Abstract
This letter considers the problem of remotely estimating the state of a scalar dynamic system over a wireless channel that is capacity-limited and lossy. In this problem, the wireless channel suffers from quantization noise and packet loss while the data for remote estimation are transferred from the transmitter to the receiver; these phenomena degrade remote estimation of the system state. To determine the transmission strategy under these phenomena, we propose the remote estimation that is designed to minimize the estimate error variance (EEV) between the real state and the remote estimate of one. To achieve this goal, we design the linear encoder and the corresponding quantizer. Finally, we construct remote estimator recursions for the determined linear encoder and quantizer. In simulations, the proposed remote estimator is shown to achieve lower averaged time-tracking EEV than the existing scheme.
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