Random walk prediction-based channel model for underground-mining visible-light communication network

Abstract

A random walk prediction (RWP)-based channel model is founded in the underground-mining (UM) visible-light communication (VLC) network. Among the factors that influence the communication performance of the UM-VLC network, the most significant ones are the arbitrary positioning and orientation of optical transmitters and receivers, tunnels with irregular walls, shadowing by machinery or miners, and scattering from dust clouds. This analysis allows for the development of a more realistic RWP-based channel model. These factors are integrated into a single-channel model that facilitates the derivation of complex expressions. The parameters are the received power of the RWP-based channel model, channel impulse response, root mean square delay spread, signal-to-noise-ratio, and bit error rate. The simulation results show that the RWP-based channel model meets the practical requirements better than other models in the reference papers.