| Summary: | 碩士 === 國立交通大學 === 網路工程研究所 === 105 === Nowadays, mobile networks play important roles in our daily live. For the design of next generation telecom networks (5G), it is critical to analyze the behaviors of mobile users. Mobile data are so privacy and precious, so telecom operators/carriers do not want to share it. Therefore, it is hard to get mobile data of users from the operators. To solve the problem, we propose a crowdsensing based platform named Crowd Measurement (CM), which is built to collect data from mobile users voluntarily around the world. The data collected is stored in database anonymously and is open to public for everyone who is interested in getting it. In this thesis, we propose an algorithm to classify data in Taiwan High Speed Rail. We demonstrate the results by drawing signal map and cell residence time distribution in different operators. We also demonstrate the figures of signal strengths, handover, and network utilization from collected data.
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