Name
Abstract | ||
|---|---|---|
Excellent performance of turbo codes approximating to the Shannon limit should be conditioned on a large codeword length which inherently requires very long trellis. There have been a number of parallel decoding algorithms in order to accelerate the decoding speed. In these algorithms, the long trellis was partitioned into a number of shorter sub-trellises so that the the parallel search along the partitioned the sub-trellises can be performed. This trellis partition usually show performance degradation. In this paper, we propose an efficient parallel decoding algorithm for double binary turbo codes. The simulation results investigated in this paper reveal that the proposed scheme speed up the decoding time almost 4 times compared to the conventional full trellis searching method with negligible performance degradation, for various code rates and codeword lengths. |
Year | DOI | Venue |
|---|---|---|
2012 | 10.1109/APCC.2012.6388261 | APCC |
Keywords | Field | DocType |
binary codes,maximum likelihood decoding,search problems,turbo codes,map decoding,code rates,codeword lengths,double binary turbo codes,full trellis searching method,parallel decoding algorithms,parallel search,decoding time,duo-binary turbo codes,iterative decoding,parallelization | Concatenated error correction code,BCJR algorithm,Convolutional code,Sequential decoding,Computer science,Parallel computing,Serial concatenated convolutional codes,Turbo code,Real-time computing,Linear code,List decoding | Conference |
ISSN | ISBN | Citations |
2163-0771 | 978-1-4673-4727-3 | 0 |
PageRank | References | Authors |
0.34 | 6 | 6 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Meixiang Zhang | 1 | 22 | 8.57 |
| Sooyoung Kim | 2 | 225 | 38.24 |
| Jongsu Lee | 3 | 78 | 7.18 |
| sangseob song | 4 | 0 | 0.34 |
| wonyong kim | 5 | 6 | 1.60 |
| yonghoon cho | 6 | 0 | 1.01 |