An Activity Management Algorithm for Improving Energy Efficiency of Small Cell Base Stations in 5G Heterogeneous Networks

TL;DR

This paper introduces an activity management algorithm with a smart sleep strategy for pico base stations in 5G HetNets, significantly enhancing energy and spectral efficiency by dynamically activating or deactivating small cells based on user demand.

Contribution

The paper proposes a novel activity management algorithm employing a smart sleep strategy for pico base stations, improving energy and spectral efficiency in 5G HetNets.

Findings

Energy efficiency increased by 20%

Average bit rates increased by 29%

Effective in different network architectures and user distributions

Abstract

Heterogeneous networks (HetNets) are proposed in order to meet the increasing demand for next generation cellular wireless networks, but they also increase the energy consumption of the base stations. In this paper, an activity management algorithm for improving the energy efficiency of HetNets is proposed. A smart sleep strategy is employed for the operator deployed pico base stations to enter sleep and active modes. According to that strategy, when the number of users exceeds the turn on threshold, the pico node becomes active and when the number of users drop below the turn off threshold, it goes into sleep mode. Mobile users dynamically enter and leave the cells, triggering the activation and deactivation of pico base stations. The performance of the system is examined for three different cellular network architectures: cell on edge (COE), uniformly distributed cells (UDC) and macro cell only network (MoNet). Two different user distributions are considered: uniform and hotspot. The effects of number of hotspot users and sleep energies of pico nodes on the energy efficiency are also investigated. The proposed activity management algorithm increases the energy efficiency, measured in bits/J, by $20\%$. The average bit rates achieved by HetNet users increase by $29\%$ compared with the MoNet architecture. Thus, the proposed activity control algorithm increases the spectral efficiency of the network while consuming the energy more efficiently.