Dynamic quantization for multisensor estimation over bandlimited fading channels with fusion center feedback.

This paper considers the state estimation of hidden Markov models(HMMs) in a network of sensors which communicate with the fusion center viafinite symbols by fading channels. The objective is to minimize the long term meansquare estimation error for the underlying Markov chain. By using feedback fromthe fusion center, a dynamic quantization scheme for the sensor nodes is proposedand analyzed by a Markov decision approach. The performance improvement byfeedback, as well as the effect of fading, is illustrated