Non-Gaussian Colored Noise Generation for Wireless Channel Simulation with Particle Swarm Optimizer

Dai, S., Li, M., Abbasi, Q. H. and Imran, M. (2020) Non-Gaussian Colored Noise Generation for Wireless Channel Simulation with Particle Swarm Optimizer. In: 2020 14th European Conference on Antennas and Propagation (EuCAP), Copenhagen, Denmark, 15-20 Mar 2020, ISBN 9788831299008 (doi:10.23919/EuCAP48036.2020.9135826)

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Abstract

Random Variable (RV) with different Probability Density Function (PDF) and Power Spectral Density (PSD) is a critical component for simulation of different wireless channel fading profile. To get a specific PSD for simulation of different multi-path scenario, the usual method is to pass a white noise through a filter with the required shape. But the filtering process will cause the change of random variable’s PDF unless the input noise follows Gaussian Distribution. In this paper, a Particle Swarm optimization (PSO) based method to generate NonGaussian noise by a pre-distortion filter and Inverse Transform Sampling (ITS) that meets both the requirement of PSD and PDF is described. As the solution is based on filtering, after the filter weight is found using PSO, the simulation could be carried out in a real-time manner compared to block-based methods. The numerical simulation confirms that it can generate the required PDF and more than 90% similar to the required PSD.

Item Type:Conference Proceedings
Status:Published
Refereed:Yes
Glasgow Author(s) Enlighten ID:Abbasi, Dr Qammer and Imran, Professor Muhammad and Dai, ShaoWei and Li, Dr David
Authors: Dai, S., Li, M., Abbasi, Q. H., and Imran, M.
College/School:College of Science and Engineering > School of Engineering > Systems Power and Energy
ISBN:9788831299008
Published Online:08 July 2020
Copyright Holders:Copyright © 2020 IEEE
First Published:First published in 2020 14th European Conference on Antennas and Propagation (EuCAP)
Publisher Policy:Reproduced in accordance with the publisher copyright policy

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