Adaptive Energy Efficient Scheduling Algorithm for LTE Pico Base Stations

Mobile data traffic is increasing dramatically, essentially due to the exploding use of wireless applications. To cope with this, one solution is the deployment of many small base station sites to cover the hot spots. With the deployment of more heterogeneous networks, the total energy expenditure will increase. Traditionally, the techniques to improve the energy efficiency of small base stations exploit the network load variation and the idle time. However, they do not consider that the resource scheduling can have an important impact on energy consumption when the network is not fully loaded. In fact, forcing the system to transmit a packet when the channel conditions are poor, results in low energy efficiency. In this paper we propose an adaptive scheduling algorithm for pico base stations that applies the optimal scheduling algorithm of “water-pouring” in time in a full LTE framework using consolidated pico base station power models from EARTH project. Our approach reduces the energy per information bit by transmitting at full load during good channel conditions and going into sleep mode the rest of the time. We quantify the achievable gains with realistic channel and network conditions and we show energy savings of up to 61% in the energy per information bit with a marginal impact on packet delay.