ON/OFF Switching Strategies of eNodeB for Green LTE Networks
Abstract:
The enormous growth in broadband communications over the last decade has propelled the ICT sector to become one of the main industries that drain a large percentage of annual global energy consumption. This has coincided with an era which is witnessing declining availability of traditional energy resources and proactive research for renewable green/clean sources of energy. In cellular communications, base stations are typically responsible for nearly 60% of the energy demand associated with cellular services. Accordingly, recent research on energy efficient strategies to manage base station operation has become of the ultimate essence. In this contribution, the aim is to investigate optimal switching ON/OFF strategies of eNodeB for green LTE networks. The approach adopted formulates the problem as an optimization algorithm that minimizes the number of ON base stations within a given area in correspondence to active traffic loads and transmission power requirements while maintaining individual subscribers’ QoS constraints.
Over the last decade, energy consumption of the information and communication technologies (ICT) sector has become a key issue due to both economic and environmental reasons. ICT has been claimed to be responsible for 2% - 10% of annual worldwide consumption[1].Moreover, on the environmental side, ICT is responsible for an insignificant percentage of global C02 emissions [2]. With projections for 2013 that indicate more than 1.82 billion smart phone units representing the most common alternative for web access (exceeding PCs) [3], the future of ICT envisions a predominant expansion in cellular/wireless infrastructures with significantly large percentage of ICT energy demands. Statistics show that base stations drain the highest amount of energy within the network of mobile operators (nearly 57% of operators’ consumption) [4]. Accordingly, research on energy savings techniques of base station operation has become of significant importance over the last couple of years[5].
Due to the alternating nature of cellular traffic demand between day and night as well as office and residential areas, strategies for switchingON/OFF the radio base stations (eNodeB in LTE) has been one of the main active topics among the techniques of energy saving in base stations operations [6], [7],[8]. This could be particularly evident if the maximum base station power transmission power at the scale of 30W-40W is compared to base station operations cost at the scale of 1500 W [9].
Strategies of switching ON/OFF the appropriate eNodeB in response to active traffic demand variations have varied form load-based to UE distance-based techniques. In the load-based approach, the eNodeB depends on a set of traffic thresholds that are predefined during configuration and eNodeB with active traffic load below the preset thresholds are switched OFF [8]. In UEs distance-based approach, eNodeB are ranked based on the average distance between them and their active served mobile subscribers. The eNodeB with the highest average distances are selected to have priority for switch OFF. In both approaches, active users of the switched OFF eNodeB must be diverted to the next nearest eNodeB without jeopardizing their QoS requirements.
In this contribution, the problem of ON/OFF switching strategies in LTE networks will be formulated as an optimization algorithm that considers both the power transmission requirementsof eNodeB to serve active mobiles users within its coverage range as well as the average power requirements for eNodeB to support mobiles users that are served by neighbor base stations. The addition to include the relation between eNodeB and mobile users served by neighbor base station in the process of selection of eNodeB that should be switched OFF contributes in providing guarantees that traffic of switched OFF eNodeB could have a better chance of being supported at their QoS requirements. Furthermore, the research in this contribution shall also incorporate the effect of fractional reuse in LTE on ON/OFF switching strategies which has been overlooked in the literature
References:
[1].Global Action Plan, “An inefficient truth,” Global Action Plan Report, Dec. 2007
[2].
[3].B. Gammage et al., “Gartner’s Top Predictions for IT Organizations and Users, 2010 and Beyond: A New Balance,” Gartner Report, Dec. 2009.
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