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    An Optimal Transmission Strategy for Kalman Filtering Over Packet Dropping Links With Imperfect Acknowledgements


    Nourian, Mojtaba and Leong, Alex S. and Dey, Subhrakanti and Quevedo, Daniel E. (2014) An Optimal Transmission Strategy for Kalman Filtering Over Packet Dropping Links With Imperfect Acknowledgements. IEEE Transactions on Control of Network Systems, 1 (3). pp. 259-271. ISSN 2325-5870

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    Abstract

    This paper presents a novel design methodology for optimal transmission policies at a smart sensor to remotely estimate the state of a stable linear stochastic dynamical system. The sensor makes measurements of the process and forms estimates of the state using a local Kalman filter. The sensor transmits quantized information over a packet dropping link to the remote receiver. The receiver sends packet receipt acknowledgments back to the sensor via an erroneous feedback communication channel which is itself packet dropping. The key novelty of this formulation is that the smart sensor decides, at each discrete time instant, whether to transmit a quantized version of either its local state estimate or its local innovation. The objective is to design optimal transmission policies in order to minimize a long-term average cost function as a convex combination of the receiver's expected estimation error covariance and the energy needed to transmit the packets. Under high-resolution quantization assumptions, the optimal transmission policy is obtained by the use of dynamic programming techniques. Using the concept of submodularity, the optimality of a threshold policy in the case of scalar systems with perfect packet receipt acknowledgments is proved. Suboptimal solutions and their structural results are also discussed. Numerical results are presented, illustrating the performance of the optimal and suboptimal transmission policies.

    Item Type: Article
    Keywords: High-resolution quantizer; Markov decision processes; imperfect state information; packet drops; state estimation; threshold policy; wireless sensor networks;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 14424
    Identification Number: https://doi.org/10.1109/TCNS.2014.2337975
    Depositing User: Subhrakanti Dey
    Date Deposited: 11 May 2021 15:14
    Journal or Publication Title: IEEE Transactions on Control of Network Systems
    Publisher: IEEE
    Refereed: Yes
    URI:

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