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Approximating Radio Maps

Boaz Ben-Moshe (SFU)

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Talk outline

• Definition, Motivation

• Known methods

• New Radar like Algorithm

• Experimental results

• Future work

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Approximating Radio Maps

Goal: Given an antenna (on a terrain T)compute it's approximated signal strength

over T (it's Radio Map):

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Definition & Motivation

Clients: • any wireless device

Base Station:• Type, patterns

Motivation:• WiMax - 802.16

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Definition & Motivation

Base Station:

• Clients ant’• Microwave links

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Definition & Motivation

Applications (of radio maps)

• Locating Base Stations:– Guarding like.– Complex objective function.

• Frequency Assignment:

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Definition & Motivation

Applications (of radio maps)

• Locating Base Stations:• Frequency Assignment:

– Conflict free frequency

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Common methodGeneral 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

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Approximating Radio-Maps General Frame work:

Sampling Set (SP) Interpolation DS

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Approximating Radio-Maps Sampling Methods:

• Random, Grid

• Client oriented

• Terrain simplification

• Hybrid

main problem: runtime!

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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)…

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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.

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Radar-like: Pizza slice

Radar DS: {pizza-slice} – fast query

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Radar-like: Pizza slice

left & right cross-sections pizza slice.

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Radar-like generic algorithm

1. Given Terrain (T), view point (vp), and fixed angle (a=A):

2. while(int i=0;i<360) {

3. S1=cross-section(i);

4. S2=cross-section(i+a);

5. if(close enough(S1, S2)) {

6. interpolate(S1, S2);

7. a = A; i = min(360, i + a);}

8. else a = a/2; }

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Generalizing radar-visibility to RF propagation model:

● Discrete visibility (boolean) continues● Visibility a long a ray RF sampling

Approximating Radio-Maps

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Approximating Radio-Maps

100*100 km elevation-map (of southern Israel) the brighter the higher.

Antenna, 30 km radius.

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Approximating Radio-Maps • Compute two consecutive cross-

sections.

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Approximating Radio-Maps • Compute a sample set along the each

cross-section: using 2D terrain simplification methods.

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Approximating Radio-Maps • Compute the signal strength along the

sample set – using pipe-line method.

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Approximating Radio-Maps

• Compute the distance between the two signal-sections:

• average / max / RMS distance

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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)

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Radio-Maps: resultsMethods:

• Random, Grid, TS

• F-Radar: fixed angle

• S-Radar: sensitive angle

• A-Radar: advance sampling

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Approximating Radio-Maps

Grid Random TS F-Radar S-Radar

• 5000 samples per radio-map

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Approximating Radio-Maps

Grid S-Radar• 5000 samples per radio-map

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Radio-Maps: resultsRun time for the same size sampling.

• The radar is 3-15 times faster than the regular sampling Radio Map methods.

• More accurate.

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Radio-Maps: results

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Radio-Maps: results

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Future-work• More testing

• Advance interpolation methods

• Interferences

http://www.cs.bgu.ac.il/~benmoshe/RadioMaps/

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Fin

Questions?