One of the 5G use cases, known as ultra- reliable communication (URC), is expected to support very low packet error rate on the order of $10^{-5}$ with a 1 ms latency. In an industrial scenario, this would make possible replacing wired connections with wireless for controlling critical processes. Industrial environments with large metallic machinery and concrete structures can lead to deep shadowing and severe fading in the radio propagation channel, and thus pose a challenge for achieving the outage levels in connection with URC. In this paper, we present and analyze the large-scale propagation characteristics of two different industrial environments - open production space and dense factory clutter - based on measurements conducted at 2.3 and 5.7 GHz. By including a large number of spatially distributed samples, as per our experimental approach, we show the importance of properly characterizing the large-scale fading outage for URC. For instance, we show that based on a simple one-slope distance dependent path loss model, the conventional log-normal model for large-scale shadow fading is by far too simple for this environment. Our results show that at the 10^{-4} percentile, the tail of the shadow fading distribution can deviate by up to 10-20 dB from the log-normal model with respect to the average NLOS values (around 6 dB and 8 dB at 2.3 and 5.7 GHz, respectively). The simplicity of the one-slope path loss model, and its ability as we show, to express the trends with respect to scenarios, frequencies, and antenna heights, makes it an attractable option. However, there is a need for further experimental insight, possibly in combination with deterministic analysis, to get a better understanding of the large-scale fading for the study of URC in industrial environments.


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    Titel :

    Radio Propagation Analysis of Industrial Scenarios within the Context of Ultra-Reliable Communication




    Erscheinungsdatum :

    01.06.2018


    Format / Umfang :

    2193147 byte





    Medientyp :

    Aufsatz (Konferenz)


    Format :

    Elektronische Ressource


    Sprache :

    Englisch



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