Enhancement of Optical Wireless Discrete Multitone Channel Capacity Based on Li-Fi Using Sparse Coded Mask Modeling

A sparse coded mask modeling technique is proposed to increase the transmission capacity of an optical wireless link based on Li-Fi. The learning model for the discrete multitone (DMT) signal waveform is implemented using the proposed technique, which is designed based on a masked auto-encoder. The entire length of the DMT signal waveform, encoded using quadrature phase shift keying (QPSK) or 16-quadrature amplitude modulation (16-QAM) symbols, is divided into equal intervals to generate DMT patches, which are subsequently compressed based on the specified masking ratio. After 1-m optical wireless transmission, the DMT signal waveform is reconstructed from the received DMT patch through a decoding process and then QPSK or 16-QAM symbols are recovered. Using the proposed technique, we demonstrate that we can increase the transmission capacity by up to 1.85 times for a 10 MHz physical bandwidth. Additionally, we verify that the proposed technique is feasible in Li-Fi networks with illumination environments above 240 lux.