In order to quantify the energy efficiency of a wireless network, the power consumption of the entire system needs to be captured. In this paper, the necessary extensions with respect to existing performance evaluation frameworks are discussed. The most important addendums of the proposed energy efficiency evaluation framework (E 3 F) are a sophisticated power model for various base station (BS) types, as well as large-scale long-term traffic models. The BS power model maps the RF output power radiated at the antenna elements to the total supply power of a BS site.The proposed traffic model emulates the spatial distribution of the traffic demands over large geographical regions, including urban and rural areas, as well as temporal variations between peak and off-peak hours. Finally, the E 3 F is applied to quantify the energy efficiency of the downlink of a 3GPP LTE radio access network. Index TermsEnergy efficiency, green radio, power & traffic model, system level energy efficiency simulations, energy aware radio and network technologies (EARTH)

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Abstract-In order to quantify the energy savings in wireless networks, the power consumption of the entire system needs to be captured and an appropriate energy efficiency evaluation framework must be defined. In this paper, the necessary enhancements over existing performance evaluation frameworks are discussed, such that the energy efficiency of the entire network comprising component, node and network level contributions can be quantified. The most important addendums over existing frameworks include a sophisticated power model for various base station (BS) types, which maps the RF output power radiated at the antenna elements to the total supply power of a BS site. We also consider an approach to quantify the energy efficiency of large geographical areas by using the existing small scale deployment models along with long term traffic models. Finally, the proposed evaluation framework is applied to quantify the energy efficiency of the downlink of a 3GPP LTE radio access network.Index Terms-energy efficiency, green radio, power & traffic model, system level energy efficiency simulations, energy aware radio and network technologies (EARTH)

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 energy consumption 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]. The EARTH 1 project [3] is a concerted effort to achieve this goal and as part of its objectives, a holistic framework is developed to evaluate and compare the energy efficiency of several design approaches of wireless cellular communication networks.For the quantification of energy savings in wireless networks, the power consumption of the entire system needs to be captured and an appropriate energy efficiency evaluation framework (E 3 F) is to be defined. The EARTH E 3 F presented in Section 1.2 provides the key levers to facilitate the assessment of the overall energy efficiency of cellular networks over a whole country. The E 3 F primarily builds on well-established methodology for radio network performance evaluation developed in 3GPP; the most important addendums, introduced in Sections 1.3 and 1.4, are to add a sophisticated power model of the base stations 1 EU funded research project EARTH (Energy Aware Radio and neTwork tecHnologies), FP7-

Abstract-With the explosion of wireless communications in number of users and data rates, the reduction of network power consumption becomes more and more critical. This is especially true for base stations which represent a dominant share of the total power in cellular networks. In order to study power reduction techniques, a convenient power model is required, providing estimates of the power consumption in different scenarios. This paper proposes such a model, accurate but simple to use. It evaluates the base station power consumption for different types of cells supporting the 3GPP LTE standard. It is flexible enough to enable comparisons between state-of-the-art and advanced configurations, and an easy adaptation to various scenarios. The model is based on a combination of base station components and sub-components as well as power scaling rules as functions of the main system parameters.

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Power models are needed to assess the power consumption of cellular base stations (BSs) on an abstract level. Currently available models are either too simplified to cover necessary aspects or overly complex. We provide a parameterized linear power model which covers the individual aspects of a BS which are relevant for a power consumption analysis, especially the transmission bandwidth and the number of radio chains. Details reflecting the underlying architecture are abstracted in favor of simplicity and applicability. We identify current power-saving techniques of cellular networks for which this model can be used. Furthermore, the parameter set of typical commercial BSs is provided and compared to the underlying complex model. The complex model is well approximated while only using a fraction of the input parameters.

This paper presents a biologically inspired approach for distributed slot synchronization in wireless networks. This is facilitated by modifying and extending a synchronization model based on the theory of pulse-coupled oscillators. The proposed Meshed Emergent Firefly Synchronization (MEMFIS) multiplexes synchronization words with data packets and adapts local clocks upon the reception of synchronization words from neighboring nodes. In this way, a dedicated synchronization phase is mitigated, as a network-wide slot structure emerges seamlessly over time as nodes exchange data packets. Simulation results demonstrate that synchronization is accomplished regardless of the arbitrary initial situation. There is no need for the selection of master nodes, as all nodes cooperate in a completely self-organized manner to achieve slot synchrony. Moreover, the algorithm is shown to scale with the number of nodes, works in meshed networks, and is robust against interference and collisions in dense networks.