Joint reconstruction of Reed-Solomon encoder and convolutional interleaver in a noisy environment
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...
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| Main Authors: | , , , |
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| Other Authors: | |
| Format: | Conference or Workshop Item |
| Language: | English |
| Published: |
2020
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| Subjects: | |
| Online Access: | https://hdl.handle.net/10356/144748 |
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| Institution: | Nanyang Technological University |
| Language: | English |
| Summary: | 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. |
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