Development of an Improved Dynamic Algorithm To enhance Energy Saving in Long Term Evolution Mobile Access Networks.
ABSTRACT
This research work presents a dynamic algorithm for improving energy saving in Long Term Evolution (LTE) mobile access networks through off mode, sleep mode, and multi-cell cooperation utilization at the eNodeBs.
The LTE mobile access network environment and the eNodeBs energy-saving models were developed with a view to implementing a dynamic energy-saving algorithm. The dynamic energy-saving algorithm is an integration of two algorithms, namely: the energy estimation algorithm and the load/traffic sharing algorithm.
The energy estimation algorithm is used to estimates the energy consumption of the eNodeBs when they are powered on, irrespective of the traffic loading. The load/traffic sharing algorithm transfers traffic between eNodeBs which enabled the off mode, sleep mode, and multi-cell cooperation of the eNodeBs.
The dynamic energy-saving algorithm was implemented in MATLAB 2013b environment. The performance of the dynamic energy-saving algorithm was carried out by simulation using the developed MATLAB graphical user interface (GUI) program called the LTE network energy saving analysis software based on dynamic scheduling.
Validation of the proposed dynamic energy-saving algorithm was carried out by comparison with the “always-on” algorithm by Chiaraviglio et al., (2012) and the “sleep-wake” algorithm by Hossain et al., (2013).
The result showed that the proposed dynamic energy-saving algorithm achieved the highest energy saving of 51.84%and 11.84% as compared to the “always-on” algorithm by Chiaraviglio et al., (2012)and the“sleep-wake” algorithm by Hossain et al., (2013)which achieve an energy saving of 0% and 40% respectively while guaranteeing a call blocking probability of at an energy-load proportionality constant
INTRODUCTION
Background
The information and communication technology (ICT) systems consume up to 10% of the world‟s energy accounting for about 2% of global emissions(Marsan et al., 2009).
The telecommunications network is one of the main energy consumers of the information and communication technology sector(digital et al., 2014). About 37% of the total emissions from ICT devices and systems are due to the telecommunication infrastructure and devices (oh and Krishnamacharya, 2010), where about a tenth of the estimate is due to cellular mobile communication networks (son et al., 2013).
This accounts for about 0.2% of the global Emissions and 1% of the world’s energy consumption(Richter et al., 2009). The mobile cellular communications sector alone consumes approximately 60 billion kWh per year(dufková et al., 2010).
Correspondingly, energy consumption, as well as the footprint of mobile cellular networks, are increasing at an alarming rate due to the exponential growth in mobile data traffic (wu et al., 2015).
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