کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
381341 1437500 2008 13 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Soft output decision convolutional (SONNA) decoders based on the application of neural networks
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
پیش نمایش صفحه اول مقاله
Soft output decision convolutional (SONNA) decoders based on the application of neural networks
چکیده انگلیسی

The paper investigates principles of work and BER characteristics of a new soft decision algorithm for decoding convolutional codes that is based on neural network applications. The novelty of the algorithm is in its capability to generate soft output estimates of the message bits encoded. For this purpose the noise energy function, which is defined and used for the neural network decoding of convolutional codes, has been related to the well known log-likelihood function and the soft decision decoding rule has been defined and derived. The BER curves are obtained for this novel algorithm and then compared to the curve obtained by the Viterbi algorithm and the gradient descent algorithm. Based on the theoretical model a simulator of coding communication system has been developed and used to confirm theoretically expected results. It was found that the performances of the proposed soft decision decoder are comparable or better than the performances of the recurrent neural network decoder and decoders based on the Viterbi algorithm.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Engineering Applications of Artificial Intelligence - Volume 21, Issue 1, February 2008, Pages 1–13
نویسندگان
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