  We consider the effects of decoding costs in energy harvesting communication
systems. In our setting, receivers, in addition to transmitters, rely solely on
energy harvested from nature, and need to spend some energy in order to decode
their intended packets. We model the decoding energy as an increasing convex
function of the rate of the incoming data. In this setting, in addition to the
traditional energy causality constraints at the transmitters, we have the
decoding causality constraints at the receivers, where energy spent by the
receiver for decoding cannot exceed its harvested energy. We first consider the
point-to-point single-user problem where the goal is to maximize the total
throughput by a given deadline subject to both energy and decoding causality
constraints. We show that decoding costs at the receiver can be represented as
generalized data arrivals at the transmitter, and thereby moving all system
constraints to the transmitter side. Then, we consider several multi-user
settings. We start with a two-hop network where the relay and the destination
have decoding costs, and show that separable policies, where the transmitter's
throughput is maximized irrespective of the relay's transmission energy
profile, are optimal. Next, we consider the multiple access channel (MAC) and
the broadcast channel (BC) where the transmitters and the receivers harvest
energy from nature, and characterize the maximum departure region. In all
multi-user settings considered, we decompose our problems into inner and outer
problems. We solve the inner problems by exploiting the structure of the
particular model, and solve the outer problems by water-filling algorithms.
