TY - JOUR
T1 - Distributed Energy-Saving Cellular Network Management Using Message-Passing
AU - Lee, Sang Hyun
AU - Sohn, Illsoo
N1 - Funding Information:
This work was supported in part by the National Research Foundation of Korea (NRF) funded by the Ministry of Science, ICT, and Future Planning of the Korean Government under Grant NRF-2015R1C1A1A01052529 and in part by the Basic Science Research Program through the NRF funded by the Ministry of Education under Grant NRF-2015R1D1A1A01057100.
Publisher Copyright:
© 2016 IEEE.
PY - 2017/1
Y1 - 2017/1
N2 - This paper presents a distributed energy-saving management strategy for green cellular networks. During off-peak periods, an energy-saving operation is activated. A subset of base stations (BSs) in the network enters an energy-saving state, i.e., switched-off mode, while satisfying traffic demands without discontinuity of user services. To this end, the remaining operating BSs should compensate for the coverage holes by taking over the responsibility of user service. Such a scenario can be formulated into a combinatorial optimization that maximizes the overall energy savings of the network. To address this computationally demanding task, we develop a distributed algorithm that provides an efficient solution by using a state-of-the-art technique based on a message-passing framework. The simulation results confirm considerable energy-saving gains over previously existing techniques and prove the viability for this strategy for self-organizing green cellular networks.
AB - This paper presents a distributed energy-saving management strategy for green cellular networks. During off-peak periods, an energy-saving operation is activated. A subset of base stations (BSs) in the network enters an energy-saving state, i.e., switched-off mode, while satisfying traffic demands without discontinuity of user services. To this end, the remaining operating BSs should compensate for the coverage holes by taking over the responsibility of user service. Such a scenario can be formulated into a combinatorial optimization that maximizes the overall energy savings of the network. To address this computationally demanding task, we develop a distributed algorithm that provides an efficient solution by using a state-of-the-art technique based on a message-passing framework. The simulation results confirm considerable energy-saving gains over previously existing techniques and prove the viability for this strategy for self-organizing green cellular networks.
KW - Energy-saving management
KW - green cellular networks
KW - message-passing algorithms
UR - http://www.scopus.com/inward/record.url?scp=85009877490&partnerID=8YFLogxK
U2 - 10.1109/TVT.2016.2536106
DO - 10.1109/TVT.2016.2536106
M3 - Article
AN - SCOPUS:85009877490
SN - 0018-9545
VL - 66
SP - 635
EP - 644
JO - IEEE Transactions on Vehicular Technology
JF - IEEE Transactions on Vehicular Technology
IS - 1
M1 - 7422166
ER -