WCSE 2017
ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.216

Base Station Sleeping Mechanism for Reduced Delay Using Traffic Load Prediction

Ali Alnoman, Alagan Anpalagan

Abstract— Small cells are expected to be densely deployed in future networks to improve spectral and energy efficiencies. Due to the their small coverage and fluctuating number of users, the On-Off mechanism in small cell base stations (SBSs) has to be dynamically adapted in order to reduce the total energy consumption. However, the time delay associated with the transition from the Off to ON states can degrade the network performance. In this paper, a traffic prediction algorithm is proposed to perform a proactive SBS activation by anticipating future workload in SBS clusters using information of distance and received signal power of associated users. The distance and power measurements are smoothed using Haar wavelet filters to get a better approximation of the cluster’s traffic load. Each SBS operates in a self-organized manner in coordination with the neighbouring SBSs in that cluster wherein the information of associated users are exchanged among SBSs. The work aims to adaptively modify the On-Off mechanism while minimizing the time delay that is incurred from the wake-up process of SBSs. Simulation results show that the proposed algorithm can significantly reduce the delay with a slight increase in power consumption.

Index Terms— small cells, sleeping mechanism, wavelet, traffic prediction, delay, energy efficiency.

Ali Alnoman, Alagan Anpalagan
Ryerson University, CANADA

ISBN: 978-981-11-3671-9 DOI: 10.18178/wcse.2017.06.17Xsrc="http://www.wcse.org/uploadfile/2019/0823/20190823055609629.png" style="width: 120px; height: 68px;" />[Download]

Cite: Ali Alnoman, Alagan Anpalagan, "Base Station Sleeping Mechanism for Reduced Delay Using Traffic Load Prediction," Proceedings of 2017 the 7th International Workshop on Computer Science and Engineering, pp. 1240-1245, Beijing, 25-27 June, 2017.