Signal Strength Monitoring And Propagation Model Calibration For Cellular Network In Road Environment

With the rapid growth of mobile data traffic and vehicles in urban traffic environments,the demand for vehicle users to access the Internet is increasing.At present,the cellular network is one of the main communication technology used by vehicles.However,its coverage does not fully satisfy the communication requirements of vehicles,by constructing accurate received signal strength(RSS)distribution map and propagation model for cellular network,it can ensure the full coverage of network signals and provide important reference for the layout of roadside units for VANET.Therefore,it has received extensive attention from academia and enterprises.However,the current research on the construction of cellular network signal distribution maps and its propagation model mostly stays in the level of theory and smallscale simple-environment experiments,the analysis under the real road environment still needs further exploration.Therefore,this thesis takes the main roads in the Campus of Shanghai Jiaotong University and its surrounding roads(including the typical interference factors such as viaducts,vehicles and buildings)as the research area,realizes the detection of RSS and the construction of RSS distribution map.Finally,the propagation model of different scenarios(congestion,smooth road conditions,etc.)was corrected.The specific research contents are as follows:Firstly,a signal strength acquisition platform based on NI PXI equipment is constructed to realize network spectrum signal acquisition in each frequency band of 2G,3G,4G networks,and the spectrum is converted to accurate network signal strength values through signal processing.After that,the main roads on the campus of Shanghai Jiaotong University and its surrounding areas are used as the test environment.The signal collection plan covering early peaks and normal time periods is designed and implemented,and a highprecision road RSS distribution map is constructed.The measured data are used to analyze the influence of time and space for RSS distribution in the road environment.Secondly,considering that the PXI platform can't meet the demand of signal strength collection in a large area and its huge amount of data,the RSS acquisition application based on Android terminal is designed to effectively reduce the acquisition cost.Due to the difference among the signal strengths collected by different terminals,a signal strength estimation algorithm based on multi-source data fusion is designed.PXI data is used to evaluate its accuracy and propose correction and optimization methods,which greatly improves the accuracy of the estimation results.In addition,based on the Bayesian learning mechanism,the dynamic update rule of the RSS distribution map is designed to ensure the real-time display of the map.Finally,based on the RSS distribution map,three typical road scenarios are selected to calibrated the signal propagation models of LTE networks.The influence of different interference factors during signal propagation is analyzed.Quantitative index parameters of the influence of various factors such as buildings and vehicles on the RSS received by the collection terminal in the actual road environment are calculated.In addition,the accuracy and versatility of the calibration model are verified based on similar scenarios.The above research realizes the signal strength acquisition,the RSS distribution map construction and the propagation model calibration of the cellular network in the urban road environment.An accurate RSS distribution map and the general model parameters are obtained,which can ensure the full coverage of network signals and provide important reference for the layout of roadside units for VANET,laying the foundation for V2 I communication based on cellular network.