Motivated by the emerging internet of things (IoT) applications, wireless systems encounter the challenges of providing accurate indoor localization to massive IoT devices. Although the received signal strength indicator (RSSI)-based fingerprinting can provide accurate localization with low system requirements, it still suffers from multipath and fading effects. To resolve this, we propose a beam domain-based fingerprinting localization that can leverage the spatial feature with multiple antenna systems to improve the localization. Specifically, we consider using the beam domain receive power map (BDRPM), which is an RSSI-based map that captures important features of spatial fingerprints of the environment, for localization. To learn the environmental fingerprints via using BDRPMs and to conduct the localization, we propose a deep-learning approach based on the 2D convolutional neural network and auto-encoder structure. We conduct practical simulations to evaluate our proposed localization approach. The results show that our approach can provide very accurate localization, be resistant to environmental changes, and outperform the reference schemes in the literature.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Beam Domain Based Fingerprinting Indoor Localization with Multiple Antenna Systems


    Beteiligte:
    Yang, Chia-Hsing (Autor:in) / Lee, Ming-Chun (Autor:in) / Lin, Chia-Hung (Autor:in) / Lee, Ta-Sung (Autor:in)


    Erscheinungsdatum :

    01.06.2022


    Format / Umfang :

    1130603 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



    Multi-site fusion for WLAN based indoor localization via maximum discrimination fingerprinting

    Shata, Amr M. / El-Hamid, Salma S. Abd / Heiba, Yehia A. et al. | IEEE | 2018


    Indoor Localization with Irregular Antenna Deployment

    Zheng, Yang / Liu, Junyu / Sheng, Min et al. | IEEE | 2017


    Hybrid Bayesian-based Indoor Localization Mechanisms for Distributed Antenna Systems

    Tercas, Leonardo / de Lima, Carlos H. M. / Saloranta, Jani et al. | IEEE | 2021


    Covariance Difference of Arrival based Fingerprinting Localization

    Li, Xinze / Al-Tous, Hanan / Hajri, Salah Eddine et al. | IEEE | 2023