JOURNAL ARTICLE

Energy-optimal probabilistic base station sleeping under a separation network architecture

Abstract

To further improve energy efficiency from the view of the whole network, a separation architecture has been proposed, where the control plane and data plane are separated and implemented by different base stations. Under this architecture, the data base stations (DBS) can be turned off adaptively according to the traffic load while signaling base stations (SBS) provide the guarantee of coverage. A key issue of this architecture is the design of effective BS sleeping mechanisms, which should guarantee the quality of service (QoS) and minimize network power consumption. In this paper, a probabilistic DBS sleeping mechanism is proposed and optimized under the separation architecture. Users within the sleeping DBSs are offloaded to SBSs for QoS guarantee. An optimization problem is formulated, where the sleeping probability and spectrum resource allocation are jointly optimized to minimize network power consumption. The optimal BS sleeping scheme is found to be threshold-based. When the ratio of sleeping DBSs is below a certain threshold which depends on the traffic load, the lightly-loaded DBSs should be turned off first; otherwise, only the heavily loaded DBSs go into sleep. Numerical results show nearly 30% energy can be saved under a typical daily traffic profile, and there exists a tradeoff between energy saving and network capacity.

Keywords:
Computer science Probabilistic logic Base station Quality of service Energy consumption Computer network Resource allocation Efficient energy use Network architecture Engineering Artificial intelligence

Metrics

34
Cited By
3.33
FWCI (Field Weighted Citation Impact)
11
Refs
0.94
Citation Normalized Percentile
Is in top 1%
Is in top 10%

Citation History

Topics

Advanced MIMO Systems Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Advanced Wireless Network Optimization
Physical Sciences →  Engineering →  Electrical and Electronic Engineering
Software-Defined Networks and 5G
Physical Sciences →  Computer Science →  Computer Networks and Communications

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