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Spectral Efficiency Comparison Between FTN Signaling and Optimal PR Signaling for Low Complexity Detection Algorithm

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Internet of Things, Smart Spaces, and Next Generation Networks and Systems (NEW2AN 2018, ruSMART 2018)

Part of the book series: Lecture Notes in Computer Science ((LNCCN,volume 11118))

Abstract

This paper is devoted to detection of signals with intentionally introduced intersymbol interference (ISI). Faster-than-Nyquist (FTN) signaling and optimal partial response signaling (PRS) are considered. As the detection algorithm it is used a sub-optimal modification of BCJR algorithm, named Max-Log-M-BCJR. Signals are compared in the plane of spectral efficiency and energy consumptions for the fixed value of bit error rate (BER) and different grades of detection algorithm complexity. It is shown that using the sub-optimal BCJR algorithm provides a noticeable decrease in the computational complexity of the detection. For deep ISI optimal PR signaling provides higher spectral efficiency as compared with FTN signaling and vise versa.

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Authors and Affiliations

  1. Peter the Great St. Petersburg Polytechnic University, St. Petersburg, Russia

    Aleksei Plotnikov & Aleksandr Gelgor

Authors
  1. Aleksei Plotnikov
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  2. Aleksandr Gelgor
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Correspondence to Aleksei Plotnikov .

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Editors and Affiliations

  1. Tampere University of Technology, Tampere, Finland

    Olga Galinina

  2. Tampere University of Technology, Tampere, Finland

    Sergey Andreev

  3. FRUCT Oy, Helsinki, Finland

    Sergey Balandin

  4. Tampere University of Technology, Tampere, Finland

    Yevgeni Koucheryavy

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Plotnikov, A., Gelgor, A. (2018). Spectral Efficiency Comparison Between FTN Signaling and Optimal PR Signaling for Low Complexity Detection Algorithm. In: Galinina, O., Andreev, S., Balandin, S., Koucheryavy, Y. (eds) Internet of Things, Smart Spaces, and Next Generation Networks and Systems. NEW2AN ruSMART 2018 2018. Lecture Notes in Computer Science(), vol 11118. Springer, Cham. https://doi.org/10.1007/978-3-030-01168-0_18

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  • DOI: https://doi.org/10.1007/978-3-030-01168-0_18

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-01167-3

  • Online ISBN: 978-3-030-01168-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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