3,207 research outputs found
Leveraging intelligence from network CDR data for interference aware energy consumption minimization
Cell densification is being perceived as the panacea for the imminent capacity crunch. However, high aggregated energy consumption and increased inter-cell interference (ICI) caused by densification, remain the two long-standing problems. We propose a novel network orchestration solution for simultaneously minimizing energy consumption and ICI in ultra-dense 5G networks. The proposed solution builds on a big data analysis of over 10 million CDRs from a real network that shows there exists strong spatio-temporal predictability in real network traffic patterns. Leveraging this we develop a novel scheme to pro-actively schedule radio resources and small cell sleep cycles yielding substantial energy savings and reduced ICI, without compromising the users QoS. This scheme is derived by formulating a joint Energy Consumption and ICI minimization problem and solving it through a combination of linear binary integer programming, and progressive analysis based heuristic algorithm. Evaluations using: 1) a HetNet deployment designed for Milan city where big data analytics are used on real CDRs data from the Telecom Italia network to model traffic patterns, 2) NS-3 based Monte-Carlo simulations with synthetic Poisson traffic show that, compared to full frequency reuse and always on approach, in best case, proposed scheme can reduce energy consumption in HetNets to 1/8th while providing same or better Qo
Dimming cellular networks
We propose a novel technique called dimming to improve the energy efficiency of cellular networks by reducing the capacity, services, and energy consumption of cells without turning off the cells. We define three basic methods to dim the network: coverage, frequency, and service dimming. We construct a multi-time period optimization problem to implement frequency dimming and extend it to implement both frequency and service dimming together. We illustrate the ability of dimming techniques to adapt the capacity and network services in proportion to the dynamic spatial and temporal load resulting in significant energy savings through numerical results for a sample network. ©2010 IEEE
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Energy savings using an adaptive base station-to-relay station switching paradigm
Applying a Base Station (BS) sleep approach during low traffic periods has recently been advocated as a strategy for reducing energy consumption in cellular networks. The complete switching off of certain BS however, can lead to coverage holes and severe performance degradation in terms of off-cell user throughput, greater transmit power dissipation in both the up and downlinks, and more complex interference management. This paper presents a novel cellular network energy saving model in which certain BS rather being turned off are switched to Relay Station (RS) mode during low traffic periods. The switched RS and other shared RS deployed at the cross border of each cell are responsible for upholding the same quality of service (QoS) provision as when all BS are active. A centralised adaptive switching threshold algorithm is also introduced to undertake the switching decision, instead of using a fixed threshold. Simulation results confirm the new BS-RS Switching model using an adaptive threshold can reduce network energy consumption by more than half, as well as improving off-cell users’ throughput
Quantifying Potential Energy Efficiency Gain in Green Cellular Wireless Networks
Conventional cellular wireless networks were designed with the purpose of
providing high throughput for the user and high capacity for the service
provider, without any provisions of energy efficiency. As a result, these
networks have an enormous Carbon footprint. In this paper, we describe the
sources of the inefficiencies in such networks. First we present results of the
studies on how much Carbon footprint such networks generate. We also discuss
how much more mobile traffic is expected to increase so that this Carbon
footprint will even increase tremendously more. We then discuss specific
sources of inefficiency and potential sources of improvement at the physical
layer as well as at higher layers of the communication protocol hierarchy. In
particular, considering that most of the energy inefficiency in cellular
wireless networks is at the base stations, we discuss multi-tier networks and
point to the potential of exploiting mobility patterns in order to use base
station energy judiciously. We then investigate potential methods to reduce
this inefficiency and quantify their individual contributions. By a
consideration of the combination of all potential gains, we conclude that an
improvement in energy consumption in cellular wireless networks by two orders
of magnitude, or even more, is possible.Comment: arXiv admin note: text overlap with arXiv:1210.843
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