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

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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 coverage Area 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.
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33--47
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Bibliogr. 14 poz., tab., wykr.
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Bibliografia
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  • [7] Laiho, J.,Wacker, A., Novosad, T.: Radio network planning and optimization for UMTS, JohnWiley & Sons Ltd, 2006.
  • [8] Lee, W. H., Tseng, S. S., Wang, C. H.: Design and Implementation of Electronic Toll Collection System Based on Vehicle Positioning System Techniques, Elsevier Computer and Communications, 31(12), 2008, 2725.
  • [9] Liu, H. Y., Wang, C. H., Shieh, W. S., Jeng, B. S.: An intelligent taxi dispatching management system, In Proceedings of the Cross Strait Conference on ITS, 2005.
  • [10] Megerian, S., Koushanfar, F., Potkonjak, M., Srivastava, M. B.: Worst and Best-Case Coverage in Sensor Networks, IEEE Trans. on Mobile Computing, 4(1), 2005, 84.
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  • [12] Tsai, C. F., Tsai, C. W., Wu, H. C., Yang, T.: ACODFGa novel data clustering approach for data mining in large database, ACM - Journal of Systems and Software, 73(1), 2004, 133.
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  • [14] Wang, C. W., Chiu, C. C.: A Geocoding Application on GIS Using Address Data: Case Study of Taiwan Address Database, In Proceedings of the TGIS Annual Conference, 2003
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS8-0010-0003
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