Paper Info
Title
On the Energy Minimization of Heterogeneous Cloud Radio Access Networks.
Abstract
Next-generation 5G networks is the future of information networks and it will experience a tremendous growth in traffic. To meet such traffic demands, there is a necessity to increase the network capacity, which requires the deployment of ultra dense heterogeneous base stations (BSs). Nevertheless, BSs are very expensive and consume a significant amount of energy. Meanwhile, cloud radio access networks (C-RAN) has been proposed as an energy-efficient architecture that leverages the cloud computing technology where baseband processing is performed in the cloud. In addition, the BS sleeping is considered as a promising solution to conserving the network energy. This paper integrates the cloud technology and the BS sleeping approach. It also proposes an energy-efficient scheme for reducing energy consumption by switching off remote radio heads (RRHs) and idle BBUs using a greedy and first fit decreasing (FFD) bin packing algorithms, respectively. The number of RRHs and BBUs are minimized by matching the right amount of baseband computing load with traffic load. Simulation results demonstrate that the proposed scheme achieves an enhanced energy performance compared to the existing distributed long term evolution advanced (LTE-A) system.
Year
DOI
Venue
2016
10.1007/978-3-319-53850-1_22
Lecture Notes of the Institute for Computer Sciences, Social Informatics, and Telecommunications Engineering
Keywords
Field
DocType
Base station sleep,Bin packing,Cloud computing,C-RAN,Energy efficiency,HetNets,Virtualization
Virtualization,Base station,Baseband,Efficient energy use,Computer science,C-RAN,Computer network,Energy consumption,Bin packing problem,Cloud computing
Conference
Volume
ISSN
Citations 
186
1867-8211
0
PageRank 
References 
Authors
0.34
0
4
Name
Order
Citations
PageRank
Tshiamo Sigwele1264.39
Atm Shafiul Alam2212.50
Prashant Pillai356846.40
Yim-Fun Hu48316.86