B. , Performances pour un canal à évanouissements en présence du bruit industriel

, En considérant maintenant l'eet du bruit industriel, notre architecture de communication permet de détecter entièrement l'information à partir d'un SNR de 30dB tel que illustré sur la gure, vol.26

, L'écart des taux d'erreur est très considérable et dépend du canal de propagation

, Amélioration de la robustesse de l'architecture Figure 5.27 Architecture OTM avec codage correcteur d'erreur

, Codage du canal

, Ceci permettra d'améliorer la robustesse du système de communication et ainsi rendre la qualité des signaux reçus plus able. Pour un code de rendement 1/2 la détection des signaux se fait sans aucune erreur à un SNR de 8dB pour un canal à évanouissement tel que présenté sur la gure(5.28). Et pour un codage avec un taux de 1/4 les erreurs sont éliminées à, Combattre les eets du canal à évanouissement nécessite l'utilisation d'un bloc d'encodage du canal à l'émission (gure 5.27)

, Surtout que les réseaux de capteurs sans l sont contraints à fonctionner avec une énergie optimale. D'où l'intérêt de la diversité spatiale permettant de récupérer l'information sur au moins un capteur dans le cas où un autre capteur est en ressources limités en termes d'énergie

, Ce modèle doit illustrer les diérents phénomènes de propagation tels les évanouissements, interférences et les variations temporelles dues à la mobilité. Ceci pourrait se faire en faisant des mesures réelles en utilisant une plateforme de test, Cette plateforme modélisera au mieux un environnement industriel et comportera plusieurs capteurs qui opèrent à diérentes fréquences et portées selon les applications et les technologies que nous souhaitons tester. REVUES

S. Saadaoui, M. Tabaa, F. Monteiro, M. Chehaitly, and A. Dandache, Discrete Wavelet Packet Transform based Industrial Digital Wireless Communication Systems, vol.10, p.104, 2019.

M. Chehaitly, M. Tabaa, F. Monteiro, S. Saadaoui, and A. Dandache, High Troughput congurable architecture based on IDWPT/DWPT for Impulse Radio Wireless Communications, AIP-CP Journal, 2019.

M. Tabaa, S. Saadaoui, M. Chehaitly, and A. Dandache, NLOS Identication for UWB Body communications, International Journal of Computer Applications, vol.124, 2015.

A. Khalil, S. Saadaoui, and M. Tabaa, Performances of Convolutional and Reed-Solomon codes for IWSN applications, 2019.

M. Tabaa, B. Chouri, and S. Saadaoui, Industrial Communication based on Modbus and Node-RED, Procedia Computer Science, vol.130, pp.583-588, 2018.

S. Saadaoui, M. Tabaa, F. Monteiro, M. Chehaitly, A. Dandache et al., Industrial WSN Based on Discrete Wavelet Packet Transform for Smart Factory Wireless Communications, Available at SSRN, 2018.

S. Saadaoui, M. Tabaa, F. Monteiro, and A. Dandache, IWSN Based on DWPT Using an Industrial Noisy Channel for Industry 4.0 Wireless Applications, Proceedings of the 2018 International Conference on Software Engineering and Information Management, pp.113-117, 2018.

S. Saadaoui, M. Tabaa, F. Monteiro, M. Chehaitly, A. Dandache et al., IWSN under an industrial wireless channel in the context of, 29th International Conference on, pp.1-4, 2017.

S. Saadaoui, M. Tabaa, F. Monteiro, and A. Dandache, Journée doctorale des sciences de l'ingénieur 3éme édition, 2016.

S. Saadaoui, M. Chehaitly, M. Tabaa, F. Monteiro, and A. Dandache, Vers une nouvelle approche des communications impulsionnelles ULB basée sur la transformée par paquet d'ondelette', 5th Edition On Innovation and News Trends in Information Systems INTIS, 2016.

S. Saadaoui, M. Chehaitly, M. Tabaa, F. Monteiro, A. Dandache et al., A new WSN Transceiver based on DWPT for WBAN applications, IEEE International conference on Microelectronics ICM2015, pp.20-23

, Magasine Schneider Electric de l'enseignement technologique er professionnel : Les bus et les réseaux de terrain en automatisme industriel Schneider Electric, 2002.

T. Sauter, The three generations of eld-level networksEvolution and compatibility issues, IEEE Transactions on Industrial Electronics, vol.57, issue.11, pp.3585-3595, 2010.

, Rapport technique de Phoenix 'Industrial Wireless : industrial wireless Communication sans l du capteur jusqu'au réseau', Phoenix Contact inspiring innovation, 2012.

M. Andersson, Wireless Technologies for Industrial applications, ConnectBlue Février, 2013.

. Jp and . Hauet, Aperçu sur les nouvelles communications sans l et leurs applications dans l'industrie, 2004.

S. Sesia, M. Baker, and I. Touk, LTE -The UMTS Long Term Evolution : From Theory to Practice, p.421456, 2011.

F. Hu and Q. Hao, Intelligent Sensor Network : The Integration of Sensor Networks Signal Processing and Machine Learning, pp.978-979, 2013.

, Semiannual technical summary report of the defense advanced research projects agency, 1987.

P. Corke, T. Wark, R. Jurdak, W. Hu, P. Valencia et al., Environmental Wireless Sensor Networks, vol.98, 2010.

M. R. Yuce, Implementation of wireless body area networks for healthcare systems', sensors and actuators A, vol.162, pp.116-129, 2010.

J. A. Gutiérrez, D. B. Durocher, B. Lu, R. G. Harley, and T. G. Habelter, pplying Wireless Sensor Networks in industrial Plant Energy Evaluation and Planning Systems, 2005.

F. Abdelfatah, Développement d'une bibliothèque de capteurs', 2008.

M. Wollschlaeger, T. Sauter, J. , and J. , The future of industrial communication : Automation networks in the era of the internet of things and industry 4.0, IEEE Industrial Electronics Magazine, vol.11, issue.1, pp.17-27, 2017.

B. Michael-dorge and T. Scheer, Using ipv6 and 6lowpan for home automation networks, Consumer Electronics-Berlin (ICCE-Berlin), 2011 IEEE International Conference on, p.4447, 2011.

H. Sasajima, T. Ishikuma, and H. Hayashi, Future IIOT in process automationLatest trends of standardization in industrial automation, IEC/TC65.' Society of Instrument and Control Engineers of Japan (SICE), 2015.

J. Zuniga, B. Carlos, and . Ponsard, Sigfox system description, vol.97, 2016.

L. Vangelista, A. Zanella, and M. Zorzi, Long-range IoT technologies : The dawn of LoRa, Future Access Enablers of Ubiquitous and Intelligent Infrastructures, pp.51-58, 2015.

R. S. Sinha, Y. Wei, and S. H. Hwang, A survey on LPWA technology : LoRa and NB-IoT, vol.3, pp.14-21, 2017.

M. Lauridsen, From LTE to 5G for connected mobility, IEEE Communications Magazine, vol.55, pp.156-162, 2017.

J. B. Keller, Geometrical Theory of Diraction, J. Opt. Soc. Am, vol.52, issue.2, p.22, 1962.

M. Paetzold, Mobile Fading Channels, 2002.

H. Hijazi, Estimation de canal radio-mobile à évolution rapide dans les systèmes à modulation OFMD, 2008.

T. S. Rappaport, Wireless communications : principles and practice, vol.2, 1996.

J. D. Parsons, The Mobile Radio Propagation Channel, 2000.

S. R. Saunders and A. Aragon, Antennas and Propagation for Wireless communication Systems, vol.2, 2007.

J. , Industrial environment characterization for future M2M applications, Electromagnetic Compatibility (EMC), IEEE International Symposium, 2011.

S. Y. Wang, P. F. Wang, Y. W. Li, and L. C. Lau, Design and Implementation of a more Realistic Radio Propagation Model for Wireless Vehicular Networks over the NC-TUns Network Simulator, IEEE WCNC (Wireless Communications and N etworking Conference), 2011.

P. Mariage, M. Liénard, and P. Degauque, Theoretica1 and Experimental Approach of the Propagation of High Frequency Waves in Road Tunnels, IEEE Transactions on Antennas and Propagation, issue.1, p.81, 1994.

S. Rappaport, Indoor radio communication for factories of the future', IEEE communication magazine, 1989.

S. Kjesbu and T. Brunsvik, Radiowave propagation in industrial environments' Industrial Electronics Society, vol.4, 2000.

E. Tanghe, The industrial indoor channel : large-scale and temporal fading at 900, 2400, and 5200 MHz, IEEE Transactions on Wireless Communications, vol.7, issue.7, 2008.

S. Rappaport, Statistical channel impulse response models for factory and open plan building radio communication system design, IEEE transactions on communications, vol.39, issue.5, 1991.

A. A. Saleh and R. Valenzuela, A statistical model for indoor multipath propagation, IEEE Journal on selected areas in communications, vol.5, pp.128-137, 1987.

J. , A measurement-based statistical model for industrial ultra-wideband channels, IEEE transaction on wireless communications, vol.6, issue.8, 2007.

, Wireless Communication for industrial Applications, 2002.

C. Holloway, M. Cotton, and P. Mckenna, A model for predicting the power delay prole characteristics inside a room, IEEE Trans. on Vehicular Technolog, vol.48, issue.4, p.11101120, 1999.

M. Cheena, Industrial indoor multipath propagationA physical-statistical approach', Personal, Indoor, and Mobile Radio Communication (PIMRC), IEEE 25th Annual International Symposium on, 2014.

M. Cheena, Propagation channel characteristics of industrial wireless sensor networks, IEEE Antennas and Propagation Magazine, vol.58, pp.66-73, 2016.

E. Tanghe, The industrial indoor channel : Statistical analysis of the power delay prole', International journal of electronics and communication AEU, 2009.

J. Coll and . Ferrer, Rf channel characterization in industrial, hospital and home environments', Licentiate thesis, 2012.

H. Sheikh, On the design of a wireless network in an industrial environment, IEEE Communication Systems (ICCS), 2010.

K. S. Yee, Numerical solution of initial boundary value problems insolving maxwell's equations in isotropic media, IEEE Antennas and Propagation, 1966.

Y. Chartois, Étude paramétrique avancée de canaux SISO et MIMO en environnements complexes : Application au système HiperLAN/2

, Université Rennes, vol.1, 2005.

H. Ling, R. Chou, and S. Lee, Shooting and bouncing rays : calculating the rcs of an arbitrarily shaped cavity'. Antennas and Propagation, IEEE Transactions on, vol.37, issue.2, p.205, 1989.

T. Huschka, Ray tracing models for indoor environments and their computational complexity'. In Personal, Indoor and Mobile Radio Communications, 5th IEEE International Symposium on, vol.490, p.486, 1994.

Y. Karasawa, K. Minamisoto, and T. Matsudo, Propagation channel model for personal mobile satellite systems, PIERS'94 Conference, 1994.

E. Lutz, D. Cygan, M. Dippold, F. Dolainsky, and W. Papke, The land mobile satellite communication channel-recording', statistics, and channel model, IEEE Trans. Veh

. Technol, , vol.40, p.375386, 1991.

A. Anthony and S. , Modelisation du canal de propagation par satellite dans les bandes, 2009.

X. Li, Un modèle hybride statistique-déterministe du canal LMS en environnements complexes, 2010.

K. E. Essamlali and . Hariri, Modélisation hybride du canal radio dans un contexte industriel, 18ièmes Journées Nationales Microondes, 2013.

H. A. Myers, Industrial equipment spectrum signatures, IEEE Transactions on Radio Frequency Interference, vol.5, pp.30-42, 1963.

S. Zabin and H. Poor, Parameter estimation for middleton class a interference processes, IEEE Trans. on Communications, vol.37, issue.10, p.10421051, 1989.

Q. Shan, Characteristics of impulsive noise in electricity substations, Signal Processing Conference, 2009.

S. Bhatti and . Ahmed, Vulnerability of Zigbee to impulsive noise in electricity substations, General Assembly and Scientic Symposium, 2011.

G. Tsihrintzis and C. Nikias, Fast estimation of the parameters of alpha-stable impulsive interference, IEEE Transactions on Signal Processing, vol.44, issue.6, pp.1492-1503, 1996.

Y. Kim and G. Zhou, Representation of the Middleton class B model by symmetric alpha-stable processes and chi-distributions, Fourth International Conference on Signal Processing Proceedings, 1998. ICSP'98, p.180183, 1998.

K. A. Saaifan and W. Henkel, Decision boundary evaluation of optimum and suboptimum detectors in class-A interference, IEEE Transactions on Communications, vol.61, pp.197-205, 2013.

S. Park and . Keun, Method and apparatus for impulsive noise mitigation using adaptive blanker based on BPSK modulation system, vol.118, p.25

S. Tarik, I. M. Shehata, and M. Al-tanany, Suboptimal detectors for alpha stable noise : Simpling design and improving performances, IEEE Transactions on Communications, vol.60, issue.10, pp.2982-2989, 2012.

S. V. Zhidkov, Impulsive noise suppression in OFDM-based communication systems, IEEE Transactions on Consumer Electronics, vol.49, pp.944-948, 2003.

X. Hu, Z. Chen, and F. Yin, Impulsive noise cancellation for MIMO power line communications, Journal of Communications, vol.9, pp.241-247, 2014.

H. Oh, H. Nam, and S. Park, Adaptive threshold blanker in an impulsive noise environment, IEEE Transactions on Electromagnetic Compatibility, vol.56, pp.1045-1052, 2014.

S. Hakimi and G. Hodtani, Generalized maximum correntropy detector for non-Gaussian environments, International Journal of Adaptive Control and Signal Processing32, vol.1, pp.83-97, 2018.

K. Wong and . Daniel, Physical layer considerations for wireless sensor networks, IEEE International Conference on Networking, Sensing and Control, vol.2, 2004.

J. Yick, B. Mukherjee, and D. Ghosal, Wireless sensor network survey' Computer networks 52, vol.12, pp.2292-2330, 2008.

M. Ghavami, L. B. Michael, S. Haruyama, and R. Kohno, A novel UWB pulse shape modulation system, vol.23, pp.105-120, 2002.

G. Mastroianni and G. Milovanovic, , pp.75-192, 2008.

M. Gautier, Algorithmes et architectures de récepteurs pour les systèmes multiporteuses par paquets d'ondelettes' Diss, 2006.

S. Ciolino, M. Ghavami, and H. Aghvami, Wavelet-based ultra wideband pulse generator circuits, IET communications, vol.2, pp.642-649, 2008.

M. Lakshmanan, H. Kumar, and . Nikookar, A review of wavelets for digital wireless communication, Wireless personal communications, vol.37, pp.387-420, 2006.

M. Lakshmanan, H. Kumar, and . Nikookar, Construction of optimum wavelet packets for multi-carrier based spectrum pooling systems', Wireless personal communications54, vol.1, pp.95-121, 2010.

M. Tabaa, A novel transceiver architecture based on wavelet packet modulation for UWB-IR WSN applications', Wireless Sensor Network, p.191, 2016.

R. X. Gao and R. Yan, Wavelets : Theory and applications for manufacturing, 2010.

S. G. Mallat, A theory for multiresolution signal decomposition : the wavelet representation, vol.11, pp.674-693, 1989.

H. Karl and A. Willig, Protocols and architectures for wireless sensor networks, 2005.

I. Rhee, A. Warrier, J. Min, and L. X. Drand, distributed Randomized TDMA scheduling for wireless ad-hoc networks, MobiHoc conference, 2006.

S. Mukherejee and G. P. Biswas, Design of hybrid MAC protocol for wirless sensor network, Recent advances in information technology', Advances in intelligent systems and computing 266, 2014.

S. De, C. Qiao, A. Pados, M. Chatterjee, and S. J. Philip, An integrated cross-layer study of wireless CDMA sensor networks, IEEE journal on selected areas in communications, vol.22, issue.7, 2004.

J. Decotignie, Ethernet-based real-time and industrial communications, Proceedings of the IEEE 93, vol.6, pp.1102-1117, 2005.

W. Hou, W. Liu, and M. Fei, A token-based MAC oriented wireless industrial control networks, IEEE International Conference on Information Acquisition, 2006.

S. Saadaoui, M. Tabaa, F. Monteiro, A. Dandache, and K. Alami, A new WSN Transceiver based on DWPT for WBAN applications', International conference on Microelectronics ICM2015, pp.20-23

S. Saadaoui, M. Tabaa, F. Monteiro, M. Chehaitly, and A. Dandache, Industrial WSN Based on Discrete Wavelet Packet Transform for Smart Factory Wireless Communications, Available at SSRN, 2018.

S. Saadaoui, M. Tabaa, F. Monteiro, and A. Dandache, IWSN Based on DWPT Using an Industrial Noisy Channel for Industry 4.0 Wireless Applications, Proceedings of the 2018 International Conference on Software Engineering and Information Management, pp.113-117

D. Dessales, Conception d'un réseau de capteurs sans l, faible consommation, dédié au diagnostic in-situ des performances des bâtiments en exploitation, 2011.

M. M. Salah and A. A. Elrahman, Energy eciency based concatenated LDPC and turbo codes for wireless sensor networks, Communications and Computing (ICSPCC), 2015 IEEE International Conference on, 2015.

L. Liang, Energy-ecient design and implementation of turbo codes for wireless sensor network' Diss, 2012.

D. Schmidt, M. Berning, and N. Wehn, Error Correction in Single-Hop Wireless Sensor Networks : A Case Study, Proceedings of the Conference on Design, Automation and Test, p.12961301, 2009.

A. Viterbi, Error Bounds for Convolutional Codes and an Asymptotically Optimum Decoding Algorithm, IEEE Transactions on Information Theory, vol.13, issue.2, p.260269, 1967.

R. V. Nee and R. Prasad, OFDM for wireless multimedia communications, 2000.