Combining data fusion with joint source-channel coding of correlated sensors

We consider a source sensed by several correlated sensors. Each one of the sensors receives a noisy version of the source, performs channel coding, and transmits this information through an independent noisy channel to a central processing unit. The processing unit fuses all the received sequences with the objective of obtaining the best possible estimate of the source of interest. This is performed by utilizing at the decoder a graphical model that jointly describes the channel decoders for each sensor and the probabilistic dependence between the source and the sensors.