Final Year Project LYU0301

1. Final Year ProjectLYU0301 Using GSM Cell Information on Mobile Phone Mok Ming Fai CEG mfmok1@cse Lee Kwok Chau CEG leekc1@cse

2. Agenda • Symbian OS • Location-based services (LBS) • Connectivity of GSM base stations and mobile phones • Using GSM cell information • Example application: MTRTravaller • Future Work

3. Symbian and Symbian OS • Symbian: • a software licensing company owned by Ericsson, Nokia, Panasonic, Psion, Samsung Electronics Siemens and Sony Ericsson. • Symbian OS: • standard operating system for data-enabled mobile devices

4. Symbian OS • Currently supported mobile phones • Nokia 6600, 7650, 3650, N-Gage and 9210 Communicator • Sony Ericsson P800, P900 • Motorola A920 • Fujitsu F2051, F2102V • New mobile phones supporting Symbian OS • Samsung SGH-D700 • Siemens SX1 • Sendo X • BenQ P30

5. Characteristics of Symbian OS • Integrated multimode mobile telephony • Open application environment • Open standards and interoperability • Multi-tasking • Fully object-oriented and component based • Flexible user interface design

6. Special Features in Symbian OS • Error Handling • Cleanup Stack • Two-phase Constructions • Active Object • implements multi-tasking without using multithread • One active scheduler per thread cooperating with one or mor active objects • Non-preemptive, no mutual exclusion codes are needed

7. Programs Written for Symbian OS • Robot Hello World • Illustrations of the use of GUI components and basic APIs • Nokia Square • Illustrations of the basic APIs and the structure of Symbian-based applications

8. Location-Based Services (LBS) • Services are provided based on user’s current location. • Applicable on different fields: • Driving • Billing • Shopping Guides • Security • Games and Entertainment • ...... • Each of them requires different accuracy and latency.

9. Current Technologies on LBS • 1) Global Positioning System (GPS) • Good Accuracy: 30-100m • Poor indoor and urban-area capabilities • Generally high power consumption • Expensive hardware • 2) 3rd Generation GSM (3G) • Need time to replace current mobile network • 3) Modified SIM Card • Cooperation with telco • 4) Global System for Mobile Communications (GSM) • Common regular mobile phone network standard • Available on ordinary cell phones

10. Operation of Mobile Phone Connectivity Location: [50] Cell ID: [2] Location: [50] Cell ID: [4] Location: [50] Cell ID: [3] Location: [50] Cell ID: [1]

11. Using GSM Cell Information • Main idea: each base station may somehow indicate certain ‘information’ about location or region • Cell information includes: • Location ID • Cell ID • Received Signal Strength

12. AT+CREG? Location: [50] Cell ID: [7474] +CREG: <n>,<stat>[,50,7474] Traditional Cell Information Collection Methods • 1) Communicating with GSM modem • Using AT command • Require different kinds of hardware

13. Traditional Cell Information Collection Methods • 2) Phone engineering mode • Tell you a list of cell information • Need to record them manually

14. Getting Cell Information via Symbian API • Problem: • Current Nokia SDK doesn’t provide any method for retrieving GSM cell information • The internal library of the phone actually contains such API • Solution: • Use header file from other Symbian SDK • GSMStatus • Integrate current cell information and application

15. Cell Information for LBS Accuracy depends on: • Base station deployment • Cell size • Pico-cell: 10-1000m • Micro-cell: 100-1000m • Small Macro-cell: 1000-3000m • Large Macro-cell: 3000-30km • Not accurate enough telling where you are • How can we make use of such information?

16. Problem of Pure Cell ID Detection Location: [50] Cell ID: [2] • Different registered cell in a particular location each time Location: [50] Cell ID: [4] Location: [50] Cell ID: [3] Location: [50] Cell ID: [1]

17. Pure Cell Detection VS Cell Change Event • Event of Entering / Leaving a boundary • Provide transition Information (from 1 cell to another)

18. Cell IDs in the 2D Space • Initiatives • To locate the approximate location of a mobile phone uses with a program run on Symbian OS • Determining GSM cells coverage and their distribution • Plot a cell ID-to-location map • Locate current position of a mobile device

19. Cell ID Data Collection • Collected location ID and cell ID pairs for two telcos in the CU campus. • Data Collection method: • Static Method for SmarTone • Cell Change Method for Peoples

20. Principle of the two data collection methods • Static Method • Wait for a sufficiently long period of time at a specific point in the 2D map to see the strength and stability of a cell strength. • Determine the location ID and cell ID of that specific location after observing for a period of time

21. Principle of the two data collection methods • Cell Change Method • Walk around the campus and find the “boundaries” of different cells • When cell change occurs we note down the change and try to find out the boundaries of the cells

22. Advantages and Disadvantages of the Two Methods • Static Method: • Accurate at those specific point • Experiment only done on a set of specific points selected from the 2D map • Takes a longer time • Cannot figure out the cell boundary clearly unless those sample points are dense enough

23. Advantages and Disadvantages of the Two Methods • Cell Change Method: • Most of the cell boundaries can be detected • Can discover different overlapping of cells • Use less time • Boundaries detected are “regions” instead of sharp lines

24. Expectations • We expected: • GSM Cells are of similar size • Only small overlapped region at the cell boundaries • No large cell completely covering a smaller cell • Can be modeled as hexagonal shape covering the area.

25. Experimental Result For Peoples

26. Experimental Result

27. Experimental Result For SmarTone

28. Experimental Result

29. Inconsistencies with Our Expectations • Cells vary greatly in size and shape • Large scale of cell overlap • Some marco-cell encapsulating smaller micro-cells • Cells may change shapes under different environment condition at different time • Cells in CU are too large to get an accurate location of the mobile device

30. Conclusion on the Experiment • Potential difficulties in 2D Space • ID-to-location map drawn not accurate enough • Cannot locate the location of a mobile device to an acceptable accuracy owing to the large size of cells • Hierarchy of cells make it even harder to locate your current position

31. The Idea of Cell IDs in 1D Space • Owing to the difficulties and inaccuracy of the detection of cell ID in 2-dimensional space, we turn to the 1-dimensional space • Only travel in one direction • Concentrate on the Entrance of a region • Limitation in 1D space helps to ease the inaccuracy.

32. Cell IDs in 1D Space Location: [50] Cell ID: [2] Location: [50] Cell ID: [4] Location: [50] Cell ID: [3] Location: [50] Cell ID: [1] Cell ID: [1->2] Cell ID: [2->3]

33. MTRTraveller for Stations in Subway • Apply to traffic route • MTRTraveller - tell user the station arrival • Initial Observation: • Between two stations in subway, there is exactly one change • This event can tell user that you are going from one station to another station • Due to the shape of antenna in these stations Cell ID Changes Here Station 1 Station 2

34. Station Cells: [S1, O], [S1, B], [S1, P] Station Cells: [S1, O], [S1, B] MTRTraveller for Stations in Open Area • KCR Stations in open area • Many cell IDs in between two stations • A station platform may also involve multiple cells • Transition pair => in between S1 and S2 • Station cell => in the station platform Station 2 Station 1 Transition Pairs: [S1, S2, O], [S1, S2, B], [S1, S2, P], [S1, S2, G]

35. MTR Cell ID Data • Peoples

36. KCR Cell ID Data • Peoples

37. MTR Cell ID Data • SmarTone

38. KCR Cell ID Data • SmarTone

39. MTR Cell ID Data • Sunday

40. Statistics • Time of ‘station arrival’ event occurrence before entering that station • Should be enough for user to figure out the change Entering station in open area

41. Demonstration • Map data, station data, transition data • Movie in actual stations • Simulation

42. Potential Problems All cell data depends on cell deployment • Cannot control time to tell user the event of station arrival • Problem occurred if two or more stations share the same cell ID • Up-to-date cell information required • Developers - collect data regularly • Automatic cell information collection kit • Users - update their data regularly • Convenient update using SMS / GPRS

43. More to Improve… • Personalize • Informative • Fancy user interface • Distributed intelligence

44. Other Possible Applications • Bus route • All bus stops are in open area • Tram route for tourism • Just tell tourists that they are in a particular district (e.g. Causeway Bay, Wan Chai)

45. Other Possible Applications • Detection of car speed detectors • Make use of inaccuracy of GSM cell • More data have to be stored Oh, there is speed detector! I am caught!

46. Future Work • Automatic cell information collection kit • Improvement on MTRTraveller • Personalization • User Interface • Informative • Distributed intelligence • Generic middleware/library for developers • Other applications

47. Conclusion • Symbian OS for mobile phones • GSM provides location-related information • Using GSM cell information in Symbian program • Not accurate enough for positioning • Easily available for ordinary mobile phones • Pure cell ID detection VS cell ID change event • Design special applications mastering these information • MTRTraveller • Other applications

48. End of Presentation • Thank you very much!