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    Full-Duplex Self Cancellation Techniques Using Independent Component Analysis

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    Type
    Conference Paper
    Authors
    Lu, Hsi-Hung
    Fouda, Mohammed E.
    Shen, Chung-An
    Eltawil, A.
    Date
    2020
    Permanent link to this record
    http://hdl.handle.net/10754/670948
    
    Metadata
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    Abstract
    Independent component analysis (ICA) has been shown as a promising means for solving the self-interference cancellation (SIC) problem for in-band full duplex systems. This paper presents a detailed analysis of the interference suppression capability and computational complexity of several different ICA algorithms, operating at either real-valued or complex-valued domain. In addition, on the basis of the setup of the full-duplex system, we show that a much simplified complex-valued ICA algorithm that only performs whitening and decorrelation processes are sufficient to separate the signal of interest from the mixed signal. Extensive simulation results are presented in this paper to illustrate the performance and complexity of various ICA approaches applying to the full-duplex system.
    Citation
    Lu, H.-H., Fouda, M. E., Shen, C.-A., & Eltawil, A. (2020). Full-Duplex Self Cancellation Techniques Using Independent Component Analysis. 2020 54th Asilomar Conference on Signals, Systems, and Computers. doi:10.1109/ieeeconf51394.2020.9443385
    Sponsors
    The authors gratefully acknowledge support from the National Science Foundation under award number 1710746.
    Publisher
    IEEE
    Conference/Event name
    54th Asilomar Conference on Signals, Systems and Computers, ACSSC 2020
    ISBN
    9780738131269
    DOI
    10.1109/IEEECONF51394.2020.9443385
    Additional Links
    https://ieeexplore.ieee.org/document/9443385/
    ae974a485f413a2113503eed53cd6c53
    10.1109/IEEECONF51394.2020.9443385
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