Threshold-based transmission scheduling for energy harvesting sensor nodes with finite data and energy storage

Driven by the intermittent nature of energy harvesting, this paper aims to maximize the long-term average transmission reward of energy harvesting sensor nodes subject to the finite data and energy storage. In particular, we first propose a sub-optimal threshold-based transmission scheduling policy for energy harvesting sensor nodes through maximizing conditional expected rewards with respect to data storage and energy storage, respectively. We then study the properties of the conditional expected rewards and further propose a low complexity algorithm to efficiently compute these reward value thresholds. Numerical results show that the system expected reward increases with the increase of data and energy storage capacity. Our analysis further shows that the proposed transmission scheduling can guarantee the same reward by increasing the data storage space when the energy storage knowledge is imperfect.