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http://hdl.handle.net/10609/77107
Title: Spectral efficient and energy aware clustering in cellular networks
Author: Kollias, Georgios
Adelantado Freixer, Ferran  
Verikoukis, Christos
Others: Iquadrat Informática
Universitat Oberta de Catalunya. Internet Interdisciplinary Institute (IN3)
Centre Tecnològic de Telecomunicacions de Catalunya
Keywords: cellular networks
clustering
device-to-device (D2D)
clustering algorithms
Issue Date: 16-Jun-2017
Publisher: IEEE Transactions on Vehicular Technology
Citation: Kollias, G., Adelantado, F. & Verikoukis, C. (2017). Spectral Efficient and Energy Aware Clustering in Cellular Networks. IEEE Transactions on Vehicular Technology, 66(10), 9263-9274. doi: 10.1109/TVT.2017.2716387
Project identifier: info:eu-repo/grantAgreement/PITNGA-2012-317126
info:eu-repo/grantAgreement/TEC2015-71303-R
info:eu-repo/grantAgreement/TEC2014-60130-P
info:eu-repo/grantAgreement/2014 SGR 1551
Also see: https://ieeexplore.ieee.org/document/7951010
Abstract: The current and envisaged increase of cellular traffic poses new challenges to mobile network operators (MNO), who must densify their radio access networks (RAN) while maintaining low capital expenditure and operational expenditure to ensure long-term sustainability. In this context, this paper analyzes optimal clustering solutions based on device-to-device communications to mitigate partially or completely the need for MNOs to carry out extremely dense RAN deployments. Specifically, a low-complexity algorithm that enables the creation of spectral efficient clusters among users from different cells, denoted as enhanced clustering optimization for resources' efficiency is presented. Due to the imbalance between uplink and downlink traffic, a complementary algorithm, known as clustering algorithm for load balancing, is also proposed to create nonspectral efficient clusters when they result in a capacity increase. Finally, in order to alleviate the energy overconsumption suffered by cluster heads, the clustering energy efficient algorithm (CEEa) is also designed to manage the tradeoff between the capacity enhancement and the early battery drain of some users. Results show that the proposed algorithms increase the network capacity and outperform existing solutions, while, at the same time, CEEa is able to handle the cluster heads energy overconsumption.
Language: English
URI: http://hdl.handle.net/10609/77107
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