Online Throughput Maximization for Energy Harvesting Communication Systems with Battery Overflow
Abstract: Energy harvesting communication system enables energy to be dynamically harvested from natural resources and stored in capacitated batteries to be used for future data transmission. In such a system, the amount of future energy to harvest is uncertain and the battery capacity is limited. As a consequence, battery overflow and energy dropping may happen, causing energy underutilization. To maximize the he data throughput by using the energy efficiently, a rate rate-adaptive transmission schedule must address the trade-off trade off between a high high-rate transmission which avoids energy overflow and a low low-rate rate transmission which avoids energy shortage. In this paper, we study study an online throughput maximization problem without knowing future information. To the best of our knowledge, this is the first work studying the fully fully-online online transmission rate scheduling problem for battery-capacitated battery capacitated energy harvesting communication systems. ystems. We consider the problem under two models of the communication channel, a static channel model that assumes the channel status is stable, and a fading channel model that assumes the channel status varies. For the former, we develop an online algorithm hm that approximates the offline optimal solution within a constant factor for all possible inputs. For the latter, that the channel gains vary in range [hmin; hmax], we propose an online algorithm with a proven ⊖(log(hmax/