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5. Optimization of convolutional turbocodes
Convolutional turbocodes: the turbocode described in the original article achieves correction performance close to theoretical limits. However, as the noise level decreases, its efficiency diminishes. This leads to a so-called floor phenomenon (see figure 21 ): as the noise level falls, the residual error rate continues to decrease, but much more slowly. This behavior is due to two distinct factors. Firstly, for a correcting code to have good asymptotic performance, it...
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