Dynamic energy savings in heterogeneous cellular networks based on traffic prediction using compressive sensing

The information and communication technolo-gies(ICT)industry has emerged as one of the main future consumers of the world energy and the radio access network, specially BS(base station) consumes over 80%. Thus this paper focuses on the BS energy efficiency issues of heterogeneous cellular networks. We analyze the energy saving potential of adaptively turning on and off some BSs to minimize the number of working BSs, based on traffic data prediction through spatio-temporal compressive sensing. Simulation results prove the accuracy of the traffic forecasting and large energy efficiency improvement.