Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/144748
Title: Joint reconstruction of Reed-Solomon encoder and convolutional interleaver in a noisy environment
Authors: Swaminathan, Ramabadran
Madhukumar, A. S.
Wang, Guohua
Ting, Shang Kee
Keywords: Engineering::Computer science and engineering
Issue Date: 2018
Source: Swaminathan, R., Madhukumar, A. S., Wang, G. & Ting, S. K. (2018). Joint reconstruction of Reed-Solomon encoder and convolutional interleaver in a noisy environment. Proceedings of the 2018 International Symposium on Information and Its Applications (ISITA), 683-687. doi:10.23919/ISITA.2018.8664312
Abstract: Blind estimation of code and interleaver parameters plays a vital role in various applications such as non-cooperative systems, adaptive modulation and coding, signal intelligence, etc. The present paper proposes novel algorithms to jointly estimate code and interleaver parameters from Reed-Solomon (RS) coded and convolutionally interleaved data stream based on the rank ratio and non-zero-mean-ratio values for noiseless and noisy environments, respectively. Simulation results validating the proposed algorithms are given for various test cases and the accuracy of estimation of convolutional interleaver and RS code parameters is investigated for different values of interleaver width and modulation schemes. It is inferred that the accuracy of parameter estimation improves with decrease in modulation order and interleaver width of convolutional interleaver.
URI: https://hdl.handle.net/10356/144748
ISBN: 978-4-88552-318-2
DOI: 10.23919/ISITA.2018.8664312
Rights: © 2018 Institute of Electronics, Information and Communication Engineers (IEICE). All rights reserved. This paper was published in 2018 International Symposium on Information and Its Applications (ISITA) and is made available with permission of Institute of Electronics, Information and Communication Engineers (IEICE).
Fulltext Permission: open
Fulltext Availability: With Fulltext
Appears in Collections:SCSE Conference Papers

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