Approximating Radio Maps

1. Approximating Radio Maps Boaz Ben-Moshe (SFU)

2. Talk outline • Definition, Motivation • Known methods • New Radar like Algorithm • Experimental results • Future work

3. Approximating Radio Maps Goal: Given an antenna (on a terrain T) compute it's approximated signal strength over T (it's Radio Map):

4. Definition & Motivation Clients: • any wireless device Base Station: • Type, patterns Motivation: • WiMax - 802.16

5. Definition & Motivation Base Station: • Clients ant’ • Microwave links

6. Definition & Motivation Applications (of radio maps) • Locating Base Stations: • Guarding like. • Complex objective function. • Frequency Assignment:

7. Definition & Motivation Applications (of radio maps) • Locating Base Stations: • Frequency Assignment: • Conflict free frequency

8. Common method General Frame work: • Given a terrain and an antenna on it • Sample the area of 'interest' (SP) • For each p in SP: compute the signal strength • Compute a interpolation DS for SP Note: Propagation model: SKE, MKE

9. Approximating Radio-Maps General Frame work: Sampling Set (SP) Interpolation DS

10. Approximating Radio-Maps Sampling Methods: • Random, Grid • Client oriented • Terrain simplification • Hybrid main problem: runtime!

11. Main Obstacle run-time: computing radio maps is often the runtime bottle-neck of wireless networks facility location algorithms. Existing radio maps methods are often too slow or not accurate enough. Solution: Radar-Like-Algorithm (RLA)…

12. Approximating Radio Maps Related work [BCK 04]: Visibility Approximating: Given a terrain T and a view point p compute the set of points on the surface of T that are visible from p.

13. Radar-like: Pizza slice Radar DS: {pizza-slice} – fast query

14. Radar-like: Pizza slice left & right cross-sections  pizza slice.

15. Radar-like generic algorithm Given Terrain (T), view point (vp), and fixed angle (a=A): while(int i=0;i<360) { S1=cross-section(i); S2=cross-section(i+a); if(close enough(S1, S2)) { interpolate(S1, S2); a = A; i = min(360, i + a);} else a = a/2; }

16. Approximating Radio-Maps Generalizing radar-visibility to RF propagation model: • Discrete visibility (boolean) continues • Visibility a long a ray RF sampling

17. Approximating Radio-Maps 100*100 km elevation-map (of southern Israel) the brighter the higher. Antenna, 30 km radius.

18. Approximating Radio-Maps • Compute two consecutive cross-sections.

19. Approximating Radio-Maps • Compute a sample set along the each cross-section: using 2D terrain simplification methods.

20. Approximating Radio-Maps • Compute the signal strength along the sample set – using pipe-line method.

21. Approximating Radio-Maps • Compute the distance between the two signal-sections: • average / max / RMS distance

22. Approximating Radio-Maps Putting it all together: • Sensitive Radar algorithm • Sensitive 2D Simplification • Robust distance norm Fine Tuning: • None grid sampling (2D) • Parameters (terrain independent)

23. Radio-Maps: results Methods: • Random, Grid, TS • F-Radar: fixed angle • S-Radar: sensitive angle • A-Radar: advance sampling

24. Approximating Radio-Maps Grid Random TS F-Radar S-Radar • 5000 samples per radio-map

25. Approximating Radio-Maps Grid S-Radar • 5000 samples per radio-map

26. Radio-Maps: results Run time for the same size sampling. • The radar is 3-15 times faster than the regular sampling Radio Map methods. • More accurate.

27. Radio-Maps: results

28. Radio-Maps: results

29. Future-work • More testing • Advance interpolation methods • Interferences http://www.cs.bgu.ac.il/~benmoshe/RadioMaps/

30. Fin Questions?