1. Shashika Biyanwila Research Engineer
Cellular Positioning
Shashika Biyanwila Research Engineer

2. Outline What is Cellular Positioning Positioning Parameters
Feasible Approaches Identified
Implementation
Some Trial Results
Future Approach of the Research
Cellular Positioning

3. What is cellular positioning ?
Determining the position of a Mobile Station (MS), using location sensitive parameters
Why ????
To provide Location Based Services…
Cellular Positioning

4. Applications of cellular positioning
Operator services
Billing
Network management
Location based services
Wireless Gaming
Assistance
Roadside assistance
Personal or vehicle emergency
Alarm management
Driving Directions
Tracking
Tracking criminals
Tracking external resources containers etc
Monitoring
Monitoring delivery process
Fleet & freight tracking
Personal Child Security
Mobile Worker management
Information
Traffic
Nearest service
news
navigation help
advertising
Information Directory
Cellular Positioning

5. Positioning Parameters
Cell-ID
Received Signal Strength Intensity (RSSI)
Timing Advance (TA)
Uplink Time (Difference) Of Arrival (TDOA)
Downlink Observed Time Differences (E-OTD)
Angle of Arrival (AOA)
Cellular Positioning

6. Feasible Approaches Identified
Cellular Positioning

7. 1. Geometrical Approach Based on distance measurements Two Steps:
- Distance calculation
- Location Estimation
Cellular Positioning

8. Geometrical approach contd..
Distance Calculation
- Measure the RSSI from neighboring cells
- Apply Propagation models to calculate the distance
Propagation Models
- Hata Model
- Extended Hata Model
- Lee’s Model
- CCIR Model
- Walfisch-Ikegami Model (for micro cells)
Cellular Positioning

9. 2. Statistical Approach
Construct a statistical propagation model for the RSSI
Find RSSI at distance d from the transmitter
Offsite calibration is necessary to estimate the propagation parameters
Define a probability distribution for the RSSI
Location estimation problem is solved as an inverse or, rather, inference problem
Cellular Positioning

10. Statistical Approach contd..
Log-loss or Log-distance model
Gaussian Probability Distribution
Propagation Parameter Estimation
- Maximum Likelihood estimation
Location Estimation
- Maximum A posteriori Probability
Cellular Positioning

11. Statistical Approach cntd..
Area being considered is divided into several squares
A posterior probability of the location be within a square, is calculated for each square
Square with
Maximum A posterior
Probability
Cellular Positioning

12. 3. Database correlation Method (DCM)
Involves a database of reference fingerprints for the whole area of interest.
Fingerprint – a recorded measurement sample from a certain location in the area
GPS coordinates of a location
RSSI (from available cells) in that location
Cellular Positioning

13. How to collect fingerprints? By measurements
DCM contd…
How to collect fingerprints?
By measurements
Using a Network planning tool
High sampling resolution is needed.
Measurement
Fingerprint
Test route
Cellular Positioning

14. Compare the input measurement with reference fingerprints
DCM contd…
Location estimation
Input
Measurement
DCM Algorithm
Database
Estimated
Location
Compare the input measurement with reference fingerprints
- Using Cost Functions
Location of the best matching reference fingerprint
Estimated Location
Cellular Positioning

15. Implementation Interfacing Program Database
RSS
Measurement Unit
RSSI + GPS Reading
Commands
Interfacing Program
Database
Location Estimation Algorithm
Display Program
Software environment
Location ?
Hardware Environment
Cellular Positioning

16. Trial & Results Urban - Wellawaththa to Kolpetty Suburban
- Katubedda to Piliyandala
Rural
- Ibbagamuwa
Cellular Positioning

17. Urban area…..
Cellular Positioning

18. Suburban area ……….
Cellular Positioning

19. Rural area ……..
Cellular Positioning

20. Future Approach of the Research
Improvements to the current DCM approach
Drawbacks
- Few instances of poor estimations
- Creating, updating & maintenance of the database
How To Overcome
- Refined estimation techniques
- Use of a Network planning tool to create fingerprints
Cellular Positioning

21. Implementation of a positioning engine and associated services
Get your own location
Track others – web-based location on a map
GSM Network
Estimated Location
Received Signal Fingerprint
Location Estimation using Received Signal Fingerprint & database
System Information
Calibration Fingerprints
Digital Maps
Positioning Engine
Cellular Positioning

22. Thank You