A Low-Complexity Maximum-Likelihood Decoder for Tail-Biting Convolutional Codes
| Autor: | Yunghsiang S. Han, Po-Ning Chen, Pramod K. Varshney, Ting-Yi Wu |
|---|---|
| Rok vydání: | 2018 |
| Předmět: |
Computer science
020302 automobile design & engineering 020207 software engineering Data_CODINGANDINFORMATIONTHEORY 02 engineering and technology Viterbi algorithm symbols.namesake 0203 mechanical engineering Transmission (telecommunications) Search algorithm Convolutional code 0202 electrical engineering electronic engineering information engineering Code (cryptography) symbols Electrical and Electronic Engineering Algorithm Decoding methods Computer Science::Information Theory Block (data storage) |
| Zdroj: | IEEE Transactions on Communications. 66:1859-1870 |
| ISSN: | 0090-6778 |
| Popis: | Due to the growing interest in applying tail-biting convolutional coding techniques in real-time communication systems, fast decoding of tail-biting convolutional codes has become an important research direction. In this paper, a new maximum-likelihood decoder for tail-biting convolutional codes is proposed. It is named bidirectional priority-first search algorithm (BiPFSA) because priority-first search algorithm has been used both in forward and backward directions during decoding. Simulations involving the antipodal transmission of (2, 1, 6) and (2, 1, 12) tail-biting convolutional codes over additive white Gaussian noise channels shows that BiPFSA not only has the least average decoding complexity among the state-of-the-art decoding algorithms for tail-biting convolutional codes but can also provide a highly stable decoding complexity with respect to growing information length and code constraint length. More strikingly, at high SNR, its average decoding complexity can even approach the ideal benchmark complexity, obtained under a perfect noise-free scenario by any sequential-type decoding. This demonstrates the superiority of BiPFSA in terms of decoding efficiency. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|