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Optimized sleep strategy based on clustering in dense heterogeneous networks - 2018

Optimized sleep strategy based on clustering in dense heterogeneous networks

Research Area:  Wireless Sensor Networks


As a large number of small base stations have been deployed in dense heterogeneous networks, the increasing cost of energy has become a challenging issue. In this paper, we propose an optimized clustering-based sleep strategy to release the power consumption and interference in the system. First, we group the small base stations with large interference as a cluster in which the binary particle swarm optimization (BPSO) algorithm is used to formulate a sleep strategy for small base stations in the clusters. Since the small base stations between clusters have less interference, the whole spectrum resources can be shared in all clusters and the orthogonal spectrum resources are allocated for the small base stations in the same cluster. The strategy effectively restrains the co-tier interference in the system. Furthermore, a separate sleep strategy is applied for each cluster to improve the sleep and activation efficiency of the small base stations. The simulation results show that the proposed sleep strategy can improve the satisfaction of user equipment and reduce the power consumption. As the increasing number of user equipment, the outage probability of the system can be reduced effectively.


Author(s) Name:  Jun Li, Hao Wang, Xiumin Wang and Zhengquan Li

Journal name:  EURASIP Journal on Wireless Communications and Networking

Conferrence name:  

Publisher name:  Springer

DOI:  10.1186/s13638-018-1311-2

Volume Information:   volume 2018, Article number: 290 (2018)