Optical Encoding Model Based on Orbital Angular Momentum Powered by Machine Learning - Erick Lamilla; Christian Sacarelo; Manuel S. Alvarez-Alvarado; Arturo Pazmino; Peter Iza (Sensors, 2023)
Based on orbital angular momentum (OAM) properties of Laguerre–Gaussian beams LG(<semantics>p,ℓ</semantics>), 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 <semantics>=10−9</semantics> for <semantics>10.2</semantics> dB of signal-to-noise ratio in one of the SVM models.