Adaptive optical wireless communication systems with camera-based underwater turbulence and fog channel estimation

This paper presents an optical wireless communication system that uses camera-based channel estimation to enhance reliability. The proposed system utilizes the k-nearest neighbors (k-NN) algorithm to estimate the channel conditions in an underwater optical wireless communication (UOWC) channel. The proposed technique is evaluated using a lab-based OWC channel emulator. To achieve reliable OWC links under time-varying channel conditions, adaptive modulation is then implemented. The modulation type and order are adapted to the channel condition. The system also uses image processing techniques to estimate the intensity attenuation along the OWC channel and adaptively controls the transmit power accordingly. The results show that with this channel estimation approach, reliability is enhanced under time-varying channel conditions. Two sample channel impairments considered to demonstrate the efficacy of the proposed techniques are underwater turbulence and fog.