Stability of state estimation over sensor networks with Markovian fading channels

Stochastic stability for centralized Kalman filtering over a wireless sensor network with correlated fading channels is studied. On their route to the gateway, sensor packets, possibly aggregated with measurements from several nodes, may be dropped because of fading links. By assuming the network states to be Markovian, we establish sufficient conditions that ensure the Kalman filter to be exponentially bounded in norm. In the one sensor case, this new stability condition is shown to include previous results obtained in the literature as special cases. The results also hold when applying power control, where the transmission power of each node is a nonlinear mapping of the network state and the channel gains.