  This paper proposes a novel channel estimation method, and a cluster-based
opportunistic scheduling policy, that enhances the efficiency of wireless
energy transfer in a system consisting of multiple energy receivers (ERs).
Firstly, in the training stage, the energy transmitter (ET) obtains a set of
RSSI feedback values from all ERs, and these values are used to estimate the
channels between the ET and all ERs. Next, based on the channel estimates, the
ERs are grouped into clusters, and the cluster that has its members closest to
its centroid in phase is picked. This cluster will be given priority, and the
beamformer that maximizes the minimum harvested energy among all ERs in the
selected cluster is found by solving a convex optimization problem. This
beamformer is used to transfer energy to the ERs using maximum ratio transmit
beamforming. All ERs have the same chance of being selected regardless of their
distances from the ET, and hence, this scheduling policy can be considered to
be opportunistic as well as fair. It is shown that the proposed method achieves
significant performance gains.
