1. MAGNÚS MÁR HALLDÓRSSON, PROFESSOR SCHOOL OF COMPUTER SCIENCE | RU LECTURE MARATHON Capacity of Wireless Networks

2. www.hr.is Current topic: Wireless Communication How much communication can you have in a wireless network? How long does it take to meet a given communication demand?

3. www.hr.is Capacity: How much communication can you have in a wireless network? Not a new problem... Studied empirically, in EE Studied analytically (EE) –Assumptions about input distribution –Only existential Studied algorithmically, in CS: –But, in simplistic models

4. www.hr.is The Algorithmic Capacity of Wireless Networks We want: -- General properties –that holds for all inputs and all situations -- Algorithms –to create efficient protocols

5. www.hr.is Interference Range CS Models: e.g. Disk Model (Protocol Model) Reception Range

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7. Example: Protocol vs. Physical Model 1m Assume a single frequency (and no fancy decoding techniques!) Let  =3,  =3, and N=10nW Transmission powers: P B = -15 dBm and P A = 1 dBm SINR of A at D: SINR of B at C: 4m 2m A B C D Is spatial reuse possible? NOProtocol Model YESWith power control

8. www.hr.is Possible Application – Hotspots in WLAN Traditionally: clients assigned to (more or less) closest access point  far-terminal problem  hotspots have less throughput X Y Z

9. www.hr.is Possible Application – Hotspots in WLAN Potentially better: create hotspots with very high throughput Every client outside a hotspot is served by one base station  Better overall throughput – increase in capacity! X Y Z

10. www.hr.is Some of our results First algorithm for capacity maximization with provable performance [Goussievskaia, H, Wattenhofer, Welzl, INFOCOM ‘09] Algorithmic results for capacity with power control [H, ESA ‘09] Generalizations: metrics, power assignments etc. [H, Mitra, SODA ‘11] Distributed algorithms [H, Mitra, submitted] More to come...

11. www.hr.is Future work Treating obstacles, walls, etc.

12. www.hr.is Attenuation by objects Shadowing (3-30 dB): –textile (3 dB) –concrete walls (13-20 dB) –floors (20-30 dB) reflection at large obstacles scattering at small obstacles diffraction at edges fading (frequency dependent) reflectionscatteringdiffractionshadowing

13. www.hr.is Future work Treating obstacles, walls, etc. Coding techniques Spectrum management and cognitive radio Communication structures Basic questions: Weighted capacity & scheduling

14. www.hr.is Thanks!

15. www.hr.is Signal-To-Interference-Plus-Noise Ratio (SINR) Formula Minimum signal- to-interference ratio Power level of sender u Path-loss exponent Noise Distance between two nodes Received signal power from sender Received signal power from all other nodes (=interference)

16. www.hr.is Network Topology? All these capacity studies make very strong assumptions on node deployment, topologies –randomly, uniformly distributed nodes –nodes placed on a grid –etc. What if a network looks differently…?

17. www.hr.is EE Models: e.g. SINR Model (Physical Model)

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