Traffic-Aware Energy-Saving Base Station Sleeping and Clustering in Cooperative Networks

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We consider energy efficient base station (BS) sleeping and clustering problems in cooperative cellular networks, where clusters of base stations jointly transmit to users. Our key idea of energy saving is to exploit spatio-temporal fluctuation of traffic demand, and use minimal energy to provide achievable data rate only slightly greater than varying traffic demand. However, it is highly challenging to design traffic-aware algorithms without the future traffic demand information. To overcome this difficulty, we develop joint BS sleeping and clustering algorithms using queue instead of the future traffic information. The queue length information captures spatio-temporal mismatch between traffic demand and offered data rate. For BS clustering problem, we propose an optimal algorithm under given BS sleep mode state that has polynomial complexity. We integrate the optimal clustering solution into the sleeping problem, which is a complex combinatorial problem, and develop a joint optimal clustering and sleeping algorithm with reduced complexity compared to the exhaustive search. We also develop a greedy algorithm that finds a near-optimal clustering and sleeping solution with polynomial complexity. Through extensive simulations, we show that the proposed algorithms can save significant energy when traffic load is low.
Publisher
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
Issue Date
2018-02
Language
English
Article Type
Article; Proceedings Paper
Keywords

DISTRIBUTED ANTENNA SYSTEMS; GREEN CELLULAR NETWORKS; HETEROGENEOUS NETWORKS; COMMUNICATION-SYSTEMS; MOBILE NETWORKS; DELAY TRADEOFFS; TRANSMISSION; INFRASTRUCTURE; PERSPECTIVE; PERFORMANCE

Citation

IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.17, no.2, pp.1173 - 1186

ISSN
1536-1276
DOI
10.1109/TWC.2017.2776916
URI
http://hdl.handle.net/10203/240611
Appears in Collection
EE-Journal Papers(저널논문)
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