Abstract
Practical decoders that take advantage of the source redundancy without requiring prior knowledge of the source statistics are designed. Discrete universal denoiser (DUDE)-enhanced decoders including, hard-denoising and decoding, soft-denoising and decoding, and iterative denoising and decoding, are considered. The results indicate that these decoders can provide substantial reductions in bit-error rates over conventional decoders that ignore redundancy in the source. The results involving Markov sources and repeat accumulate (RA) codes show that the proposed DUDE-enhanced belief propagation (BP) decoders closely track the performance of various source distribution dependent BP decoder structures.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 165 |
| Number of pages | 1 |
| Journal | IEEE International Symposium on Information Theory - Proceedings |
| State | Published - 2004 |
| Event | Proceedings - 2004 IEEE International Symposium on Information Theory - Chicago, IL, United States Duration: Jun 27 2004 → Jul 2 2004 |
All Science Journal Classification (ASJC) codes
- Theoretical Computer Science
- Information Systems
- Modeling and Simulation
- Applied Mathematics
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