In present-day society,train tunnels are extensively used as a means of transportation.Therefore,to ensure safety,streamlined train operations,and uninterrupted internet access inside train tunnels,reliable wave propa...In present-day society,train tunnels are extensively used as a means of transportation.Therefore,to ensure safety,streamlined train operations,and uninterrupted internet access inside train tunnels,reliable wave propagation modeling is required.We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea.The measured path loss and the received signal strength were modeled with the Close-In(CI),Floating intercept(FI),CI model with a frequency-weighted path loss exponent(CIF),and alpha-beta-gamma(ABG)models,where the model parameters were determined using minimum mean square error(MMSE)methods.The measured and the CI,FI,CIF,and ABG modelderived path loss was plotted in graphs,and the model closest to the measured path loss was identified through investigation.Based on the measured results,it was observed that every model had a comparatively lower(n<2)path loss exponent(PLE)inside the tunnel.We also determined the path loss component’s possible deviation(shadow factor)through a Gaussian distribution considering zero mean and standard deviation calculations of random error variables.The FI model outperformed all the examined models as it yielded a path loss closer to the measured datasets,as well as a minimum standard deviation of the shadow factor.展开更多
文摘In present-day society,train tunnels are extensively used as a means of transportation.Therefore,to ensure safety,streamlined train operations,and uninterrupted internet access inside train tunnels,reliable wave propagation modeling is required.We have experimented and measured wave propagation models in a 1674 m long straight train tunnel in South Korea.The measured path loss and the received signal strength were modeled with the Close-In(CI),Floating intercept(FI),CI model with a frequency-weighted path loss exponent(CIF),and alpha-beta-gamma(ABG)models,where the model parameters were determined using minimum mean square error(MMSE)methods.The measured and the CI,FI,CIF,and ABG modelderived path loss was plotted in graphs,and the model closest to the measured path loss was identified through investigation.Based on the measured results,it was observed that every model had a comparatively lower(n<2)path loss exponent(PLE)inside the tunnel.We also determined the path loss component’s possible deviation(shadow factor)through a Gaussian distribution considering zero mean and standard deviation calculations of random error variables.The FI model outperformed all the examined models as it yielded a path loss closer to the measured datasets,as well as a minimum standard deviation of the shadow factor.
