A novel hard decision decoding scheme based on genetic algorithm and neural network |
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Authors: | Jianguo Yuan Changwei HeWenchun Gao Jinzhao LinYu Pang |
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Institution: | Key Lab of Optical Fiber Communications Technology, Chongqing University of Posts and Telecommunications, Chongqing 400065, China |
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Abstract: | A novel hard decision decoding scheme based on a hybrid intelligent algorithm combining genetic algorithm and neural network, named as genetic neural-network decoding (GND), is proposed. GND offsets the reliability loss caused by channel transmission error and hard decision quantization by making full use of the genetic algorithm's optimization capacity and neural network's pattern classification function to optimize the hard decision outputs of received matched filter and restore a more likelihood codeword as the input of hard decision decoder. As can be seen from the theoretical analysis and computer simulation, GND scheme is close to the traditional soft decision decoding in error correction performance, while its complexity, compared with the traditional soft decision decoding, is greatly reduced because its decoding process does not need to use the channel statistical information. |
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Keywords: | Genetic algorithm Neural network Hard decision decoding Complexity Error correction performance |
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