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Lecture notes in computer science

Soft Distance Metric Decoding of Polar Codes

Mónica Liberatori, Leonardo J. Arnone, Jorge Castiñeira Moreira, Patrick Guy Farrell

Published Jan 1, 2015• 5 citations
Publisher
DOI
10.1007/978-3-319-27239-9_10

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A new soft-input,soft-output algorithm for decoding LDPC codes is described in this paper.Using soft squared Euclidean distance as the metric,the algorithm realizes decoding by iterating the antilog-sum of the Euclidean distance.A simplified algorithm is also put forward to reduce computational complexity.The proposed algorithm does not require knowledge of the signal-to-noise ratio of the received signal and is less complex to implement than other soft decision algorithms.The results of simulation show that the performance is very close to that of sum-product algorithm while the computational complexity is sharply reduced.
To deal with the complexity of traditional BP decoding algorithm,a kind of blind decoding algorithm for LDPC codes based on soft-input,soft-output is put forward in this paper.The algorithm uses soft squared Euclidean distance as the metric,realizes decoding by iterating the antilog-sum of the Euclidean distance as the process taken in BP algorithm.The proposed algorithm does not require knowledge of the signal-to-noise ratio of the received signal,and is less complex to implement than other soft decision algorithms.At the same time,a simplified algorithm is also put forward to reduce the computational complexity.What's more,the proposed SBSD decoding algorithm can not only decode Binary LDPC codes,but also can be used for Qary-LDPC codes.Simulations results show that the proposed algorithm can achieve good performance not only on the AWGN channels but also on Rayleigh channel,and the performance is very close to that of the sum-product algorithm,but the computational complexity is reduced sharply.