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Field strength prediction of mobile communication network based on GIS
Authors:Xiaoyong CHEN  Hualing WU  Tran Minh TRI
Institution:1. Faculty of Geomatics, East China Institute of Technology , 56 Xuefu Road, Fuzhou , 344000 , China chenxy@ecit.cn;3. Faculty of Geomatics, East China Institute of Technology , 56 Xuefu Road, Fuzhou , 344000 , China;4. School of Engineering and Technology, Asian Institute of Technology , Bangkok , Thailand
Abstract:This article describes GIS-based models successfully developed for predicting the coverage of Cityphone cellular network, visualizing the predicted signal strength, and analyzing the field strength coverage. In order to predict the signal coverage strength of communication network more accurately, the spatial and nonspatial databases of a mobile cellular network are combined by GIS and produce the necessary parameters. A GIS model named COST-231-Walfisch–Ikegami model (WIM) is developed for signal coverage prediction in Ho Chi Minh City. Radio-line-of-sight and nonradio-line-of-sight conditions can be determined by this model. In addition, in case of nonradio-line-of-sight conditions, average building height, building separation, building width, incident radio path, and road orientation with respect to the direct radio path were obtained using GIS. Road orientation loss, multiscreen diffraction loss, and shadowing gain were predicted more accurate by this model. The scale of maps in the experiment was 1:2000 and the average of floor height was 3?m because there were no exact building height measurements. Statistical results show that the path loss predicted by the COST 231 WIM overcame the real path loss of each cell station. And this method can be used for signal coverage prediction of mobile cellular network in urban areas. Compared to the current situation with the Ho Chi Minh City Posts and Telecommunications system, this model can be effectively applied to improve the Cityphone mobile network quality as well as capability. Developed GIS models can help designers in predicting cell station coverage using real spatial maps that make the results more reliable. This research can help network operators improve the network quality and capability with the best investment efficiently.
Keywords:mobile communication network  GIS model  field strength prediction
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