abstract

In this chapter, the authors propose a joint BS sleeping strategy, resource allocation, and 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 the proposed scheme and algorithm.

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