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Dimensionality Reduction and Improving the Performance of Automatic Modulation Classification Using Genetic Programming
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نویسنده
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Latif A. ,Hessampour K.
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منبع
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International Journal Of Engineering - 2014 - دوره : 27 - شماره : 5 - صفحه:709 -714
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چکیده
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This paper shows how we can make advantage of using genetic programming in selection of suitable features for automatic modulation recognition. automatic modulation recognition is one of the essential components of modern receivers. in this regard, selection of suitable features may significantly affect the performance of the process. simulations were conducted with 5db and 10db snrs. test and training data released from real ones were recorded in an actual communication system. for performance analyzing of the proposed method, a set of experiments were conducted considering signals with 2psk, 4psk, 2fsk, 4fsk, 16qam and 64 qam modulations. the results show that the selected features by the model improve the performance of automatic modulation recognition substantially. during our experiments, we also reached the suitable values and forms for mutation and crossover ratio, fitness function as well as other parameters for the proposed model.
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کلیدواژه
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Decision Tree; Entropy; Genetic Programming; Modulation Automatic Detection; Multi-Layer Neural Network Perceptron
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آدرس
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Yazd University, ایران, Yazd University, ایران
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Authors
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