Title: The influence of Gaussian kernel width on indoor and outdoor radio channels identification from binary output measurements

Authors: Rachid Fateh; Anouar Darif; Said Safi

Addresses: Laboratory of Innovation in Mathematics, Applications and Information Technologies, Department of Mathematics and Informatics, Polydisciplinary Faculty, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal, 23000, Morocco ' Laboratory of Innovation in Mathematics, Applications and Information Technologies, Department of Mathematics and Informatics, Polydisciplinary Faculty, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal, 23000, Morocco ' Laboratory of Innovation in Mathematics, Applications and Information Technologies, Department of Mathematics and Informatics, Polydisciplinary Faculty, Sultan Moulay Slimane University, P.O. Box 592, Beni Mellal, 23000, Morocco

Abstract: With the rapid evolution of digital communication systems and channels identification; there is a significant interest in the finite impulse response (FIR) filter theory, which has strong potential practical applications in various fields such as process control, signal processing, audio, and Hilbert transformers. In this paper, we are focused on the finite impulse response identification problem for single-input single-output nonlinear systems, whose outputs are detected by binary value sensors. In one hand, we have used the kernel recursive least squares (KRLS), and recursive least square (RLS) algorithms to identifying the practical frequency selective fading channels, called broadband radio access network (BRAN), standardised by the European Telecommunications Standards Institute (ETSI). In the other hand, the impact of Gaussian kernel width on the BRAN channels impulse responses identification and the mean square error (MSE) is also investigated. Monte Carlo simulation results in noisy environment and for various kernel sizes are presented to improve for what kernel size we obtain the optimal results.

Keywords: channel identification; indoor radio; outdoor radio; Gaussian kernel width; nonlinear system; kernel recursive least squares; KRLS.

DOI: 10.1504/IJICT.2023.134853

International Journal of Information and Communication Technology, 2023 Vol.23 No.4, pp.327 - 345

Received: 31 May 2021
Accepted: 09 Oct 2021
Published online: 14 Nov 2023 *

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