Please use this identifier to cite or link to this item:
https://hdl.handle.net/10356/81610
Title: | Classification of error correcting codes and estimation of interleaver parameters in a noisy transmission environment | Authors: | Swaminathan, Ramabadran Madhukumar, A. S. |
Keywords: | Adaptive modulation and coding Blind/semi-blind estimation |
Issue Date: | 2017 | Source: | Swaminathan, R., & Madhukumar, A. S. (2017). Classification of Error Correcting Codes and Estimation of Interleaver Parameters in a Noisy Transmission Environment. IEEE Transactions on Broadcasting, 63(3), 463-478. | Series/Report no.: | IEEE Transactions on Broadcasting | Abstract: | Channel encoder, which includes a forward error correcting (FEC) code followed by an interleaver, plays a vital role in improving the error performance of digital storage and communication systems. In most of the applications, the FEC code and interleaver parameters are known at the receiver to decode and de-interleave the information bits, respectively. But the blind/semi-blind estimation of code and interleaver parameters at the receiver will provide additional advantages in applications such as adaptive modulation and coding, cognitive radio, non-cooperative systems, etc. The algorithms for the blind estimation of code parameters at the receiver had previously been proposed and investigated for known FEC codes. In this paper, we propose algorithms for the joint recognition of the type of FEC codes and interleaver parameters without knowing any information about the channel encoder. The proposed algorithm classify the incoming data symbols among block coded, convolutional coded, and uncoded symbols. Further, we suggest analytical and histogram approaches for setting the threshold value to perform code classification and parameter estimation. It is observed from the simulation results that the code classification and interleaver parameter estimation are performed successfully over erroneous channel conditions. The proposed histogram approach is more robust against the analytical approach for noisy transmission environment and system latency is one of the important challenges for the histogram approach to achieve better performance. | URI: | https://hdl.handle.net/10356/81610 http://hdl.handle.net/10220/42741 |
ISSN: | 0018-9316 | DOI: | 10.1109/TBC.2017.2704436 | 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: [http://doi.org/10.1109/TBC.2017.2704436]. | Fulltext Permission: | open | Fulltext Availability: | With Fulltext |
Appears in Collections: | SCSE Journal Articles |
Files in This Item:
File | Description | Size | Format | |
---|---|---|---|---|
Classification of error correcting codes preprint.pdf | 290.46 kB | Adobe PDF | View/Open |
SCOPUSTM
Citations
10
60
Updated on Mar 22, 2024
Web of ScienceTM
Citations
10
42
Updated on Oct 25, 2023
Page view(s) 50
494
Updated on Mar 29, 2024
Download(s) 10
423
Updated on Mar 29, 2024
Google ScholarTM
Check
Altmetric
Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.