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Title: Estimation of Random Channel Gain for SISOVisible Light Communications System
Authors: Yaseen, Maysa
Canbilen, Ayse E.
Ikki, Salama
Keywords: Bayesian Cramer-Rao lower bound (BCRLB)
channel estimation
least square (LS)
linear minimum mean square error (LMMSE)
maximum likelihood (ML)
maximum posteriori probability (MAP)
visible light communication (VLC)
Issue Date: 2023
Publisher: Ieee Canada
Abstract: In this article, the estimation of random channel gain is studied for a single-input single-output (SISO) visible light communication (VLC) system. Five different estimators, namely maximum likelihood (ML), least square (LS), maximum posteriori probability (MAP), linear minimum mean square error (LMMSE), and minimum mean square error (MMSE), are proposed. The performances of these estimators are compared with the derived Bayesian Cramer-Rao lower bound (BCRLB), which can be used as a benchmark to evaluate the efficiency of the unbiased estimators. The presented analytical results, corroborated with Monte Carlo simulations, indicate that the MMSE estimator provides the best results. Additionally, the increasing number of pilot symbols as well as the ascending transmitted power improve the system performance. On the other hand, the noise variance has a negative effect on the channel estimation in terms of mean square error (MSE), and thus, it can dramatically reduce the performance of the estimators.
Description: Article; Early Access
ISSN: 2694-1783
Appears in Collections:Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collections
WoS İndeksli Yayınlar Koleksiyonu / WoS Indexed Publications Collections

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