Introduction

The global mobile communication industry is growing rapidly. Today there are already more than 4 billion mobile phone subscribers worldwide [1], more than half the entire population of the planet. Obviously, this growth is accompanied by an increased energyconsumption of mobile networks. Global warming and heightened concerns for the environment of the planet require a special focus on the energy efficiency of these systems [2].

Many approaches to wireless energy-efficiency are limited to the power consumption of single nodes, e.g. a base station [3]–[5]. This scope is comparably easy to specify and to measure, but it fails to capture the network performance aspects (e.g. system throughput) implied by coverage and interference issues. Other methodologies are very broad, capturing the ICT industry in total [6]. Recently an assessment framework for the power consumption of deployed wireless networks has been published, the mobile energyefficiency (MEE) network benchmarking service [7], based on metering all components of a network. However, for the energy efficiency it is not possible to directly compare, e.g. an Indian network with a Scandinavian network, therefore MEE has to introduce correction terms for the climate, for the number of base stations operated off-grid, and for the generations of equipment in the field.

However, the above approaches do not give insight into which parts of a network are most energy intensive or which provide the highest energy-saving potentials. There is a need for a simulation tool studying theoretically the effect of improvements in hardware, deployment strategies, and network management.