Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning
Erick Lamilla, Christian Sacarelo, Manuel S. Alvarez‐Alvarado, Arturo Pazmiño, Peter Iza
Abstract
Based on orbital angular momentum (OAM) properties of Laguerre–Gaussian beams LG(p,ℓ), a robust optical encoding model for efficient data transmission applications is designed. This paper presents an optical encoding model based on an intensity profile generated by a coherent superposition of two OAM-carrying Laguerre–Gaussian modes and a machine learning detection method. In the encoding process, the intensity profile for data encoding is generated based on the selection of p and ℓ indices, while the decoding process is performed using a support vector machine (SVM) algorithm. Two different decoding models based on an SVM algorithm are tested to verify the robustness of the optical encoding model, finding a BER =10−9 for 10.2 dB of signal-to-noise ratio in one of the SVM models.