In this work, a channel estimation method for OTFS using superimposing pilot is proposed. The pilot is superimposing on the first transmitter data symbol, yielding an enhanced frequency domain of Delay-Doppler domain pattern at the receiver end. A deep convolution neural network is proposed to de-noise the interfered channel matrix. Simulation results show that the bit error rate performance of the proposed method is better than that of the existing methods at low pilot energy.


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    Titel :

    Delay-Doppler Frequency Domain-Aided Superimposing Pilot OTFS Channel Estimation Based on Deep Learning


    Beteiligte:
    Yang, Chaoyi (Autor:in) / Wang, Junlong (Autor:in) / Pan, Zhenni (Autor:in) / Shimamoto, Shigeru (Autor:in)


    Erscheinungsdatum :

    01.09.2022


    Format / Umfang :

    3493095 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




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