Energy-Efficient Sensing Mechanism for Licensed-Assisted Access Under Non-Saturated Traffic Condition

Title
Energy-Efficient Sensing Mechanism for Licensed-Assisted Access Under Non-Saturated Traffic Condition
Author(s)
김용재; 박은혜; 송유재; 한영남
KIOST Author(s)
Song, Yujae(송유재)
Publication Year
2017-12-11
Abstract
This paper investigates the energy-efficiency oflicensed-assisted access (LAA) which enable long-term evolutionsystems to operate in unlicensed spectrum. Since Wi-Fi with802.11 n/ac is a typical radio access technology in the unlicensedspectrum, we consider a scenario that the LAA small-cell basestations (SCBSs) are deployed together with Wi-Fi access points.We propose three different listen-before-talk (LBT) schemesaccording to the channel sensing mechanisms for LAA SCBC,and establish Markov chain models for each scheme under nonsaturatedtraffic condition. Using these analytical models, theenergy-efficiencies of LAA SCBSs that perform the differentLBT schemes are investigated. We also propose the algorithmto obtain the optimal contention window size of LAA SCBSsby which total energy-efficiency of networks is maximized whilesatisfying the required energy-efficiency of both LAA and Wi-Finetworks. Numerical results show that the LBT scheme whichhas an efficient channel sensing mechanism outperforms theother LBT schemes for the energy-efficiency perspective.edspectrum, we consider a scenario that the LAA small-cell basestations (SCBSs) are deployed together with Wi-Fi access points.We propose three different listen-before-talk (LBT) schemesaccording to the channel sensing mechanisms for LAA SCBC,and establish Markov chain models for each scheme under nonsaturatedtraffic condition. Using these analytical models, theenergy-efficiencies of LAA SCBSs that perform the differentLBT schemes are investigated. We also propose the algorithmto obtain the optimal contention window size of LAA SCBSsby which total energy-efficiency of networks is maximized whilesatisfying the required energy-efficiency of both LAA and Wi-Finetworks. Numerical results show that the LBT scheme whichhas an efficient channel sensing mechanism outperforms theother LBT schemes for the energy-efficiency perspective.
URI
https://sciwatch.kiost.ac.kr/handle/2020.kiost/23521
Bibliographic Citation
Asia-Pacific Conference on Communications (APCC), pp.1 - 6, 2017
Publisher
IEEE
Type
Conference
Language
English
Publisher
IEEE
Related Researcher
Research Interests

Maritime 5G and B5G,Maritime IoT,Deep reinforcement learning and its maritime applications,차세대 해양통신,해양 IoT,심층강화학습 및 해양통신 적용

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