Measured data and empirical model jointly driven prediction for path loss of VHF and UHF communication in the South China Sea

Introduction High-precision radio wave propagation over maritime environments is of great importance for ensuring reliable maritime wireless communications. Methods To support the development of maritime transmission services, this work employs genetic algorithms to extract features from measured maritime data, thereby constructing a data-model-driven propagation model. The proposed model is established using measurement datasets collected in the South China Sea, covering the frequency range of 99 MHz to 1000 MHz over transmission distances up to 60 km. By integrating the strengths of both data-driven and model-driven approaches, a high-precision empirical model for maritime VHF and UHF propagation loss is developed. Specifically, we first analyze the propagation mechanisms of radio waves in the study region based on the measured data, and then combine them with the ITU-R P.2001 model to define a driving model with undetermined coefficients. These coefficients are subsequently determined using genetic algorithms through feature extraction from the measurement data. Finally, the proposed model is validated against the measurement dataset. Results Results demonstrate that the model achieves an average root-mean-square error of 2.13 dB, representing a 72.73% improvement compared with the ITU-R P.2001 model. Discussion The study of high-precision radio wave propagation over maritime environments is of great importance for ensuring reliable maritime wireless communications.