# Research Progress on Modulation Format Recognition Technology for Visible Light Communication
## 4 Deep Learning-Based Modulation Recognition Methods
### Introduction to the VLC MFR Datasets
The study focused on four modulation formats: BPSK, QPSK, 8 PSK, and 16 QAM. Within the SNR range of 0-20 dB, 100 time-frequency diagrams were generated for each SNR condition at intervals of 2 dB. This resulted in a total of 4400 frames, with 3520 used for training and 880 for testing. In paper [32], [PERSON] et al. generated signals for eight VLC modulation formats using MATLAB. These formats included QPSK, 8-PSK, 16-PSK, 4-QAM, 8-QAM, 16-QAM, 32-QAM, and 64-QAM. A 3D CAD model was constructed using OpticStudio (see [[https://www.ansys.com/products/optics/ansys-zemax-opticstudio](https://www.ansys.com/products/optics/ansys-zemax-opticstudio)]([https://www.ansys.com/products/optics/ansys-zemax-opticstudio](https://www.ansys.com/products/optics/ansys-zemax-opticstudio)) accessed on 12 May 2025), incorporating a path loss model based on non-sequential ray tracing to simulate a real V-VLC scenario. Three weather conditions were considered: clear, rainy, and foggy. AWGN intensity was adjusted to simulate SNR conditions ranging from 5 to 25 dB. The received signal constellation diagrams were saved in JPEG format at 656 \(\times\) 656 pixels. Features were extracted through grayscale conversion, Canny edge detection, and Hough transformation. The final dataset contained over 32,000 Hough-transformed image samples for training and testing three deep neural network models that had been pre-trained on ImageNet. In paper [33], [PERSON] et al. built a real UVLC system to collect the dataset. This dataset covered 10 modulation formats, including 2/4/8/16/32/64-QAM and 8/16/32/64-APSK. The signals were processed through upsampling, pulse-shaping filtering, and amplification by an arbitrary waveform generator and an electrical amplifier. They were then emitted by a laser diode with a peak-to-peak voltage ranging from 0.1 V to 0.55 V. The voltage range of 0.2 V to 0.4 V corresponded to the high-SNR region, 0.1 V to the low-SNR region, and above \begin{table}
\begin{tabular}{c c c c c c c} \hline \hline
**Reference** & **System Platform** &
\begin{tabular}{c} **Channel** \\ **Conditions** \\ \end{tabular} & **Modulation Types** & **Sample Format** & **Dataset Size** & **Parameter Range** \\ \hline [PERSON] et al. & & & A 4-km FSO link & 8 classes & Fan-beam & \\
[28] & Optisystem & with an attenuation & (2/4/8/16 PSK, & constellation & Unclear & 5:5:30 dB (OSNR) \\  & & of 0.43 dB/km & 8/16/32/64 QAM & diagram & & \\ \hline [PERSON] et al. & & & & & & \\
[29] & MATLAB & & Gamma–gamma & 4 classes (OOK, & \\
[29] & MATLAB & atmospheric & BPSK, QPSK, & \\ channel, AWGN & & 16 QAM) & sequence & & \\ \hline [PERSON] et al. & & & AWGN, Doppler & 4 classes (BPSK, & \\
[31] & MATLAB & & MPK, Rician & 4 classes (BPSK, & \\  & & multipath fading, & & 16 QAM) & Time-frequency & \\  & & clock offset & & & \\ \hline [PERSON] et al. & & & Simulation of a & & \\
[32] & MATLAB B2020b & & realistic traffic & 8 classes (QPSK, & \\  & & multi-vehicle VLC & 8/16 PSK, & \\  & & path loss model & 4/8/16/32/64 QAM) & & \\ \hline [PERSON] et al. & & Real UVLC & & Real UVLC channel & 10 classes & \\
[33] & experimental system & with adjustable LED & (2/4/8/16/32/64 QAM, & \\  & & driving voltage & 8/16/32/64/APSK & \\ \hline  & & & UOWC channel & 15 classes & \\
[34] & MATLAB B2018b & & incorporating & & \\  & & scattering, & (4/8/16/32/64/128/256 & Constellation & \\  & & absorption, and & & QAM, 2/4/8 ASK, & \\  & & turbulence effects & & & \\ \hline \hline \end{tabular}
\end{table} 
Table 3: Typical self-built datasets for MFR in VLC systems. 0.5 V to the nonlinear region. The signals were transmitted through a 1.2-m water tank. The received signals were processed and converted into complex data, which were then coordinate-transformed and combined into 4D feature data to form the dataset. The length of each frame and the total size of the dataset were not specified. In paper [34], [PERSON] et al. simulated a UOWC system using MATLAB.