Expand this Topic clickable element to expand a topic
Skip to content
Optica Publishing Group

Experimental performance of deep learning channel estimation for an X-ray communication-based OFDM-PWM system

Not Accessible

Your library or personal account may give you access

Abstract

A deep learning channel estimation scheme in orthogonal frequency division multiplexing for X-ray communication (XCOM) is studied. The scheme uses simulated and detected data obtained with different working parameters and numbers of pilots as training and testing data, respectively, for the deep neural network (DNN) model. The bit-error-rate performance of the DNN model under various system operating parameters, numbers of pilot sequences, and channel obstructions is investigated separately. Experiment results showed that the deep-learning-based approach can address the distortion of the air-scintillator channel for XCOM, giving a performance comparable to those of least-squares and minimum-mean-square error estimation methods.

© 2022 Optical Society of America

Full Article  |  PDF Article
More Like This
Experimental evaluation of an OFDM-PWM-based X-ray communication system

Wenxuan Chen, Yunpeng Liu, Xiaobin Tang, Junxu Mu, and Sheng Lai
Opt. Express 29(3) 3596-3608 (2021)

Wireless ultraviolet scattering channel estimation method based on deep learning

Taifei Zhao, Xinzhe Lv, Haijun Zhang, and Shuang Zhang
Opt. Express 29(24) 39633-39647 (2021)

Prediction of metasurface spectral response based on a deep neural network

Ying Chen, Zhixin Ding, JianKun Wang, Jian Zhou, and Min Zhang
Opt. Lett. 47(19) 5092-5095 (2022)

Data availability

Data underlying the results presented in this Letter are not publicly available at this time but may be obtained from the authors upon reasonable request.

Cited By

You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Figures (5)

You do not have subscription access to this journal. Figure files are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Equations (3)

You do not have subscription access to this journal. Equations are available to subscribers only. You may subscribe either as an Optica member, or as an authorized user of your institution.

Contact your librarian or system administrator
or
Login to access Optica Member Subscription

Select as filters


Select Topics Cancel
© Copyright 2024 | Optica Publishing Group. All Rights Reserved