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Dynamic spectrum sharing for hybrid access in OFDMA-based cognitive femtocell networks
  • Deng, Qingyong ;
  • Li, Zhetao ;
  • Chen, Jiabei ;
  • Zeng, Fanzi ;
  • Wang, Hui Ming ;
  • Zhou, Liang ;
  • Choi, Young June
Citations

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Publication Year
2018-11-01
Publisher
Institute of Electrical and Electronics Engineers Inc.
Citation
IEEE Transactions on Vehicular Technology, Vol.67, pp.10830-10840
Keyword
AuctionCognitive femtocellDynamic spectrum sharingHybrid access
Mesh Keyword
auctionCognitive femtocellDynamic schedulingDynamic spectrum sharingFemtocell NetworksHybrid-accessResource managementUltra-fastVehicle dynamics
All Science Classification Codes (ASJC)
Automotive EngineeringAerospace EngineeringComputer Networks and CommunicationsElectrical and Electronic Engineering
Abstract
Cognitive femtocell has emerged as one of the promising ways to solve the indoor coverage and spectrum shortage problems in cellular networks. However, it is a challenge to motivate both macro base station and femtocell access points {FAPs} to adopt this hybrid access policy. In this paper, we propose a systematic dynamic spectrum sharing framework for hybrid access in orthogonal frequency-division multiple-access-based cognitive macro-femtocell networks. In this framework, the {MBS} offloads some macro user equipments {MUEs} to {FAP} to improve the transmission performance and save energy. In return, the MBS leases a portion of its spectrum to {FAP}. Then, the {FAP} can use a part of spectrum for its own transmission and use another part to serve {MUEs}. We design an auction-based approach where each {FAP} receives additional {MUE} as bidders, while MBS acts as auctioneer. We formulate the dynamic resource sharing as a sum utility maximization problem. Numerical results demonstrate that both the macro and femtocell could get benefit from our framework.
ISSN
0018-9545
Language
eng
URI
https://dspace.ajou.ac.kr/dev/handle/2018.oak/30369
DOI
https://doi.org/10.1109/tvt.2018.2869755
Fulltext

Type
Article
Funding
Manuscript received August 11, 2017; revised December 14, 2017 and July 22, 2018; accepted August 12, 2018. Date of publication September 13, 2018; date of current version November 12, 2018. This work was supported by the National Natural Science Foundation of China under Grants 61602398, 61671364, and 61571240. The review of this paper was coordinated by Prof. S. He. (Corresponding author: Zhetao Li.) Q. Deng is with the School of Information and Communication Engineering, Beijing University of Posts and Telecommunications, Beijing 100876, China, and also with the College of Information Engineering, Xiangtan University, Xiangtan 411105, China (e-mail:,dengqingyong@xtu.edu.cn).
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