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Maximum likelihood DE coding of convolutional codes using viterbi algorithm with improved error correction capability

机译:使用维特比算法的卷积码最大似然DE编码,具有改进的纠错能力

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Convolutional codes are applied in applications that require good performance with low implementation cost. It is a finite state machine, processing information bits in a series manner. Viterbi algorithm [1] can be applied to a host of problems encountered in digital communication systems. The Viterbi algorithm cannot detect any error but can sometimes correct it, while calculating one survivor path with minimum metric value. The maximum likelihood decoding of convolutional encoder with Viterbi algorithm is a good forward error correction [3] method suitable for single and double bit error correction by means of finding the code branch in the code trellis that was most likely to transmit. The modified decoding process proposed in this paper, we shall use a different approach to derive the exact bit, double bit, burst error and a symbol error correction process. It will detect and correct the errors by means of connecting and comparing the metric values at the present, previous and next states of the Viterbi decoding. also it is offering 30–36% better than the Viterbi and 99.9% of error correction, but the computational complexity is decreases and time are increases about 20–40%
机译:卷积码应用于要求高性能和低实施成本的应用中。这是一个有限状态机,以串行方式处理信息位。 Viterbi算法[1]可以应用于数字通信系统中遇到的许多问题。维特比算法无法检测到任何错误,但有时可以纠正错误,同时以最小度量值计算一条幸存者路径。用维特比算法对卷积编码器进行最大似然解码,是一种很好的前向纠错方法[3],适用于通过查找最有可能发送的代码网格中的代码分支来进行单比特和双比特纠错的方法。本文提出的修改后的解码过程,我们将使用不同的方法来得出精确的位,双位,突发错误和符号错误校正过程。它将通过连接和比较Viterbi解码的当前,先前和下一个状态的度量值来检测和纠正错误。它的性能也比维特比(Viterbi)好30–36%,纠错率达99.9%,但是计算复杂度却在降低,时间却在增加20–40%

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