225 research outputs found
Energy Efficient Relay-Assisted Cellular Network Model using Base Station Switching
Cellular network planning strategies have tended to focus on peak traffic scenarios rather than energy efficiency. By exploiting the dynamic nature of traffic load profiles, the prospect for greener communications in cellular access networks is evolving. For example, powering down base stations (BS) and applying cell zooming can significantly reduce energy consumption, with the overriding design priority still being to uphold a minimum quality of service (QoS). Switching off cells completely can lead to both coverage holes and performance degradation in terms of increased outage probability, greater transmit power dissipation in the up and downlinks, and complex interference management, even at low traffic loads. In this paper, a cellular network model is presented where certain BS rather than being turned off, are switched to low-powered relay stations (RS) during zero-to-medium traffic periods. Neighbouring BS still retain all the baseband signal processing and transmit signals to corresponding RS via backhaul connections, under the assumption that the RS covers the whole cell. Experimental results demonstrate the efficacy of this new BS-RS Switching technique from both an energy saving and QoS perspective, in the up and downlinks
Cell sleeping for energy efficiency in cellular networks: Is it viable?
An approach advocated in the recent literature for reducing energy consumption in cellular networks is to put base stations to sleep when traffic loads are low. However, several practical considerations are ignored in these studies. In this paper, we aim to raise questions on the feasibility and benefits of base station sleeping. Specifically we analyze the interference and capacity of a coverage-based energy reduction system in CDMA based cellular networks using a simple analytical model and show that sleeping may not be a feasible solution to reduce energy consumption in many scenarios. © 2012 IEEE
Planning Solar in Energy-managed Cellular Networks
There has been a lot of interest recently on the energy efficiency and
environmental impact of wireless networks. Given that the base stations are the
network elements that use most of this energy, much research has dealt with
ways to reduce the energy used by the base stations by turning them off during
periods of low load. In addition to this, installing a solar harvesting sys-
tem composed of solar panels, batteries, charge con- trollers and inverters is
another way to further reduce the network environmental impact and some
research has been dealing with this for individual base stations. In this
paper, we show that both techniques are tightly coupled. We propose a
mathematical model that captures the synergy between solar installation over a
network and the dynamic operation of energy-managed base stations. We study the
interactions between the two methods for networks of hundreds of base stations
and show that the order in which each method is intro- duced into the system
does make a difference in terms of cost and performance. We also show that
installing solar is not always the best solution even when the unit cost of the
solar energy is smaller than the grid cost. We conclude that planning the solar
installation and energy management of the base stations have to be done
jointly
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Scalable base station switching framework for green cellular networks
With the recent unprecedented growth in the wireless market, network operators are obliged not only to find new techniques including dense deployment of base stations (BSs) in order to support high data rate services and high user density, but also to reduce the operating costs and energy consumption of various network elements. To solve these challenges, powering down certain BSs during low-traffic periods, so-called BS sleeping, has emerged as an effective green communications paradigm. While BS sleeping offers the potential to significantly lower energy consumption, it also raises many challenges, since when a BS is switched off, this can lead to, for example, coverage holes, sudden degradation in quality of service (QoS), higher transmit power dissipation in off-cell mobile stations (MSs), an inability to rapidly power up/down equipment and finally, a failure to uphold regulatory requirements. In order to realise greener network designs which both maximise energy savings whilst guaranteeing QoS, innovative BS switching mechanisms need to be developed.
This thesis presents a novel BS switching framework which improves energy efficiency (EE) in comparison with existing approaches, while guaranteeing the minimum QoS and seamless services. The major technical contributions in this framework are: i) a new BS to relay station (RS) switching model where certain BSs are switched to RS mode rather than being turned off, firstly using a fixed threshold based switching algorithm utilizing temporal traffic diversity, and ii) then subsequently by means of an adaptive threshold by exploiting the inherently asymmetric traffic profile between cells, i.e., by exploiting both the temporal and spatial traffic diversity; iii) a traffic-and-interference-aware BS switching strategy that considers the impact of inter-cell interference in the decision making process to dynamically determine the best BS set to be kept active for improved EE; and finally iv) a novel scalable multimode BS switching model which enables each BS to operate in different power modes i.e., macro/micro/sleep to explore energy savings potential even at higher traffic conditions.
The thesis findings conclusively confirm this new BS switching framework provides significant EE improvements from both BS and MS perspectives, under diverse network conditions and represents a notable step towards greener communications
A Novel Multiobjective Cell Switch-Off Framework for Cellular Networks
Cell Switch-Off (CSO) is recognized as a promising approach to reduce the
energy consumption in next-generation cellular networks. However, CSO poses
serious challenges not only from the resource allocation perspective but also
from the implementation point of view. Indeed, CSO represents a difficult
optimization problem due to its NP-complete nature. Moreover, there are a
number of important practical limitations in the implementation of CSO schemes,
such as the need for minimizing the real-time complexity and the number of
on-off/off-on transitions and CSO-induced handovers. This article introduces a
novel approach to CSO based on multiobjective optimization that makes use of
the statistical description of the service demand (known by operators). In
addition, downlink and uplink coverage criteria are included and a comparative
analysis between different models to characterize intercell interference is
also presented to shed light on their impact on CSO. The framework
distinguishes itself from other proposals in two ways: 1) The number of
on-off/off-on transitions as well as handovers are minimized, and 2) the
computationally-heavy part of the algorithm is executed offline, which makes
its implementation feasible. The results show that the proposed scheme achieves
substantial energy savings in small cell deployments where service demand is
not uniformly distributed, without compromising the Quality-of-Service (QoS) or
requiring heavy real-time processing
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