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Accuracy Characterization of Cell Tower Localization

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Presentation on theme: "Accuracy Characterization of Cell Tower Localization"— Presentation transcript:

1 Accuracy Characterization of Cell Tower Localization

2 Cellular network Directional antenna

3 Cell Tower Localization

4 How to get location of Cell Tower?
Cell tower location is not available publically Estimated tower locations are used which are obtained through war-driving Wardriving is the act of searching for cellular/Wi-Fi wireless networks by a person in a moving vehicle, using a laptop or smartphone. Wardriving : (cell location, RSSI, tower ID) Two algorithms are employed usually: Strongest RSS Weighted Centroid

5 Strongest RSS The location of the strongest RSS in a trace is the estimated tower location Works when the tower is close to the road where the data is collected

6 Weighted Centroid Estimated location is the geometric center of the points where it’s signal was observed. Signal strength is taken as the weight. Estimation is sensitive to density and homogeneity of measurements around the cell.

7 Data Description We obtained access to a wardriving trace that covers three areas in the greater Los Angeles area. Wardriving : (cell location, RSSI, tower ID) The Downtown trace covers an area of 3.5km×4.2km in the downtown Los Angeles. The Residential trace covers an area of 6.3km×17km in the southern part of the Los Angeles County. The Rural trace covers an area of 35.4km×36km in the Victor Valley of San Bernardino County.

8 Data Description The wardriving trace was collected over a period of 2 months in February and March of 2009. The GSM signal strength measurements and their locations were recorded every 2 seconds and the speed of the car averaged about 32kmph---wardriving In total, we have 2,613,465 received signal strength (RSS) readings from 105,271 unique locations, resulting, on average, in 24.8 RSS readings from different cells per location. Each cell tower has 2, 3 or 6 cells attached to it, depending on the characteristics of the area and the coverage requirements. We know which cells belong to which cell tower and the actual location of each cell tower.

9 Localization Error Comparison

10 Strongest RSS to Distance Relation
Outside cell towers are the cause for large localization errors for the Strongest RSS algorithm Most of them have the strongest RSSs lower than -60dBm

11 Techniques to Improve Localization Accuracy
RSS Thresholding Boundary Filtering Tower Based Regrouping

12 RSS Thresholding Filter out all cells having strongest RSS less than a threshold. Authors use -60dBm as the threshold.

13 Boundary Filtering Outside cells will have strongest RSS on the boundary/perimeter of the war- driving area. These are thus excluded. Inside cell Inside cell A A Wardriving Wardriving B B Outside cell Outside cell Signal from tower A is strongest here (within cell A) Not exclude cell A—Cell A is an inside cell Signal from tower B is strongest here (at boundary only) Exclude cell B as outside cell

14 Tower-based Regrouping
Cells belonging to same tower have can be identified using the following techniques: Clustering cells geographically. Prefix of a cell ID up to the last digit is the same for all cells belonging to the same cell tower. (Observed from collected data) Accept: If most of the inside cells pass the previous two techniques Reject: Otherwise

15 Area-wise Analysis

16 Cell Combining Optimization
Merging wardriving traces of cells that share a common cell tower into a single trace and estimating the position of the cell tower itself improves localization results significantly.

17 Improvement After Cell Combination

18 Improvement After Cell Combination
Strongest RSS always performs better than Weighted Centroid before cell combination. Localization results after the cell combining significantly outperform those before the cell combining. There is a trade-off between RSS quality and RSS quantity.


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