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Proceedings Paper

Reducing interferences in wireless communication systems by mobile agents with recurrent neural networks-based adaptive channel equalization
Author(s): Francesco Beritelli; Giacomo Capizzi; Grazia Lo Sciuto; Christian Napoli; Emiliano Tramontana; Marcin Woźniak
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Paper Abstract

Solving channel equalization problem in communication systems is based on adaptive filtering algorithms. Today, Mobile Agents (MAs) with Recurrent Neural Networks (RNNs) can be also adopted for effective interference reduction in modern wireless communication systems (WCSs). In this paper MAs with RNNs are proposed as novel computing algorithms for reducing interferences in WCSs performing an adaptive channel equalization. The method to provide it is so called MAs-RNNs. We perform the implementation of this new paradigm for interferences reduction. Simulations results and evaluations demonstrates the effectiveness of this approach and as better transmission performance in wireless communication network can be achieved by using the MAs-RNNs based adaptive filtering algorithm.

Paper Details

Date Published: 11 September 2015
PDF: 9 pages
Proc. SPIE 9662, Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2015, 96621U (11 September 2015); doi: 10.1117/12.2197587
Show Author Affiliations
Francesco Beritelli, Univ. of Catania (Italy)
Giacomo Capizzi, Univ. of Catania (Italy)
Grazia Lo Sciuto, Roma Tre Univ. (Italy)
Christian Napoli, Univ. of Catania (Italy)
Emiliano Tramontana, Univ. of Catania (Italy)
Marcin Woźniak, Silesian Univ. of Technology (Poland)


Published in SPIE Proceedings Vol. 9662:
Photonics Applications in Astronomy, Communications, Industry, and High-Energy Physics Experiments 2015
Ryszard S. Romaniuk, Editor(s)

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