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A Method for Reducing the Complexity of Meggitt Decoder

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Communications, Signal Processing, and Systems (CSPS 2017)

Part of the book series: Lecture Notes in Electrical Engineering ((LNEE,volume 463))

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Abstract

The decoding principle of linear block code is based on the syndrome which determines the error location of the received codeword. When considering the Hamming code, there will be eight syndromes with eight decoding circuits when there is one bit error. Cyclic code is a special case of linear block codes which is still a cyclic code after cyclic shift. Therefore, it is possible to get another error pattern of the cyclic code after the cyclic shift of one error pattern. Meggitt decoder can take advantage of the cyclic shift characteristic to divide any error pattern and all the corresponding cyclic shift error patterns into one category. And the same type of error patterns can use the same decoding circuit which can simplify the complexity of the decoder. If the (n, k) cyclic code is to correct t bits error, it is easy to derivation the total number of the error patterns. But there exists error patterns that can be classified as one type. The total number of error pattern types will be discussed in this paper. And the computation complexity of error pattern types of Meggitt decoder will be reduced when using the method proposed in this paper.

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References

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Acknowledgments

This work was supported by the Fundamental Research Funds for the Center Universities (Grant No. HIT.MKSTISP.2016 13).

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Correspondence to Jiayan Zhang or Shuai Wang .

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Zhang, J., Wang, S., Lu, H., An, H. (2019). A Method for Reducing the Complexity of Meggitt Decoder. In: Liang, Q., Mu, J., Jia, M., Wang, W., Feng, X., Zhang, B. (eds) Communications, Signal Processing, and Systems. CSPS 2017. Lecture Notes in Electrical Engineering, vol 463. Springer, Singapore. https://doi.org/10.1007/978-981-10-6571-2_174

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  • DOI: https://doi.org/10.1007/978-981-10-6571-2_174

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-6570-5

  • Online ISBN: 978-981-10-6571-2

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