Name
Abstract | ||
|---|---|---|
Decoding of convolutional codes poses a significant challenge for coding
theory. Classical methods, based on e.g. Viterbi decoding, suffer from being
computationally expensive and are restricted therefore to codes of small
complexity. Based on analogies with model predictive optimal control, we
propose a new iterative method for convolutional decoding that is cheaper to
implement than established algorithms, while still offering significant error
correction capabilities. The algorithm is particularly well-suited for decoding
special types of convolutional codes, such as e.g. cyclic convolutional codes. |
Year | Venue | Keywords |
|---|---|---|
2009 | Clinical Orthopaedics and Related Research | viterbi decoder,iteration method,convolutional code,optimal control,error correction,information theory,coding theory |
Field | DocType | Volume |
Concatenated error correction code,Sequential decoding,Convolutional code,Computer science,Turbo code,Serial concatenated convolutional codes,Algorithm,Theoretical computer science,Viterbi decoder,Linear code,List decoding | Journal | abs/0909.0 |
Citations | PageRank | References |
0 | 0.34 | 2 |
Authors | ||
2 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| José Ignacio Iglesias Curto | 1 | 4 | 2.12 |
| Uwe Helmke | 2 | 337 | 42.53 |