We propose and demonstrate a low complexity Reed Solomon-based low-density parity-check (RS-LDPC) code with adaptive puncturing decodingalgorithm for elastic optical transmission system. Partial received codes and th...
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We propose and demonstrate a low complexity Reed Solomon-based low-density parity-check (RS-LDPC) code with adaptive puncturing decodingalgorithm for elastic optical transmission system. Partial received codes and the relevant column in parity-check matrix can be punctured to reduce the calculation complexity by adaptive parity-check matrix during decoding process. The results show that the complexity of the proposed decodingalgorithm is reduced by 30% compared with the regular RS-LDPC system. The optimized code rate of the RS-LDPC code can be obtained after five times iteration. (C) 2016 The Authors. Published by Elsevier B.V.
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...
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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 decodingalgorithm 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.
This paper presents a new pre-processing approach for convolutional codes that can provide the adaptive capability to a standard Viterbi decoder. By identifying and generating the decoded data from the zero Hamming di...
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ISBN:
(纸本)9781424414833
This paper presents a new pre-processing approach for convolutional codes that can provide the adaptive capability to a standard Viterbi decoder. By identifying and generating the decoded data from the zero Hamming distance path, all computations in the Viterbi decoder can be avoided. This makes it possible to stop the Viterbi decoder in real time as long as no error occurs in the received code words;the Viterbi decoder is restarted to correct errors otherwise. With this approach, significant power, i.e. 97% of a standard Viterbi decoder power dissipation, can be saved when the Eb/No is as low as 13dB.
Linear programming (LP) decoding is getting more and more attention because of the maximum-likelihood (ML) certificate *** one of the improved LP decoding methods,multistage LP (MLP) decoding has been proposed to impr...
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Linear programming (LP) decoding is getting more and more attention because of the maximum-likelihood (ML) certificate *** one of the improved LP decoding methods,multistage LP (MLP) decoding has been proposed to improve the performance of LP decoding but at the cost of higher *** this paper,the problem of achieving a balance between the performance and the complexity of LP decoding is ***,a criterion used for searching new constraints adaptively is *** a modified MLP decoding is presented by incorporating the adaptive decoding algorithm to decrease the *** presented modified MLP decoding can obtain a good tradeoff between the performance and the complexity and is proved also has the ML certificate *** with moderate block length LDPC codes show that the proposed MLP decoding achieves the same BER performance as the original MLP decoding with far fewer used constraints and faster convergence speed consequently.
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