DNN-assisted cooperative localization in vehicular networks

Jewon Eom, Hyowon Kim, Sang Hyun Lee, Sunwoo Kim

    Research output: Contribution to journalArticlepeer-review

    13 Citations (Scopus)

    Abstract

    This work develops a deep-learning-based cooperative localization technique for high localization accuracy and real-time operation in vehicular networks. In cooperative localization, the noisy observation of the pairwise distance and the angle between vehicles causes nonlinear optimization problems. To handle such a nonlinear optimization task at each vehicle, a deep neural network (DNN) technique is to replace a cumbersome solution of nonlinear optimization along with the saving of the computational loads. Simulation results demonstrate that the proposed technique attains some performance gain in localization accuracy and computational complexity as compared to existing cooperative localization techniques.

    Original languageEnglish
    Article number2758
    JournalEnergies
    Volume12
    Issue number14
    DOIs
    Publication statusPublished - 2019

    Bibliographical note

    Funding Information:
    This work was partly supported by Institute for Information and Communications Technology Promotion (IITP) grant funded by the Korean government (MSIT) (No. 2017-0-00316, Development of Fundamental Technologies for the Next Generation Public Safety Communications) and Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services).

    Funding Information:
    Acknowledgments: This work was partly supported by Institute for Information and Communications Technology Promotion (IITP) grant funded by the Korean government (MSIT) (No. 2017-0-00316, Development of Fundamental Technologies for the Next Generation Public Safety Communications) and Institute of Information & Communications Technology Planning & Evaluation (IITP) grant funded by the Korea government (MSIT) (2016-0-00208, High Accurate Positioning Enabled MIMO Transmission and Network Technologies for Next 5G-V2X (vehicle-to-everything) Services).

    Publisher Copyright:
    © 2019 by the authors

    Keywords

    • Cooperative localization
    • Deep neural network
    • Internet of vehicle
    • Multilateration
    • Vehicular networks

    ASJC Scopus subject areas

    • Renewable Energy, Sustainability and the Environment
    • Energy Engineering and Power Technology
    • Energy (miscellaneous)
    • Control and Optimization
    • Electrical and Electronic Engineering

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