  Due to stringent constraints on resources, it may be infeasible to acquire
the current channel state information at the transmitter in energy harvesting
communication systems. In this paper, we optimize an energy harvesting
transmitter, communicating over a slow fading channel, using layered coding.
The transmitter has access to the channel statistics, but does not know the
exact channel state. In layered coding, the codewords are first designed for
each of the channel states at different rates, and then the codewords are
either time-multiplexed or superimposed before the transmission, leading to two
transmission strategies. The receiver then decodes the information adaptively
based on the realized channel state. The transmitter is equipped with a
finite-capacity battery having non-zero internal resistance. In each of the
transmission strategies, we first formulate and study an average rate
maximization problem with non-causal knowledge of the harvested power
variations. 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.
