Abstract
In industries, the usage of wireless sensors has been increased tremendously due to various advantages like maintenance, convenient installation, and cable cost reduction. However, the transmission of signals over a wireless channel in a harsh industrial environment is vulnerable to interference of noise resulting in the introduction of errors. This leads to the corruption of data which may result in incorrect feedback that may lead to safety-related problems or economic loss. Thus, in order to reduce the errors, forward error correction codes (FEC) can be used to improve the reliability of the signal transmission. In this paper, the implementation of convolution coding technique in an industrial environment is presented, and the performance has been evaluated in MATLAB/Simulink by comparing bit error rate (BER) with signal-to-noise ratio (SNR).
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Morozov, I.V.: Transfer characteristics of coaxial cable lines. Widespread errors. In: International Conference on High-Power Practical Beams (BEAMS 2004), 18–23 July 2004
Yamaji, M., Ishii, Y., Shimamura, T., Yamamoto, S.: Wireless sensor networks for industrial automation. In: Proceedings of 3rd International Conference on Networked Sensing System (2006)
Eren, H.: Wireless Sensors and Instruments: Network, Design and Applications. CRC-Press, Boca Raton, USA (2006)
Lenz, J.E., Edelstein, S.: Magnetic sensors and their applications. IEEE Sens. J. 6(3) (2006 June)
Yamasaki, H.: What are Intelligent Sensors. Handbook of Sensors and Actuators, vol. 3, pp. 1–17 (1996)
Shannon, C.E.: Communications in the presence of noise. Proc. IEEE 86(2), 447–457 (1998)
Simon, M.K., Alouini, M.S.: Digital Communication over Fading Channels: A Unified Approach to Performance Analysis. Copyright 2000, Willey
Chavan, M.S., Chile, R.H., Sawant, S.R.: Multipath fading channel modeling and performance comparison of wireless channel models. Int. J. Electron. Commun. Eng. 4(2), 189–203 (2011)
Perez Fontan, F., Marino Espineria, P.: Modeling the wireless propagation channel: a simulation approach with MATLAB. Willey (2008)
Hamdan, M., Abdullah, A.: Analysis and performance evaluation of convolutional codes over binary symmetric channel using MATLAB. In: Proceedings of the Second International Conference on Electrical and Electronic Engineering, Telecommunication Engineering and Mechatronics, Philippines (2016)
Hamming, R.W.: Error detecting and error correcting codes. Bell Syst. Tech. J. 29, pp. 147–160 (1950 Apr)
Li, X.: Simulink based simulation of quadrature amplitude modulation (QAM) system. In: Proceedings of the 2008 IAJC-IJME International Conference
Abubeker, K.M., et al.: Maximum likelihood decoding of convolutional codes using Viterbi algorithm with improved error correction capability. In: IEEE Conference on Information and Communication Technology, pp. 161–164 (2013)
Gangula, R.R., Gottapu, S.R.: BER analysis of LTE-4G standard Rayleigh Flat fading channel with adaptive modulation. Innov. Electron. Commun. Eng., 355–360
Goswami, R., Rao, G.S., Babu, R.: “8 state rate 2/3 TCM code design for fading channel. IEEE India Conference INDICON, pp. 323–326 (2008)
Rao, G.S.: Mobile Cellular Communication (2013)
Sasi Bhushana Rao, G., Sateesh Kumar, G., Kumar, M.N.V.S.S.: GPS signal Rician fading model for precise navigation in urban environment. Indian J. Radio Space Phys. 42, 192–196 (2013)
Dunn, W.C.: Fundamentals of Industrial Instrumentation and Process Control (2005)
Bergman, N.W., Hou, L.: Energy efficient machine condition monitoring using wireless sensor networks. In: 2014 International Conference on Wireless Communication and Sensor Network, pp. 285–290
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Prakash, V., Ramesh Patnaik, M. (2020). Design and Implementation of Convolution Coding Technique in Industrial Automation. In: Satapathy, S., Bhateja, V., Nguyen, B., Nguyen, N., Le, DN. (eds) Frontiers in Intelligent Computing: Theory and Applications. Advances in Intelligent Systems and Computing, vol 1014. Springer, Singapore. https://doi.org/10.1007/978-981-13-9920-6_10
Download citation
DOI: https://doi.org/10.1007/978-981-13-9920-6_10
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9919-0
Online ISBN: 978-981-13-9920-6
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)