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https://hdl.handle.net/10356/144740
Title: | Parameter identification of Reed-Solomon codes over noisy environment | Authors: | Swaminathan, Ramabadran Madhukumar, A. S. Wang, Guohua Ting, Shang Kee |
Keywords: | Engineering::Computer science and engineering | Issue Date: | 2017 | Source: | Swaminathan, R., Madhukumar, A. S., Wang, G., & Ting, S. K. (2017). Parameter identification of Reed-Solomon codes over noisy environment. Proceedings of the 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall), 1-5. doi:10.1109/VTCFall.2017.8287916 | Conference: | 2017 IEEE 86th Vehicular Technology Conference (VTC-Fall) | Abstract: | Blind reconstruction of code parameters plays a vital role in non-cooperative applications. It also provides additional advantages in applications such as adaptive modulation and coding, reconfigurable receivers, etc. In this paper, blind estimation algorithm is proposed to identify Reed-Solomon (RS) code parameters at the receiver over noisy channels. Simulation results validating the proposed algorithm are given for various test cases. Further, the accuracy of estimation of RS code parameters using the proposed algorithm is also evaluated for various M-ary quadrature amplitude modulation schemes. From the simulation results, it is observed that the accuracy of estimation improves with a decrease in code dimension and modulation order and the proposed algorithm outperforms other algorithms in the prior works. | URI: | https://hdl.handle.net/10356/144740 | ISBN: | 978-1-5090-5935-5 | DOI: | 10.1109/VTCFall.2017.8287916 | Schools: | School of Computer Science and Engineering | Rights: | © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works. The published version is available at: https://doi.org/10.1109/VTCFall.2017.8287916 | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Conference Papers |
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