Traffic aware sleeping strategies for Small-Cell Base Station in the Ultra dense 5G Small Cell Networks

Abstract

The 5G ultra-dense small cell network plays a key role in the future generation of mobile networks. It provides high data rate, seamless coverage and reliable services for wireless communication in an ultra-dense network. The dense deployment of small cells is needed to control forthcoming traffic demands which leads to enhance the operational cost and reduces the energy efficiency. One way to improve the energy efficiency is by using the sleeping strategy of small cell by transferring the traffic load of a small cell to other small cells. This work proposes an Initial Connection algorithm for establishing an initial association between the UEs and small base stations (s-BSs) while considering the UE preference. The Initial Connection algorithm creates a connected network. Moreover, the proposed Load Sharing Based Sleep Approach (LSBSA) algorithm performs small cells sleeping on the connected network which results in the deployment of s-BSs. The proposed Initial Connection and LSBSA algorithms are implemented and evaluated in MATLAB for different mobile data traffic. Also, various UEs distribution scenarios are considered. The results are demonstrated that the proposed approaches improve network performance in terms of energy efficiency of the small cell network by deploying the optimal number of active s-BSs.