Abstract

Over the last two decades we have witnessed significant growth of the cellular network energy consumption caused by a rapid increase in the number of mobile users and data volumes. This is contributed to by a tenfold increase of data rates every 5 years, and such a trend in up growth of energy consumption will continue with the introduction of a new throughput demanding services. Hence, development of new energy-saving techniques and estimation of the influence on energy savings when ensuring different service rates are the focus of this article. For the purpose of reducing cellular network energy consumption, this article proposes a new approach to energy-efficient management of network resources. The energy-efficient management is based on adaptive changes of on/off states of a complete base station (BS) site in accordance with the traffic pattern variations. Besides adaptations to the temporal traffic variations, the BS can adapt capacity to the spatial traffic variations through dynamic scaling of transmitted power according to capacity demand. We formulate the problem of energy-efficient management as a binary integer programming problem dedicated to energy consumption minimization of a complete network. Proposed methodology is simulated on a set of real size Universal Mobile Telecommunications System network instances consisting of different radio propagation environments. In addition, this article analyzes the influence on the energy savings potential of BSs switching granularity. Obtained results show that the proposed optimization approach offers significant reductions in the network energy consumption while preserving the most important QoS constraints like full area coverage and guaranteed service rates.

Highlights

  • Fast growth of wireless cellular networks in the past decades raises a critical problem of energy consumed by network equipment

  • To the best of the authors’ knowledge, we have proposed for the first time, in [13,14], a binary integer programming (BIP) optimization approach focused on energy consumption minimization of a complete large-scale wireless local area network (WLAN)

  • In this article, we have presented a novel optimization model which can be used for energy-saving purposes at the level of a complete cellular access network

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Summary

Introduction

Fast growth of wireless cellular networks in the past decades raises a critical problem of energy consumed by network equipment. Component and link levels will be important contributors to “greener” wireless cellular networks, we believe that the network level approach can offer the highest energy savings. This is because the component level approach limits improvements to individual components of the BS only. The network level approach based on the dynamic management of BS resources seems to be the most promising [7] This approach allows the system to shut down an entire BS and transfer the corresponding traffic to a neighboring BS during the periods of low user activity

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