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Approximating Radio Maps

Approximating Radio Maps. Boaz Ben-Moshe (SFU). Talk outline. Definition, Motivation Known methods New Radar like Algorithm Experimental results Future work. Approximating Radio Maps. Goal: Given an antenna (on a terrain T)

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Approximating Radio Maps

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  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?

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