  Devices can now be powered wirelessly by Access Points (APs). However, an AP
cannot transmit frequently to charge devices as it may starve other nearby APs
operating on the same channel. Consequently, there is a need to schedule the
transmissions of APs to ensure their data queues remain short whilst charging
energy-harvesting devices. We present a finite-horizon Markov Decision Process
(MDP) to capture the queue states at APs and also channel conditions to nodes.
We then use the MDP to investigate the following transmission policies: max
weight, max queue, best channel state and random. Our results show that the max
weight policy has the best performance in terms of queue length and delivered
energy.
