  This paper proposes a novel channel estimation method and a cluster-based
opportunistic scheduling policy, for a wireless energy transfer (WET) system
consisting of multiple low-complex energy receivers (ERs) with limited
processing capabilities. Firstly, in the training stage, the energy transmitter
(ET) obtains a set of Received Signal Strength Indicator (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 selected for dedicated WET. The beamformer that maximizes the minimum
harvested energy among all ERs in the selected cluster is found by solving a
convex optimization problem. 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 over benchmark schemes.
