errorcorrectingcodes are well known techniques for improving bit error rate (BER) performance in digital communication systems and are particularly important in wireless information networks to help establish reliab...
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This work proposes a new adaptive approach to the soft decision decoding of the so-called combined Chase-GMD class of algorithms (CGA). A reliability threshold is used to match the decoding performance to the channel ...
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This work proposes a new adaptive approach to the soft decision decoding of the so-called combined Chase-GMD class of algorithms (CGA). A reliability threshold is used to match the decoding performance to the channel conditions. As a result, a significant reduction in decoding complexity can be achieved by reducing the number of required algebraic decodings. The proposed adaptive application can achieve the upper performance limit of the CGA with significant complexity reduction.
We propose a novel soft-decision decoding algorithm for cyclic codes based on energy minimization principle. The well-known soft-decision decoding algorithms for block codes perform algebraic (hard-decision) decoding ...
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We propose a novel soft-decision decoding algorithm for cyclic codes based on energy minimization principle. The well-known soft-decision decoding algorithms for block codes perform algebraic (hard-decision) decoding several times in order to generate candidate codewords using the reliability of received symbols. In contrast, the proposed method defines energy as the Euclidean distance between the received signal and a codeword and alters the values of information symbols so as to decrease the energy in order to seek the codeword of minimum energy, which is the most likely codeword. We let initial positions be the information parts of signals obtained by cyclically shifting a received signal and look for the point, which represents a codeword, of minimum energy by moving each point from several initial positions. This paper presents and investigates reducing complexity of the soft-decision decoding algorithm. We rank initial positions in order of reliability and reduce the number of initial positions in decoding. Computer simulation results show that this method reduces decoding complexity.
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