Name
Title | ||
|---|---|---|
Efficient source decoding over memoryless noisy channels using higher order Markov models |
Abstract | ||
|---|---|---|
Exploiting the residual redundancy in a source coder output stream during the decoding process has been proven to be a bandwidth-efficient way to combat noisy channel degradations. This redundancy can be employed to either assist the channel decoder for improved performance or design better source decoders. In this work, a family of solutions for the asymptotically optimum minimum mean-squared error (MMSE) reconstruction of a source over memoryless noisy channels is presented when the redundancy in the source encoder output stream is exploited in the form of a γ-order Markov model (γ≥1) and a delay of δ,δ0, is allowed in the decoding process. It is demonstrated that the proposed solutions provide a wealth of tradeoffs between computational complexity and the memory requirements. A simplified MMSE decoder which is optimized to minimize the computational complexity is also presented. Considering the same problem setup, several other maximum a posteriori probability (MAP) symbol and sequence decoders are presented as well. Numerical results are presented which demonstrate the efficiency of the proposed algorithms. |
Year | DOI | Venue |
|---|---|---|
2004 | 10.1109/TIT.2004.833337 | IEEE Transactions on Information Theory |
Keywords | Field | DocType |
efficient source,memoryless noisy channel,higher order markov model,source coder output stream,noisy channel degradation,channel decoder,source encoder output stream,mmse decoder,residual redundancy,decoding process,computational complexity,better source decoder,minimum mean square error,higher order,indexing terms,markov processes,markov model,decoding | Discrete mathematics,Markov process,Markov model,Computer science,Communication channel,Minimum mean square error,Algorithm,Speech recognition,Redundancy (engineering),Decoding methods,Maximum a posteriori estimation,Computational complexity theory | Journal |
Volume | Issue | ISSN |
50 | 9 | 0018-9448 |
Citations | PageRank | References |
7 | 0.47 | 34 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lahouti, F. | 1 | 133 | 11.22 |
| A. K. Khandani | 2 | 297 | 19.65 |