TY - GEN
T1 - On the energy minimization of heterogeneous cloud radio access networks
AU - Sigwele, Tshiamo
AU - Alam, Atm Shafiul
AU - Pillai, Prashant
AU - Hu, Yim Fun
N1 - Publisher Copyright:
© ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering 2017.
PY - 2017
Y1 - 2017
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=85018570538&partnerID=8YFLogxK
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U2 - 10.1007/978-3-319-53850-1_22
DO - 10.1007/978-3-319-53850-1_22
M3 - Conference contribution
AN - SCOPUS:85018570538
SN - 9783319538495
T3 - Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST
SP - 223
EP - 234
BT - Wireless and Satellite Systems - 8th International Conference, WiSATS 2016, Proceedings
A2 - Pillai, Prashant
A2 - Otung, Ifiok
A2 - Eleftherakis, George
A2 - Giambene, Giovanni
PB - Springer Verlag
T2 - 8th International Conference on Wireless and Satellite Systems, WiSATS 2016
Y2 - 19 September 2016 through 20 September 2016
ER -