Save-then-transmit scheme for Gaussian channels powered by random energy harvesters

Energy harvesting (EH) from renewable energy resources is more environmental friendly and convenient than the conventional energy supplies. This paper considers a point-to-point channel with the transmitter powered by the random energy harvester and a save-then-transmit scheme is adopted due to the battery halfduplex constraint: the transmitter first harvests energy for a certain time, and then stops EH to transmit information with accumulated energy at the battery. It is crucial to determine a proper stopping time for the EH process, since larger EH duration provides more the accumulated energy while decreases the average throughput. In this paper, our goal is to obtain the optimal stopping time to maximize the average throughput of the considered systems. First, this paper proves the existence of the optimal stopping rule and shows that this rule has a state-dependent “threshold-based” structure under the Markov energy arrival case. Then, for a special independent identically distributed (i.i.d.) energy arrival case, this paper further proves that the corresponding threshold is a constant and can be efficiently computed by a proposed algorithm.