Paper Info
Title
A Self-Organizing Base Station Sleeping Strategy In Small Cell Networks Using Local Stable Matching Games
Abstract
A distributed small-base stations (s-BSs) sleeping approach is proposed for optimizing energy efficiency (EE) in small cell networks (SCNs). Different from the existing studies, the associating preferences of both s-BSs and user equipments (UEs) are considered to enhance the flexibility of optimization. The SCNs sleeping problems are modeled as matching markets. The s-BSs sleeping problem is disassembled into two subproblems: optimization of the associations and turning off of the superfluous s-BSs. Based on the matching game theory, we put forward a Matching Game Based UE Association Algorithm (MGBAA) in settling the first sub-problem and a local matching sleeping algorithm (LMSA) in solving the second. The proposed sleeping strategy optimizes the irrational associations as well as moderates the redundant s-BSs without whittling down network throughput. The simulation results verify that the suggested sleeping approach deployment scheme surpasses the existing cell planning scheme with the objective of the energy efficiency ratio (EER) under various scenarios.
Year
DOI
Venue
2018
10.1007/978-3-319-94268-1_45
WIRELESS ALGORITHMS, SYSTEMS, AND APPLICATIONS (WASA 2018)
Keywords
Field
DocType
Sleeping strategy, Matching game, Small cell networks
Base station,Matching game,Software deployment,Efficient energy use,Computer science,Local matching,Small cell,Throughput,Distributed computing
Conference
Volume
ISSN
Citations 
10874
0302-9743
0
PageRank 
References 
Authors
0.34
19
4
Name
Order
Citations
PageRank
Yiwei Xu100.34
panlong yang245862.73
Jian Gong33612.67
Kan Niu400.34