Intelligent beamforming by using a complex-valued neural network

Authors:
Andriyan Bayu Suksmono;Akira Hirose
Affiliations:
(Correspd. E-mail: suksmono@yahoo.com/ suksmono@ltrgm.ee.itb.ac.id) Department of Electrical Engineering, Institut Teknologi Bandung, Jl. Ganesha No. 10, Bandung 40132, Indonesia;Department of Electrical and Electronic Engineering, University of Tokyo 7-3-1 Hongo, Bunkyo-ku, Tokyo 113-8656, Japan
Venue:
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology - Engineering applications of Computational Intelligence
Year:
2004

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Abstract

This paper describes an intelligent beamforming (IBF) system based on complex-valued neural network (CVNN). A multilayer network structure with complex-valued neurons has been used. The system employs the complex-valued backpropagation algorithm (CVBPA) to intelligently adapt incoming signals impinging to sensors array. Performance of the CVNN-IBF system is compared with that of the conventional single-layer adaptive system using complex-valued least mean square (CLMS) algorithm. Experiments for multiple beam-pointing and multiple null-steering demonstrate that the CVNN-IBF outperforms the CLMS one in terms of convergence speed and interferences suppression levels.