Enhanced demodulation of perfect optical vortices shift keying in LDPC-coded FSO communication via conformal vision transformer

We propose a conformal vision transformer (CViT)-based demodulation for the perfect optical vortices shift keying (POV-SK) signal in the low-density parity check (LDPC) coded free-space optical (FSO) link. Despite the growing interest in POV for FSO links, atmospheric turbulence (AT) induces phase distortions, resulting in POV-SK demodulation errors and degrading POV-SK FSO communication performance. The CViT demodulator utilizes conformal mapping to reshape the circular POV-SK patterns into rectangles, enabling more efficient feature learning. Paired with ViT's comprehensive global feature extraction capabilities, the CViT demodulator effectively counters turbulence and boosts accuracy in identifying the POV-SK modes. In this study, the CViT POV-SK demodulation method is thoroughly described. The extensive numerical simulations compare CViT, ViT, Conformal ResNet18, and the lightweight RCDT-based 'shallow' CNN in terms of recognition accuracy, PSNR, and bit error rate (BER). Under severe turbulence (<i>C</i> <i>n</i>2=4.4×10^-12 <i>m</i> ^-2/3), conformal mapping can improve the recognition accuracy of ViT from 0.7636 to 0.8437 (CViT), while reducing the BER from 3.6 × 10^-2 to 1.1 × 10^-3. Under the premise of keeping recognition accuracy and BER the same, CViT significantly reduces the number of model parameters and time consumption compared to Conformal ResNet18, which is essential for meeting the system's future real-time demands. In addition, in moderate turbulence, the performance of the RCDT-based CNN is acceptable, but it significantly lags behind CViT in severe turbulence, with the BER being an order of magnitude higher than that of CViT.