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Underground Channel Model for Visible Light Wireless Communication Based on Neural Networks

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Trends and Innovations in Information Systems and Technologies (WorldCIST 2020)

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 1160))

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Abstract

An accurate channel model is both essential and challenging when designing a reliable wireless Visible Light Communication (VLC) system. Modeling the channel in a restricted and harsh environment such as an underground mine, is even more difficult. The objective in our work is to investigate a suitable design of a VLC link for an underground environment, while providing a reliable connectivity between the optical transmitter and optical receiver. In this paper, we present an experimental study that aims to determine a general model of an underground mine optical channel. Considering that the underground optical channel has a nonlinear dynamic behavior described by a nonlinear autoregressive exogenous (NARX) mathematical model, the system’s order is established with a feedforward neural network (NN), with a parallel architecture. In this work, in order to define a proper Underground Mine Optical Channel Model (UMOCM) for reliable VLC, we present an innovative approach based on a suitable mathematical model and neural networks (NNs).

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Author information

Authors and Affiliations

  1. University of Petrosani, 332006, Petrosani, Romania

    Simona Riurean, Olimpiu Stoicuta, Monica Leba & Andreea Ionica

  2. University of Coimbra, Coimbra, Portugal

    Álvaro Rocha

Authors
  1. Simona Riurean
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  2. Olimpiu Stoicuta
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  3. Monica Leba
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  4. Andreea Ionica
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  5. Álvaro Rocha
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Corresponding author

Correspondence to Simona Riurean .

Editor information

Editors and Affiliations

  1. Departamento de Engenharia Informática, Universidade de Coimbra, Coimbra, Portugal

    Álvaro Rocha

  2. College of Engineering, The Ohio State University, Columbus, OH, USA

    Hojjat Adeli

  3. FEUP, Universidade do Porto, Porto, Portugal

    Luís Paulo Reis

  4. DIMES, Università della Calabria, Arcavacata di Rende, Italy

    Sandra Costanzo

  5. Faculty of Electrical Engineering, University of Montenegro, Podgorica, Montenegro

    Irena Orovic

  6. Universidade Portucalense, Porto, Portugal

    Fernando Moreira

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© 2020 The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG

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Riurean, S., Stoicuta, O., Leba, M., Ionica, A., Rocha, Á. (2020). Underground Channel Model for Visible Light Wireless Communication Based on Neural Networks. In: Rocha, Á., Adeli, H., Reis, L., Costanzo, S., Orovic, I., Moreira, F. (eds) Trends and Innovations in Information Systems and Technologies. WorldCIST 2020. Advances in Intelligent Systems and Computing, vol 1160. Springer, Cham. https://doi.org/10.1007/978-3-030-45691-7_27

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