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    Linear Encoder-Decoder-Controller Design over Channels with Packet Loss and Quantization Noise


    Dey, Subhrakanti and Chiuso, Alessandro and Schenato, Luca (2015) Linear Encoder-Decoder-Controller Design over Channels with Packet Loss and Quantization Noise. In: 2015 European Control Conference (ECC). IEEE, pp. 934-939. ISBN 978-3-9524-2694-4

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    Abstract

    We consider a decentralized multisensor estimation problem where L sensor nodes observe noisy versions of a possibly correlated random source. The sensors amplify and forward their observations over a fading coherent multiple access channel (MAC) to a fusion center (FC). The FC is equipped with a large array of N antennas, and adopts a minimum mean square error (MMSE) approach for estimating the source. We optimize the amplification factor (or equivalently transmission power) at each sensor node in two different scenarios: 1) with the objective of total power minimization subject to mean square error (MSE) of source estimation constraint, and 2) with the objective of minimizing MSE subject to total power constraint. For this purpose, we apply an asymptotic approximation based on the massive multiple-input-multiple-output (MIMO) favorable propagation condition (when L ≪ N). We use convex optimization techniques to solve for the optimal sensor power allocation in 1) and 2). In 1), we show that the total power consumption at the sensors decays as 1/N, replicating the power savings obtained in Massive MIMO mobile communications literature. Through numerical studies, we also illustrate the superiority of the proposed optimal power allocation methods over uniform power allocation.

    Item Type: Book Section
    Additional Information: Cite as: S. Dey, A. Chiuso and L. Schenato, "Linear encoder-decoder-controller design over channels with packet loss and quantization noise," 2015 European Control Conference (ECC), 2015, pp. 934-939, doi: 10.1109/ECC.2015.7330662.
    Keywords: Linear; Encoder-Decoder-Controller; Design over Channels; Packet Loss; Quantization Noise;
    Academic Unit: Faculty of Science and Engineering > Electronic Engineering
    Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Item ID: 14531
    Identification Number: https://doi.org/10.1109/ECC.2015.7330662
    Depositing User: Subhrakanti Dey
    Date Deposited: 15 Jun 2021 14:14
    Publisher: IEEE
    Refereed: Yes
    URI:

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