A physics-based statistical model for wave propagation through foliage

Accurate estimation of signal attenuation in highly scattering environments such as a forest medium has long been a challenging problem. The challenges arise from the fact that the incoherent power, which becomes dominant after some distance of wave propagation in the random medium, is difficult to model. In this paper, a statistical wave propagation model (SWAP) is developed for predicting the wave propagation path-loss in foliage. In this analysis, the forest is assumed to be statistically homogeneous along the direction of wave propagation, and the potentially large distance between the transmitter and receiver in the forest is divided into many statistically similar blocks of finite dimension. A fractal-based forest coherent scattering model (FCSM) is used as a foundation for predicting the characteristics of wave interaction with the foliage. By applying FCSM to a representative block of the forest, the statistical input-output field relationship including field attenuation and regeneration (due to scattering), is computed by a Monte Carlo simulation. These precomputed statistical quantities of the forest are then reused for all blocks using a network theory. The overall received power, and hence the path-loss, is estimated by following the coherent and incoherent power through all the forest blocks. Compared to a brute force approach, the computation time is significantly reduced while the prediction accuracy is maintained. Simulation results for path-loss as a function of propagation distance, frequency, and forest density are presented. The model is successfully validated by comparing its predictions against independent propagation measurements through foliage.