MAGNÚS MÁR HALLDÓRSSON, PROFESSORSCHOOL OF COMPUTER SCIENCE | RU LECTURE MARATHON

Capacity of Wireless Networks

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?

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

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

www.hr.is

InterferenceRange

CS Models: e.g. Disk Model (Protocol Model)

ReceptionRange

www.hr.is6

www.hr.is

Example: Protocol vs. Physical Model

1m

Assume a single frequency (and no fancy decoding techniques!)

Let =3, =3, and N=10nWTransmission powers: PB= -15 dBm and PA= 1 dBm

SINR of A at D:

SINR of B at C:

4m 2m

A B C D

Is spatial reuse possible? NO Protocol Model

YES With power control

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

XY

Z

www.hr.is

Possible Application – Hotspots in WLAN

Potentially better: create hotspots with very high throughputEvery client outside a hotspot is served by one base station Better overall throughput – increase in capacity!

XY

Z

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...

www.hr.is

Future work

• Treating obstacles, walls, etc.

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)

reflection scattering diffractionshadowing

www.hr.is

Future work

• Treating obstacles, walls, etc.• Coding techniques• Spectrum management and cognitive radio• Communication structures• Basic questions: Weighted capacity & scheduling

www.hr.is

Thanks!

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 betweentwo nodes

Received signal power from sender

Received signal power from all other nodes (=interference)

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…?

www.hr.is

EE Models: e.g. SINR Model (Physical Model)

www.hr.is