Variational Sparse Bayesian Learning for Estimation of Gaussian Mixture Distributed Wireless Channels
In this paper, variational sparse Bayesian learning is utilized to estimate the multipath parameters for wireless channels. Due to its flexibility to fit any probability density function (PDF), the Gaussian mixture model (GMM) is introduced to represent the complicated fading phenomena in various co...
Main Authors: | Lingjin Kong, Xiaoying Zhang, Haitao Zhao, Jibo Wei |
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Format: | Article |
Language: | English |
Published: |
MDPI AG
2021-09-01
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Series: | Entropy |
Subjects: | |
Online Access: | https://www.mdpi.com/1099-4300/23/10/1268 |
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