Neural Network-Based Channel Estimation and Detection in Spatial Modulation VLC Systems

Autor:	Kapila W. S. Palitharathna, Himal A. Suraweera, Roshan I. Godaliyadda, Vijitha R. Herath, John S. Thompson
Jazyk:	angličtina
Rok vydání:	2022
Předmět:	Modulation Azimuth spatial modulation user mobility light emitting diode (LED) Modeling and Simulation Visible light communication Channel estimation Electrical and Electronic Engineering legged locomotion Receivers artificial neural network Computer Science Applications
Zdroj:	Palitharathna, K, Suraweera, H A, Godaliyadda, R, Herath, V R & Thompson, J 2022, ' Neural Network-Based Channel Estimation and Detection in Spatial Modulation VLC Systems ', IEEE Communications Letters, vol. 26, no. 7, pp. 1598-1602 . https://doi.org/10.1109/LCOMM.2022.3166221
DOI:	10.1109/LCOMM.2022.3166221
Popis:	We consider a spatial modulation aided indoor visible light communication system with user mobility and random receiver orientation. Two artificial neural networks (ANNs) are proposed which are able to predict the channel state information (CSI) with high accuracy and resolution. These architectures use estimated CSI at pilot instances obtained using least square or minimum mean square error estimation and predict CSI at intermediate locations. Moreover in ANN 2, predicted user position information is used to improve the performance. Numerical results show that the proposed ANNs deliver a better bit error rate compared to a benchmark spline interpolation-based method. Further, ANN 2 is shown to perform robustly in a high mobility scenario.
Databáze:	OpenAIRE
Externí odkaz:	https://explore.openaire.eu/search/publication?articleId=doi_dedup___::952baaa5add99fa918fe641e28de10c2 https://www.pure.ed.ac.uk/ws/files/266283083/Final_Paper_Kapila.pdf Zobrazit plný text záznamu