Signal processing with alpha-stable distributions and applications
Signal processing with alpha-stable distributions and applications
Robust spatial filtering of coherent sources for wireless communications
Signal Processing
Robust auto-focusing wideband DOA estimation
Signal Processing
Robust adaptive beamforming in alpha-stable noise environments
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 05
DOA estimation based on the database retrieval technique with nonuniform quantization and clustering
Digital Signal Processing
Underwater sources location in non-Gaussian impulsive noise environments
Digital Signal Processing
IEEE Transactions on Signal Processing
A subspace-based direction finding algorithm using fractional lowerorder statistics
IEEE Transactions on Signal Processing
Measurements and models of radio frequency impulsive noise for indoor wireless communications
IEEE Journal on Selected Areas in Communications
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This paper addresses the array processing problems (mainly focuses on direction of arrival estimation and beamforming) of mobile communication system using linear antenna arrays in high impulsive noise environment. One possible way to simulate the impulsive noise is to introduce alpha-stable distribution as the noise model. In order to reduce the computational complexity, the problems of DOA and beamforming are approached as a nonlinear mapping which can be modeled using a suitable radial-basis function neural network (RBFNN) trained with input-output pairs. This paper discusses the application of a three-layer RBFNN to perform the DOA estimation and beamforming in presence of impulsive noise. The performance of the network is compared to that of the algorithms based fractional lower-order statistics. Simulations show that the RBFNN is appropriate to approach the DOA estimation and beamforming. At the same time, the RBFNN substantially reduces the computation complexity.