Superposition Coding for Energy Harvesting Communication without CSIT

We consider rate maximization for an energy harvesting node transmitting delay-constrained information over a slow fading channel corrupted by additive white Gaussian noise. Time is divided into frames of fixed duration equal to the channel coherence block length, the time duration for which the channel power gain remains constant before changing to a different value, independently. We assume that the transmitter does not know the exact channel state but has access to the channel statistics. The transmitter is equipped with a battery having non-zero internal resistance. Using superposition coding, we formulate and study an average rate maximization problem with non-causal knowledge of the harvested power. Further, assuming statistical knowledge and causal information of the harvested power variations, we propose a sub-optimal algorithm, and compare with the stochastic dynamic programming based solution and a greedy policy.