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2 Journal of Telecommunications and Information Technology

2 2016

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Support Vector Machine based Decoding Algorithm for BCH Codes

Sudharsan V., Yamuna B.

Journal of Telecommunications and Information Technology

2016

nr 2

108--112

Modern communication systems require robust, adaptable and high performance decoders for efficient data transmission. Support Vector Machine (SVM) is a margin based classification and regression technique. In this paper, decoding of Bose Chaudhuri Hocquenghem codes has been approached as a multi-class classification problem using SVM. In conventional decoding algorithms, the procedure for decoding is usually fixed irrespective of the SNR environment in which the transmission takes place, but SVM being a machinelearning algorithm is adaptable to the communication environment. Since the construction of SVM decoder model uses the training data set, application specific decoders can be designed by choosing the training size efficiently. With the soft margin width in SVM being controlled by an equation, which has been formulated as a quadratic programming problem, there are no local minima issues in SVM and is robust to outliers.

An Efficient Early Iteration Termination for Turbo Decoder

Salija P., Yamuna B.

Journal of Telecommunications and Information Technology

2016

nr 2

113--122

Turbo code finds wide applications in mobile communication, deep space communication, satellite communication and short-range communication despite its high computational complexity and iterative nature. Realizing capacity approaching turbo code is a great achievement in the field of communication systems due to its efficient error correction capability. The high computational complexity associated with the iterative process of decoding turbo code consumes large power, introducing decoding delay, and reducing the throughput. Hence, efficient iteration control techniques are required to make the turbo code more power efficient. In this paper, a simple and efficient early iteration termination technique is introduced based on absolute value of the mean of extrinsic information at the component decoders of turbo code. The simulation results presented clearly show that the proposed method is capable of reducing the average number of iterations while maintaining performance close to that of fixed iteration termination. The significant reduction in iteration achieved by the method reduces decoding delay and complexity while maintaining Bit Error Rate performance close to standard fixed iteration turbo decoder.