A Neural Network-based approach for Decoding of an Image of Low-Girth LDPC Code

A Neural Network-based approach for Decoding of an Image of Low-Girth LDPC Code

© 2022 by IJETT Journal
Volume-70 Issue-11
Year of Publication : 2022
Authors : Dharmeshkumar Patel, Ninad Bhatt
DOI : 10.14445/22315381/IJETT-V70I11P233

How to Cite?

Dharmeshkumar Patel, Ninad Bhatt, "A Neural Network-based approach for Decoding of an Image of Low-Girth LDPC Code," International Journal of Engineering Trends and Technology, vol. 70, no. 11, pp. 305-314, 2022. Crossref, https://doi.org/10.14445/22315381/IJETT-V70I11P233

The decoding of low-girth Low-Density Parity-Check code using the conventional method generates an error floor during decoding. Therefore, a neural network-based decoder can be used to overcome this problem to decode lowgirth code. However, the neural network-based decoder may not be best suitable for high-girth code. In the current work, a neural network-based low-girth LDPC decoder is developed to decode an image sample of low as well as high-girth code. The NN decoder performs best for low-girth code. However, performance in comparison with a similar decoder, the decoder developed in the current work has improved bit error rate for the same signal-to-noise ratio.

Feed-forward neural network, High-girth code, Low-density parity-check code, Low-girth code, Min-sum decoder.

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