Abstract
Abstract A coherently demodulated orbital angular momentum shift keying (OAM-SK) system over free-space turbulence channels using an image identifier based on convolutional neural network (CNN) as demodulator is proposed in this paper. Compared to the incoherent system, the proposed approach has the advantages of higher signal-to-ratio (SNR) of the detected image and fewer OAM topology charges employed for the same m-ary OAM-SK system. The CNN-based image identifier features in high recognition accuracy even under long free-space transmission and strong turbulence. In addition, the influence of the intensity of the local beam on the system performance, as well as the trade-off between the signal-to-noise ratio and the contrast of the received images, is fully investigated. Simulation results show that the demodulation accuracy of the proposed system with 16-ary OAM-SK system can be as high as > 99 % for 1500 m of free-space optical (FSO) transmission distance with strong atmospheric turbulence and appropriate intensity of local Gaussian beam.
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