  We study decentralized estimation of time-varying signals at a fusion center,
when energy harvesting sensors transmit sampled data over rate-constrained
links. We propose dynamic strategies to select radio parameters, sampling set,
and harvested energy at each node, with the aim of estimating a time-varying
signal while ensuring: i) accuracy of the recovery procedure, and ii) stability
of the batteries around a prescribed operating level. The approach is based on
stochastic optimization tools, which enable adaptive optimization without the
need of apriori knowledge of the statistics of radio channels and energy
arrivals processes. Numerical results validate the proposed approach for
decentralized signal estimation under communication and energy constraints
typical of Internet of Things (IoT) scenarios.
