.png){kind=icon}
.png){kind=icon}
Return
Low-Complexity Decoding of Block Turbo Codes Based on the Chase Algorithm
.png){kind=icon}
PRE
AI
DOI：10.1109/LCOMM.2017.2650233.png)
.png){kind=icon}
Original request for help.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Block turbo codes (BTCs) are constructed by serially concatenating linear block codes and iteratively decoded by letting each component code be decoded in two stages. The Chase algorithm is employed in the first stage to make a list of candidate codewords by generating a fixed number of test sequences (TSs) and algebraically decoding them, regardless of the signal-to-noise ratio or the iteration number. In the second stage, the extrinsic information is generated for iterative decoding. In this letter, we propose a low-complexity decoding algorithm for BTCs. The proposed algorithm first checks whether an algebraic hard-decision decoder outputs a codeword for a given decoder input vector, and then adaptively applies one of the two estimation rules. Based on these two rules, the number of TSs in the proposed algorithm can be made monotonically decreasing with iterations. Numerical results demonstrate that the proposed algorithm has much lower computational complexity with a negligible performance loss, compared with the conventional decoding scheme based on the Chase algorithm.
Keywords:
Adaptive decoding algorithm
block turbo codes (BTCs)
Chase algorithm
decoding complexity
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.