To estimate the probability of an event, conventional Monte Carlo (MC) needs $100/P_{\mathrm {e}}$ simulation runs to attain a 10% precision, where $P_{\mathrm {e}}$ is the probability of the event. It therefore encounters difficulty in simulation-based evaluation of packet error rates for ultra-reliable communication under its stringent requirement. Many fast simulation techniques for evaluating the probability of rare events have been proposed. However, a more efficient method for coded communication systems that can adaptively exploit the code structure and concentrate the generated noise vectors to the error-prone regions is desirable. We propose a method which seeks to adaptively learn a certain optimal histogram of the noise vectors and generate the noise vectors accordingly. The said histogram is a one-dimensional function and hence is easy to work with. The adaptation mechanism is code-agnostic. Simulation with cyclic redundancy check-aided polar coding in additive white Gaussian noise shows an approximately 10-100 times speed-up compared to conventional MC.


    Zugriff

    Zugriff prüfen

    Verfügbarkeit in meiner Bibliothek prüfen

    Bestellung bei Subito €


    Exportieren, teilen und zitieren



    Titel :

    Fast Simulation of Ultra-Reliable Coded Communication System via Adaptive Shaping of Noise Histogram


    Beteiligte:
    Yu, You-Zong (Autor:in) / Lin, David W. (Autor:in)


    Erscheinungsdatum :

    01.05.2020


    Format / Umfang :

    182569 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch




    Adaptive Hybrid ARQ (A-HARQ) for Ultra-Reliable Communication in 5G

    Cabrera, Emerson / Fang, Gengfa / Vesilo, Rein | IEEE | 2017


    Postprocessing of transform coded images via histogram-based edge classification

    McDonnell, J. D. / Shorten, R. N. / Fagan, A. D. | British Library Online Contents | 1997


    A Shaping Algorithm of Coded Amplitude Spectrum for Anti-Interference in Transform Domain Communication System

    Liu, Li / Zhang, Hengyang / Mao, Yuquan et al. | British Library Online Contents | 2017