A neural-network-based linearly constrained minimum variance beamformer

    Authors

    A. H. El Zooghby; C. G. Christodoulou;M. Georgiopoulos

    Comments

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    Abbreviated Journal Title

    Microw. Opt. Technol. Lett.

    Keywords

    adaptive array antennas; adaptive beamforming; neural networks; wireless; communications; interference cancellation; ANTENNA-ARRAYS; ADAPTIVE ARRAY; PERFORMANCE; Engineering, Electrical & Electronic; Optics

    Abstract

    This paper presents a neural network approach for beam-forming and interference cancellation. A three-layer radial basis function neural network is trained with input-output pairs. The results obtained from this network are in excellent agreement with the Wiener solution. It was found that networks implementing these functions are successful in hacking mobile users in real time as they move across the antenna's field of view (C) 1999 John Wiley & Sons, Inc.

    Journal Title

    Microwave and Optical Technology Letters

    Volume

    21

    Issue/Number

    6

    Publication Date

    1-1-1999

    Document Type

    Article

    Language

    English

    First Page

    451

    Last Page

    455

    WOS Identifier

    WOS:000080627500015

    ISSN

    0895-2477

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