State estimation over sensor networks with correlated wireless fading channels
DE Quevedo, A Ahlen… - IEEE Transactions on …, 2012 - ieeexplore.ieee.org
DE Quevedo, A Ahlen, KH Johansson
IEEE Transactions on Automatic Control, 2012•ieeexplore.ieee.orgStochastic stability for centralized time-varying 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. To study this situation, we introduce a network state process, which
describes a finite set of configurations of the radio environment. The network state
characterizes the channel gain distributions of the links, which are allowed to be correlated …
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. To study this situation, we introduce a network state process, which
describes a finite set of configurations of the radio environment. The network state
characterizes the channel gain distributions of the links, which are allowed to be correlated …
Stochastic stability for centralized time-varying 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. To study this situation, we introduce a network state process, which describes a finite set of configurations of the radio environment. The network state characterizes the channel gain distributions of the links, which are allowed to be correlated between each other. Temporal correlations of channel gains are modeled by allowing the network state process to form a (semi-)Markov chain. We establish sufficient conditions that ensure the Kalman filter to be exponentially bounded. 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 using power and bit-rate control policies, where the transmission power and bit-rate of each node are nonlinear mapping of the network state and channel gains.
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