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    Optimal Energy Allocation in Multisensor Estimation Over Wireless Channels Using Energy Harvesting and Sharing


    Knorn, Steffi and Dey, Subhrakanti and Ahlén, Anders and Quevedo, Daniel E. (2019) Optimal Energy Allocation in Multisensor Estimation Over Wireless Channels Using Energy Harvesting and Sharing. IEEE Transactions on Automatic Control, 64 (10). pp. 4337-4344. ISSN 0018-9286

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    Abstract

    We investigate the optimal power control for multisensor estimation of correlated random Gaussian sources. A group of wireless sensors obtains local measurements and transmits them to a remote fusion center (FC), which reconstructs the measurements using the minimum mean-square error estimator. All the sensors are equipped with an energy harvesting module and a transceiver unit for wireless, directed energy sharing between neighboring sensors. The sensor batteries are of finite storage capacity and prone to energy leakage. Our aim is to find optimal power control strategies, which determine the energies used to transmit data to the FC and shared between sensors, so as to minimize the long-term average distortion over an infinite horizon. We assume centralized causal information of the harvested energies and channel gains, which are generated by independent finite-state stationary Markov chains. The optimal power control policy is derived using a stochastic predictive control formulation. We also investigate the structure of the optimal solution, a Q-learning based suboptimal power control scheme and two computationally simple and easy-to-implement heuristic policies. Extensive numerical simulations illustrate the performance of the considered policies.

    Item Type: Article
    Additional Information: Cite as: S. Knorn, S. Dey, A. Ahlén and D. E. Quevedo, "Optimal Energy Allocation in Multisensor Estimation Over Wireless Channels Using Energy Harvesting and Sharing," in IEEE Transactions on Automatic Control, vol. 64, no. 10, pp. 4337-4344, Oct. 2019, doi: 10.1109/TAC.2019.2896048.
    Keywords: Energy harvesting; energy sharing; fading; multisensor estimation; networks; power control; Q-learning;
    Academic Unit: Faculty of Science and Engineering > Research Institutes > Hamilton Institute
    Faculty of Science and Engineering > Electronic Engineering
    Item ID: 14077
    Identification Number: https://doi.org/10.1109/TAC.2019.2896048
    Depositing User: Subhrakanti Dey
    Date Deposited: 25 Feb 2021 14:30
    Journal or Publication Title: IEEE Transactions on Automatic Control
    Publisher: IEEE
    Refereed: Yes
    URI:

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