  In this paper, we consider a wireless powered communication system, where an
energy harvesting (EH) node harvests energy from a radio frequency (RF) signal
broadcasted by an access point (AP) in the downlink (DL). The node stores the
harvested energy in an energy buffer and uses the stored energy to transmit
data to the AP in the uplink (UL). We investigate two simple online
transmission policies for the EH node, namely a best-effort policy and an
on-off policy, which do not require knowledge of the EH profile nor channel
knowledge. In particular, for both policies, the EH node transmits in each time
slot with a constant desired power if sufficient energy is available in its
energy buffer. Otherwise, the node transmits with the maximum possible power in
the best-effort policy and remains silent in the on-off policy. For both
policies, we use the theory of discrete-time continuous-state Markov chains to
analyze the limiting distribution of the stored energy for finite- and
infinite-size energy buffers. We provide this limiting distribution in closed
form for a Nakagami-m fading DL channel and analyze the outage probability for
a Nakagami-m fading UL channel. All derived analytical results are not limited
to EH via RF WPT but are applicable for any independent and identically
distributed EH process, originating from e.g. solar and wind energy. Our
results reveal that, for low outage probabilities, the best-effort policy is
superior to the on-off policy and the optimal constant UL transmit power of the
EH node that minimizes the outage probability is always less than the average
harvested power but increases with the capacity of the energy buffer. The
opposite behaviour is observed for high outage probabilities. Furthermore, we
show that the minimum outage probability of the two proposed policies closely
approaches the outage probability of the optimal offline power allocation
policy.
