The paper proposes a scalar-amplified, quantization-based encoding scheme that keeps a legitimate remote Kalman filter bounded while forcing an eavesdropper's mean estimation error to diverge over Markov fading channels.
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Recursive Privacy-Preserving Estimation Over Markov Fading Channels
The paper proposes a scalar-amplified, quantization-based encoding scheme that keeps a legitimate remote Kalman filter bounded while forcing an eavesdropper's mean estimation error to diverge over Markov fading channels.