  Wireless powered communication networks are becoming an effective solution
for improving self sustainability of mobile devices. In this context, a hybrid
access point transfers energy to a group of nodes, which use the harvested
energy to perform computation or transmission tasks. While the availability of
the wireless energy transfer mechanism opens up new frontiers, an appropriate
choice of the network parameters (e.g., transmission powers, transmission
duration, amount of transferred energy, etc.) is required in order to achieve
high performance. In this work, we study the throughput optimization problem in
a system composed of an access point which recharges the batteries of two
devices at different distances. In the literature, the main focus so far has
been on slot-oriented optimization, in which all the harvested energy is used
in the same slot in which it is harvested. However, this approach is strongly
sub-optimal because it does not exploit the possibility to store the energy and
use it at a later time. Thus, instead of considering the slot-oriented case, we
address the long-term maximization. This assumption greatly increases the
optimization complexity, requiring to consider, e.g., the channel state
realizations, its statistics and the batteries evolution. Our objective is to
find the best scheduling scheme, both for the energy transferred by the access
point and for the data sent by the two nodes. We discuss how to perform the
maximization with optimal as well as approximate techniques and show that the
slot-oriented policies proposed so far are strongly sub-optimal in the long
run.
