A self-organizing base station sleeping and user association strategy for dense cellular networks

Bart Post,Sem Borst,Hans Van Den Berg

doi:10.1007/s11276-020-02383-3

Abstract

Due to the rising concerns of energy consumption in wireless networks, base station (BS) sleeping strategies were introduced to save energy in low traffic scenarios. In this paper we analyse a weighted trade-off between energy consumption and user-perceived performance in dense cellular networks. We present an optimization problem representing this trade-off and derive properties of its optimal solutions. Using these properties we design a self-organizing strategy that dynamically (online) makes load-aware user association and BS operation decisions. Our strategy is self-organizing in the sense that it does not need any information or optimization beforehand, it simply relies on real-time load measurements at the BSs and user-reported SINR values. We furthermore present extensive simulation results, demonstrating the effectiveness of our self-organizing strategy and the impact of increased energy consumption on the user-perceived performance.

Highlights

Wireless cellular networks have experienced immense growth in traffic loads over the last years as a consequence of the rapid proliferation of smartphones, tablets, and their bandwidth-hungry applications
In this paper we present a self-organizing, load-aware strategy that makes a trade-off between energy consumption and user-perceived performance for dense cellular networks (DCNs), using a pre-specified trade-off parameter
Our strategy is self-organizing in the sense that it does not need any information or optimization beforehand, it relies on real-time load measurements at the base station (BS) and user-reported signal-to-interference-plus-noise ratio (SINR) values

Summary

Introduction

Wireless cellular networks have experienced immense growth in traffic loads over the last years as a consequence of the rapid proliferation of smartphones, tablets, and their bandwidth-hungry applications. BS sleeping strategies were introduced as a result of the rising concerns of energy consumption of wireless networks, both in in terms of environmental impact and economic cost. In MCNs, BSs are responsible for about 60–80% of the total energy consumption [28], where a single BS may consume up to 90% of its peak energy consumption in the absence of any traffic due to cooling and pilot signalling [24]. In terms of economic costs, Nokia corporation recently estimated [19] that the global energy bill of radio access networks is currently over 72 billion Euros. These costs and the environmental impact caused by the massive energy consumption of cellular networks drives the need to improve their energy efficiency.

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Conclusion