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Entropy 2011, 13(1), 64-81; doi:10.3390/e13010064

A Pattern Construction Scheme for Neural Network-Based Cognitive Communication

Faculty of Electricity and Electronics, Istanbul Technical University (iTü), 34469 Istanbul, Turkey
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Received: 1 December 2010 / Revised: 21 December 2010 / Accepted: 22 December 2010 / Published: 7 January 2011
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Abstract

Inefficient utilization of the frequency spectrum due to conventional regulatory limitations and physical performance limiting factors, mainly the Signal to Noise Ratio (SNR), are prominent restrictions in digital wireless communication. Pattern Based Communication System (PBCS) is an adaptive and perceptual communication method based on a Cognitive Radio (CR) approach. It intends an SNR oriented cognition mechanism in the physical layer for improvement of Link Spectral Efficiency (LSE). The key to this system is construction of optimal communication signals, which consist of encoded data in different pattern forms (waveforms) depending on spectral availabilities. The signals distorted in the communication medium are recovered according to the pre-trained pattern glossary by the perceptual receiver. In this study, we have shown that it is possible to improve the bandwidth efficiency when largely uncorrelated signal patterns are chosen in order to form a glossary that represents symbols for different length data groups and the information can be recovered by the Artificial Neural Network (ANN) in the receiver site.
Keywords: cognitive radio; pattern recognition; spectrum management; noise immunity; neural network cognitive radio; pattern recognition; spectrum management; noise immunity; neural network
This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

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Ustundag, B.; Orcay, O. A Pattern Construction Scheme for Neural Network-Based Cognitive Communication. Entropy 2011, 13, 64-81.

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