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DEVELOPMENT OF AN IMPROVED DYNAMIC ALGORITHM TOENHANCE ENERGY SAVING IN LONG TERM EVOLUTION MOBILE ACCESS NETWORKS.
DEVELOPMENT OF AN IMPROVED DYNAMIC ALGORITHM TOENHANCE 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: energy estimation algorithm and load/traffic sharing algorithm. The energy estimation algorithm is use 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 wasimplemented 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. Energy savings were analysed for call blocking probabilitiesof,,,, and , while varying the energy load proportionality constant between and in steps ofAn optimum energy saving for the network was achieved when maintaining a call blocking probability of which corresponded to , , , , , , , , , and for the energy-load proportionality constant of and respectively. 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 and 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 of 1.
DEVELOPMENT OF AN IMPROVED DYNAMIC ALGORITHM TOENHANCE ENERGY SAVING IN LONG TERM EVOLUTION MOBILE ACCESS NETWORKS.