Performance of Underwater Visible Light Communication for Subsea IoT Networks

Abstract

The Internet of Underwater Things (IoUT) is emerging as a key enabling technology for subsea monitoring, offshore oil and gas operations, and autonomous underwater systems. However, underwater wireless communication remains challenging due to severe attenuation, scattering, and environmental variability. Among available technologies, underwater visible light communication (UVLC) offers high data rates and low latency suitable for real-time monitoring applications. This paper investigates the performance of UVLC systems under different underwater channel conditions. Two channel models (i.e., Beer–Lambert and Double Exponential models) are considered to evaluate channel gain and signal-to-noise ratio (SNR) performance across multiple water types, including pure sea, clear ocean, coastal ocean, and turbid harbor environments. Furthermore, bit-error-ratio (BER) performance are analyzed for on-off keying (OOK) modulation. Simulation results demonstrate that water turbidity significantly impacts channel attenuation and communication reliability. The Double Exponential model predicts more severe degradation than the Beer–Lambert model, indicating the importance of realistic channel modeling. The findings provide useful insights for the design of reliable UVLC-enabled Subsea IoT networks.