Discovering the Radio Signal Coverage Hole and Weak Coverage Area in Mobile Network by Spatiotemporal Data Mining on Location-Based Services

Authors:
Wei-Hsun Lee;Shian-Shyong Tseng;Ching-Hung Wang;Shen-Lung Tung
Affiliations:
Dept. of Computer Science, National Chiao Tung University, Telecommunication Lab, Chunghwa Telecom Co., Ltd., Taiwan. E-mail: leews@cht.com.tw;Dept. of Computer Science, National Chiao Tung University, Dept. of Information Science and Applications, Asia University, Taiwan. E-mail: sstseng@asia.edu.tw;Telecommunication Lab, Chunghwa Telecom Co., Ltd., Taiwan. E-mail: amidofu@cht.com.tw;Dept. of Electrical Engineering, National Central University, Taiwan. E-mail: tung168@cht.com.tw
Venue:
Fundamenta Informaticae - Intelligent Data Analysis in Granular Computing
Year:
2010

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Abstract

Locating the radio signal coverage hole (SCH) and signal weak coverage area (SWCA) in the mobile network and taking appropriate actions to improve network quality are the major tasks for mobile network operators (MNO). A novel approach, Signal Coverage Hole and weak coverageArea DIscovering Model (SCHADIM), is proposed based on spatiotemporal data mining on the raw data collecting from location based service (LBS) to achieve this goal. It reuses the communication raw data in LBS-based applications and transforms it into mobile network communication quality monitoring information by integrating the GIS (geographical information system), road network database and mobile network base station database. By this way, the vehicles in the LBS-based applications can be regarded as the mobile network signal probing vehicles, which provides plentiful information for discovering the SCH/SWCA. Comparing to the traditionalmobile network signal probing vehicle method, which is known as radio site verification (RSV) method, the proposed SCHADIM has the spatiotemporal coverage as well as cost advantages. A mobile network monitoring system, cellular network quality safeguard (CQS), has been implemented based on the proposed model which combines with the domain expert heuristics to provide decision support information for optimizing the mobile network.