1. Siting Mobile Phone Base Stations a GRASS application on location selection
WANG, Wen-Chieh (Jeffrey)
HSU, Chien-Liang
Chaoyang University of Technology

2. GRASS: Siting Mobile Phone Base Stations
Outline
Introduction
Basic Concepts
Implementation
Verification
Conclusion
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GRASS: Siting Mobile Phone Base Stations

3. GRASS: Siting Mobile Phone Base Stations
1. Introduction
1.1 Background
1.2 Objectives
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GRASS: Siting Mobile Phone Base Stations

4. GRASS: Siting Mobile Phone Base Stations
1.1 Background
Quality of service vs. health concerns
Siting mobile phone base stations is often a fierce issue in Taiwan, because:
Densely populated urbanized areas occupied by high-rise buildings
The NIMBY-ism and unfair compensation
Intense competition, secrecy, and under the counter deals
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GRASS: Siting Mobile Phone Base Stations

5. GRASS: Siting Mobile Phone Base Stations
1.2 Objectives
Create a freely available solution to foster the knowledge dissemination and open discussion of siting mobile phone base stations.
Serve as an experiment to learn and test GRASS’s LOS and other raster processing capabilities
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GRASS: Siting Mobile Phone Base Stations

6. GRASS: Siting Mobile Phone Base Stations
2. Basic Concepts
2.1 Mobile phone system
2.2 Base station characteristics
2.3 Assumptions
2.4 Rationale of the solution
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GRASS: Siting Mobile Phone Base Stations

7. GRASS: Siting Mobile Phone Base Stations
2.1 Mobile Phone System MS BS
MTX
[Courtesy of Wikipedia]
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GRASS: Siting Mobile Phone Base Stations

8. 2.2 Base Station Characteristics
On the supply side
Signal strength
Channel capacity
On the demand side
Terrain
Spatial distribution of mobile stations
[Courtesy of Wikipedia]
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GRASS: Siting Mobile Phone Base Stations

9. GRASS: Siting Mobile Phone Base Stations
2.3 Assumptions
Mobile phone system’s radio signal behaves like light
Only works on the “macro” type of cell
There are four different cell sizes in a GSM network - macro, micro, pico and umbrella cells.
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GRASS: Siting Mobile Phone Base Stations

10. 2.4 Rationale of the Solution
From a “worm’s eye view’:
Only those BS a MS can see can serve it.
Only those BS within service distance is qualified.
Closer BS, i.e. stronger signal, is preferred.
Preferred BS must still have capacity to serve.
Go through every possible combination to find the optimal set of BS.
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GRASS: Siting Mobile Phone Base Stations

11. GRASS: Siting Mobile Phone Base Stations
3. Implementation
3.1 Some compromises
3.2 The algorithm
3.3 The code structures
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GRASS: Siting Mobile Phone Base Stations

12. GRASS: Siting Mobile Phone Base Stations
3.1 Some Compromises
A deterministic approach to a stochastic process
Use readily available UNIX tools instead of low-level programming
Raster-based GIS tools and execution speed limit the precision
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GRASS: Siting Mobile Phone Base Stations

13. GRASS: Siting Mobile Phone Base Stations
3.2 The Algorithm (1)
Prepare the DTM and MS distribution map.
Create a BS’s distance map.
Block those distances over limit to create the availability mask.
Create the BS’s visibility map through line-of-sight (LOS) analysis.
Remove “invisible” areas from the availability mask.
Save the availability mask for later use.
Assign MS demands to it, from near to far, until reaching its capacity.
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GRASS: Siting Mobile Phone Base Stations

14. GRASS: Siting Mobile Phone Base Stations
3.2 The Algorithm (2)
Repeat step 2 through 7 for every other BS.
Select a set of BS and create the set’s assignment map.
Prepare each BS’s distance map so that those unavailable areas have extremely high value.
Identify each cell’s closest BS and record that BS in the assignment map.
Repeat step 9 through 12 for every possible BS set.
Examine and compare all sets’ result to find the optimal combination of BS.
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GRASS: Siting Mobile Phone Base Stations

15. 3.3.1 Code Listing of bs.test.sh
#!/bin/sh
if test "$GISBASE" = ""; then
echo "You must be in GRASS to run this program."
exit fi
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.dist.sh
bs.site.sh
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GRASS: Siting Mobile Phone Base Stations

16. 3.3.2 Code Structure of bs.dist.sh
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17. 3.3.3 Code Structure of bs.site.sh
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18. GRASS: Siting Mobile Phone Base Stations
4. Verification
4.1 The site
4.2 Results
4.3 Discussion
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19. GRASS: Siting Mobile Phone Base Stations
4.1 The Site (1)
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20. GRASS: Siting Mobile Phone Base Stations
4.1 The Site (2)
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21. GRASS: Siting Mobile Phone Base Stations
4.2 Results (1)
bs.dist.sh result for BS3
bs.dist.sh result for BS4
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GRASS: Siting Mobile Phone Base Stations

22. GRASS: Siting Mobile Phone Base Stations
4.2 Results (2)
bs.dist.sh result for BS5
bs.site.sh result
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GRASS: Siting Mobile Phone Base Stations

23. GRASS: Siting Mobile Phone Base Stations
4.3 Discussion
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GRASS: Siting Mobile Phone Base Stations

24. GRASS: Siting Mobile Phone Base Stations
5. Conclusion
5.1 Summary
5.2 Further work
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GRASS: Siting Mobile Phone Base Stations

25. GRASS: Siting Mobile Phone Base Stations
5.1 Summary
The BS siting problem is one type of the broader location-allocation problems.
The LOS-based GRASS application does provide an intuitive approach to the BS siting problem.
The current bottleneck of obtaining a solution is not at the LOS computation but at the assignment of BS capacities to MS demands from near to far.
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GRASS: Siting Mobile Phone Base Stations

26. GRASS: Siting Mobile Phone Base Stations
5.2 Further Work
Short-term:
Improve the robustness of the code so that under no circumstance will there be unused BS capacities.
Revise the code to provide more automation and execution efficiency.
Long-term:
Use a stochastic simulation instead of the deterministic heuristic to reflect the true nature of people making phone calls.
Replace the simple LOS analysis with a more realistic method to model the behavior of mobile phone radio signal.
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GRASS: Siting Mobile Phone Base Stations

27. Comments And Questions
The End
Comments
And
Questions