Free-space 16-ary orbital angular momentum coded optical communication system based on chaotic interleaving and convolutional neural networks.

Abstract

Recently, orbital angular momentum (OAM) rays passing through free space have attracted the attention of researchers in the field of free-space optical communication systems. Throughout free space, the OAM states are subject to atmospheric turbulence (AT) distortion leading to crosstalk and power discrepancies between states. In this paper, a novel chaotic interleaver is used with low-density parity-check coded OAM-shift keying through an AT channel. Moreover, a convolutional neural network (CNN) is used as an adaptive demodulator to enhance the performance of the wireless optical communication system. The detection process with the conjugate light field method in the presence of chaotic interleaving has a better performance compared to that without chaotic interleaving for different values of propagation distance. Also, the viability of the proposed system is verified by conveying a digital image in the presence of distinctive turbulence conditions with different error correction codes. The impacts of turbulence strength, transmission distance, signal-to-noise ratio (SNR), and CNN parameters and hyperparameters are investigated and taken into consideration. The proposed CNN is chosen with the optimal parameter and hyperparameter values that yield the highest accuracy, utmost mean average precision (MAP), and the largest value of area under curve (AUC) for the different optimizers. The simulation results affirm that the proposed system can achieve better peak SNR values and lower mean square error values in the presence of different AT conditions. By computing accuracy, MAP, and AUC of the proposed system, we realize that the stochastic gradient descent with momentum and the adaptive moment estimation optimizers have better performance compared to the root mean square propagation optimizer.