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Generalised and channel independent SVM based robust decoders for wireless applications

Publication Type : Conference Paper

Publisher : ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing

Source : ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala (2009)

Url : http://www.scopus.com/inward/record.url?eid=2-s2.0-73849105549&partnerID=40&md5=758e044771225b7de1b937128f126dc8

ISBN : 9780769538457

Keywords : Channel independent, Channel model, Coding techniques, Convolution, Convolutional codes, Decoding, Emerging applications, Error correction, Error correction codes, Hamming code, Hamming codes, Learning algorithms, Machine learning algorithms, Modulation techniques, Multiclass classification problems, Neural networks, Radio, Software-defined radios, Support vector machines, SVM model, Video streaming, Viterbi, Viterbi algorithm, Viterbi decoder, Wireless application, Wireless communications, Wireless networks, Wireless telecommunication systems

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2009

Abstract : Emerging applications in wireless communications and Software Defined Radio require robust and generalized decoders with a very good efficiency. This paper aims at introducing a novel and powerful method of implementing a decoder using Support Vector Machines (SVM) to exhibit good performance irrespective of the channel model. The method proposed also ensures a generalization in the design of decoder, which can be easily adaptable for any type of coding technique used. In addition, this method overcomes the demerits of the traditional decoders like Viterbi and other decoders using Neural Networks. The error correction codes like Hamming and Convolutional codes are considered for experimentation. Using SVM, which is a class of machine learning algorithm, this process is viewed as a multi-class classification problem and error correction is achieved in a simpler way. An extensive analysis with regard to the effect of channel and modulation techniques is also made and presented. The proposed SVM model is sufficiently cross validated and found to be an effective replacement for the existing counterparts. © 2009 IEEE.

Cite this Research Publication : Dr. Ramanathan R., Valliappan, N., Mathavan, S. P., Gayathri, M., Priya, R., and Dr. Soman K. P., “Generalised and channel independent SVM based robust decoders for wireless applications”, in ARTCom 2009 - International Conference on Advances in Recent Technologies in Communication and Computing, Kottayam, Kerala, 2009.

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