Min Zhang

TL;DR: An intelligent constellation diagram analyzer is proposed to implement both modulation format recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using convolution neural network (CNN)-based deep learning technique, and the effects of multiple factors on CNN performance are comprehensively investigated.

TL;DR: An intelligent eye-diagram analyzer is proposed to implement both modulation format recognition (MFR) and optical signal-to-noise rate (OSNR) estimation by using a convolution neural network (CNN)-based deep learning technique.

TL;DR: In this article, a single RGB LED-based OCC system utilizing a combination of undersampled phase-shift on-off keying (UPSOOK), wavelength-division multiplexing (WDM), and multiple-input-multiple-output (MIMO) techniques is designed, which offers higher space efficiency (3 bits/Hz/LED), long-distance, and nonflickering VLC data transmission.

TL;DR: Experimental results showed that the average prediction accuracy of the proposed DES-SVM method was 95% when predicting the optical equipment failure state, which means that the method can forecast an equipment failure risk with high accuracy.

TL;DR: A novel joint atmospheric turbulence (AT) detection and adaptive demodulation technique based on convolutional neural network (CNN) are proposed for the OAM-based free-space optical (FSO) communication, which has the potential to be embedded in charge-coupled device (CCD) cameras deployed at the receiver to improve the reliability and flexibility for theOAM-FSO communication.