Journal ArticleDOI
A new multilevel coding method using error-correcting codes
Hideki Imai,S. Hirakawa +1 more
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TLDR
A new multilevel coding method that uses several error-correcting codes that makes effective use of soft-decisions to improve the performance of decoding and is superior to other multileVEL coding systems.Abstract:
A new multilevel coding method that uses several error-correcting codes is proposed. The transmission symbols are constructed by combining symbols of codewords of these codes. Usually, these codes are binary error-correcting codes and have different error-correcting capabilities. For various channels, efficient systems can be obtained by choosing these codes appropriately. Encoding and decoding procedures for this method are relatively simple compared with those of other multilevel coding methods. In addition, this method makes effective use of soft-decisions to improve the performance of decoding. The decoding error probability is analyzed for multiphase modulation, and numerical comparisons to other multilevel coding systems are made. When equally complex systems are compared, the new system is superior to other multilevel coding systems.read more
Citations
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Bit-interleaved coded modulation revisited: A mismatched decoding perspective
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Channel Coding: The Road to Channel Capacity Fifty years of effort and invention have finally produced coding schemes that closely approach Shannon's channel capacity limit on memoryless communication channels.
TL;DR: The contributions that have led to the most significant improvements in performance versus complexity for practical applications are focused on, particularly on the additive white Gaussian noise channel.
Proceedings ArticleDOI
Multilevel coded 16-QAM modulation with multistage decoding and unequal error protection
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Multi-Dimensional Space-Time Multilevel Codes
TL;DR: A space-time multistage decoder is developed for the proposed ST-MLCs, which allows the complexity of soft decision decoding to be significantly reduced compared to a single level approach.
References
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TL;DR: This tutorial paper begins with an elementary presentation of the fundamental properties and structure of convolutional codes and proceeds with the development of the maximum likelihood decoder, which yields for arbitrary codes both the distance properties and upper bounds on the bit error probability.
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Short convolutional codes with maximal free distance for rates 1/2, 1/3, and 1/4 (Corresp.)
TL;DR: In this paper, the authors gave a tabulation of binary convolutional codes with maximum free distance for rates of 1/2, 1/3, and 1/4 for all constraint lengths up to and including nu = 14.
Journal ArticleDOI
Short binary convolutional codes with maximal free distance for rates 2/3 and 3/4 (Corresp.)
TL;DR: In this paper, a search procedure was developed to find good short binary (N,N - 1) convolutional codes using simple rules to discard from the complete ensemble of codes a large fraction whose free distance d{free} either cannot achieve the maximum value or is equal to d_{free} of some code in the remaining set.
Journal ArticleDOI
Correction of errors in multilevel Gray coded data
TL;DR: Certain classes of low-rate binary codes that have simple decoding algorithms can be used as underlying codes in the construction of high-rate easily decodable i -compressed codes, which have higher rates than binary codes of comparable length and number of correctable errors.