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Decoding of the (31, 16, 7) quadratic residue code with four-error correcting capability

机译:具有四错误纠正功能的(31、16、7)二次余数代码的解码

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A high-speed algorithm for decoding the binary (31, 16, 7) quadratic residue (QR) code up to four errors is proposed. Core to the key idea lies in an innovative integration of the reliability-search procedure and the insight of the weight distribution of the code for searching the candidate codewords. Accordingly, the maximum-likelihood (ML) criterion is applied to pick the most possible codeword. Through simulation over the additive white Gaussian noise (AWGN) channel, it is concluded that the error-correcting performance of the new decoder is superior to that of a Chase-II decoder when no more than four errors occur. The overall bit error rate (BER) of the proposed decoder is close to that of the Chase-II decoder. More importantly, the new decoder results in great reductions of 72.34% and 92.37% in the signal-to-noise ratio (SNR) values of 0 and 7, respectively. The proposed algorithm suggests an alternative to enhance the error-correcting capability of the hard-decision decoder, but with a lower decoding complexity.View full textDownload full textKeywordsquadratic residue codes, reliability, weight, soft-decision decodingRelated var addthis_config = { ui_cobrand: "Taylor & Francis Online", services_compact: "citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,more", pubid: "ra-4dff56cd6bb1830b" }; Add to shortlist Link Permalink http://dx.doi.org/10.1080/02533839.2011.577602
机译:提出了一种解码多达四个错误的二进制(31、16、7)二次余数(QR)码的高速算法。关键思想的核心在于可靠性搜索过程的创新集成,以及对用于搜索候选码字的代码权重分布的洞察力。因此,最大似然(ML)准则被应用于选择最可能的码字。通过对加性高斯白噪声(AWGN)通道进行仿真,可以得出结论,当发生的错误不超过四个时,新解码器的纠错性能要优于Chase-II解码器。所提出的解码器的总体误码率(BER)接近于Chase-II解码器的总体误码率。更重要的是,新的解码器可将信噪比(SNR)值分别为0和7分别大幅降低72.34%和92.37%。所提出的算法提出了一种增强硬判决解码器纠错能力的方法,但具有较低的解码复杂度。查看全文下载全文关键字二次残码,可靠性,权重,软判决解码相关var addthis_config = {ui_cobrand:“泰勒和弗朗西斯在线”,services_compact:“ citeulike,netvibes,twitter,technorati,delicious,linkedin,facebook,stumbleupon,digg,google,更多”,发布号:“ ra-4dff56cd6bb1830b”};添加到候选列表链接永久链接http://dx.doi.org/10.1080/02533839.2011.577602

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