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Analysis and Modeling of Propagation in Tunnel at 3.7 and 28 GHz 被引量:1
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作者 Md Abdus Samad Dong-You Choi 《Computers, Materials & Continua》 SCIE EI 2022年第5期3127-3143,共17页
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
关键词 Path loss shadow factor telecommunications train tunnel wave propagation wireless networks
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Indoor Location Algorithm Based on the Measurement of the Received Signal Strength
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作者 NI Wei WANG Zong-xin 《Frontiers of Electrical and Electronic Engineering in China》 CSCD 2006年第1期48-52,共5页
The“distance-loss”model is amended by inserting a random distance-estimation variable.The estimation error is very small;thus,it does not change the log-normal distribution of the shadowing factor in the model.Then,... The“distance-loss”model is amended by inserting a random distance-estimation variable.The estimation error is very small;thus,it does not change the log-normal distribution of the shadowing factor in the model.Then,an iterative method is introduced to reduce the influence of shadowing,and the location estimation based on the received signal strength will be improved.Simulations show that this algorithm is effective. 展开更多
关键词 communication technology received signal strength “distance-loss”model maximum-likelihood estimation location algorithm shadowing factor
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