Conception d'un système de communication sans fil industriel basé sur la transformée en ondelettes

Abstract : In this thesis, we will present a multi-user communication architecture based on wireless sensor networks in a noisy industrial environment. Two modes of operation of this architecture are presented ; a Many-To-One mode linking several transmitter sensors to a single receiver and a One-To-Many mode linking a transmitter to several receiver sensors. The physical layer of this system is based on the inverse transform (IDWPT) at transmission and the discrete wavelet packet transform (DWPT) at reception. To test our architecture, an industrial channel model is proposed that takes into account the phenomena of multipath and fading in addition to additive noise. The latter being modelled as Gaussian noise to which is added an impulse noise causing significant signal degradation. The architecture is tested for different wireless communication configurations and wavelet shapes to provide an optimal communication mode. Also, an improvement in the robustness of our system is achieved by adding channel error correction coding and pulse noise thresholding at reception to minimize the effects of industrial noise on the received signals. Using an error-correcting code, the detection and reconstruction of signals is error-free from an SNR of 8dB for a coding rate of 1/4 for transmission on a fading channel. For an optimal receiver based on noise thresholding, the performance in terms of binary error rates is improved by 10dB for transmission over an industrial noise channel. Finally, a comparison of the robustness of our pulse architecture with a system based on a conventional OFDM multi-carrier modulation is carried out. This leads us to propose a robust multi-user communication system based on wireless sensor networks for communications in difficult industrial environments.
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Safa Saadaoui. Conception d'un système de communication sans fil industriel basé sur la transformée en ondelettes. Automatique. Université de Lorraine, 2019. Français. ⟨NNT : 2019LORR0048⟩. ⟨tel-02328130⟩

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