Title

Adaptive interference cancellation in circular arrays with radial basis function neural networks

Abstract

A new neural network based approach to the problem of adaptive interference nulling using circular arrays is presented. In modern cellular, satellite mobile communications systems and in GPS systems, both desired and interfering signals change their directions continuously. This paper develops a fast tracking system to constantly track the users, and then adapt the radiation pattern of the antenna to direct multiple narrow beams to desired users and nulls to sources of interference. In the approach suggested here, the computation of the optimum weights is viewed as a mapping problem which can be modeled using a three-layer Radial Basis Function Neural Networks (RBFNN) 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 tracking mobile users as they move across the antenna's field of view.

Publication Date

1-1-1998

Publication Title

IEEE Antennas and Propagation Society International Symposium, 1998 Digest - Antennas: Gateways to the Global Network - Held in conjunction with: USNC/URSI National Radio Science Meeting

Volume

1

Number of Pages

203-206

Document Type

Article; Proceedings Paper

Personal Identifier

scopus

DOI Link

https://doi.org/10.1109/APS.1998.699109

Socpus ID

0031631921 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/0031631921

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