Besides this operator cost issue, the rising energy consumption of mobile networks also contributes to the global emission of greenhouse gases and to global warming. Mobile network infrastructure (without mobile devices) emitted 64 Mtonns of CO 2 in 2002 and increases are projected through 2020 to 178 Mtonns [9]. Both cost and climate issues of mobile networks have recently drawn significant attention to the improvement of their energy efficiency in research initiatives [12,16,24] and conferences [18,26]. Network operators have announced reduction plans for their energy usage [27] and equipment manufacturers have reported a significant increase in base station power efficiency [6,8].The major source of power consumption in mobile networks stems from the radio base stations [20]. Therefore, power saving methods developed and deployed today mainly focus on three areas:

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An optimal vertical antenna tilt in a wireless access network plays a key role for coverage and capacity in the system. The autonomous (re-)optimization of tilts bears a large saving potential for operators as manual intervention is particularly costly. In this paper, we present a heuristic variant of the gradient ascent method to continuously optimize antenna tilts with quick convergence. We show that the average spectral efficiency in the system increases by 10% and that the spectral efficiency at the cell edge (5% quantile) increases by 100% after optimization. Changing conditions during the operational phase of the network, as for instance cell outage, can successfully be detected and compensated by an autonomous re-optimization.

many of the on-site operations. Additionally, about 24 percent of a typical wireless operator's revenue is normally spent on network OPEX, including training, support, power, transmission, and site rental [14]. Self-optimization functions can reduce the workload for site survey and analysis of network performance and thus reduce OPEX. Moreover, energy-saving functions enabled by self-optimization capabilities reduce costs for power consumed by the equipment. Additionally, the improved quality of user experience due to an optimal configuration of network elements and allocation of resources boosts the operator's profile and opens up new avenues for revenue. Figure 1 illustrates the impact of employing self-organizing network (SON) functionalities on various stages of a

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Careful modeling of the radio channel characteristics is an important issue for system level simulations. While a number of detailed path loss, shadowing and fast fading models can be found in literature, many of them entail large computational efforts and hence lead to long simulation times, or require huge amounts of memory. In this paper, we focus on shadowing models with two-dimensional correlation properties. We present handover performance evaluations as a use case from which requirements to the modeling of the shadow fading are derived. For different implementations of the shadow fading in system level simulations, we discuss their pros and cons and then focus on the sum of sinusoid model proposed by Cai and Giannakis [1]. Our main contribution lies in a new frequency sampling method to determine the coefficients of the sinusoidal waveforms. We show that this new method, denoted as Power Sampling Method (PSM), allows for a significant reduction of the number of sinusoids while the correlation properties of the shadow fading channel are preserved.

This paper provides a summary of the IEEE C37.238-2011 standard, which specifies a subset of PTP parameters and options to provide global time availability, device interoperability, and failure management. This set of PTP parameters and options allows IEEE 1588-based time synchronization to be used in mission critical power system protection, control, automation, and data communication applications utilizing Ethernet communications architecture.

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