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MASSIMO FRANCESCHETTI University of California at San Diego Information-theoretic and physical limits on the capacity of wireless networks P. Minero (UCSD), M. D. Migliore (U. Cassino)

MASSIMO FRANCESCHETTI University of California at San Diego

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Information-theoretic and physical limits on the capacity of wireless networks. MASSIMO FRANCESCHETTI University of California at San Diego. P. Minero (UCSD), M. D. Migliore (U. Cassino). TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: A A A A A. - PowerPoint PPT Presentation

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Page 1: MASSIMO FRANCESCHETTI University of California at San Diego

MASSIMO FRANCESCHETTIUniversity of California at San

Diego

Information-theoretic and physical limits on the capacity of wireless

networks

P. Minero (UCSD), M. D. Migliore (U. Cassino)

Page 2: MASSIMO FRANCESCHETTI University of California at San Diego

Standing on the shoulder of giants

Page 3: MASSIMO FRANCESCHETTI University of California at San Diego

The problem

• Computers equipped with power constrained radios • Randomly located • Random source-destination pairs• Transmit over a common wireless channel• Possible cooperation among the nodes• Maximum per-node information rate (bit/sec) ?

Page 4: MASSIMO FRANCESCHETTI University of California at San Diego

Scaling approach

• All pairs must achieve the same rate• Consider the limit

IEEE Trans-IT (2000)

Page 5: MASSIMO FRANCESCHETTI University of California at San Diego

Information-theoretic limits

• Provide the ultimate limits of communication

•Independent of any scheme used for communication

Page 6: MASSIMO FRANCESCHETTI University of California at San Diego

• Assume physical propagation model

• Allow arbitrary cooperation among nodes

Xie Kumar IEEE Trans-IT (2004)

Xue Xie Kumar IEEE Trans-IT (2005)

Leveque, Telatar IEEE Trans-IT (2005)

Ahmad Jovicic Viswanath IEEE Trans-IT (2006)

Gowaikar Hochwald Hassibi IEEE Trans-IT (2006)

Xie Kumar IEEE Trans-IT (2006)

Aeron Saligrama IEEE Trans-IT (2007)

Franceschetti IEEE Trans-IT (2007)

Ozgur Leveque Preissmann IEEE Trans-IT (2007)

Ozgur Leveque Tse IEEE Trans-IT (2007)

Classic Approach

Page 7: MASSIMO FRANCESCHETTI University of California at San Diego

Information theoretic “truths”

High attenuation regime

Low attenuation regime without fading

Low attenuation regime with fading

No attenuation regime, fading only

Page 8: MASSIMO FRANCESCHETTI University of California at San Diego

Good research should shrink the knowledge tree

Page 9: MASSIMO FRANCESCHETTI University of California at San Diego

There is only one scaling law

This is a degrees of freedom limitation dictated by Maxwell’s physics and by Shannon’s theory of information. It is independent of channel models and cannot be overcome by any cooperative communication scheme.

Page 10: MASSIMO FRANCESCHETTI University of California at San Diego

Approach

Page 11: MASSIMO FRANCESCHETTI University of California at San Diego

. . .

Approach

. . .. . .

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Information flow decomposition

ADV

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First flow component

. . .. . .

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Second flow component

. . .. . . . . .

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Second flow component

D

O

M

Page 16: MASSIMO FRANCESCHETTI University of California at San Diego

Singular values have a phase transition at the critical value

Hilbert-Schmidt decomposition of operator

G

Page 17: MASSIMO FRANCESCHETTI University of California at San Diego

Singular values of operatorG

Page 18: MASSIMO FRANCESCHETTI University of California at San Diego

Degrees of freedom theorem

O

Page 19: MASSIMO FRANCESCHETTI University of California at San Diego

The finishing touches

O

Page 20: MASSIMO FRANCESCHETTI University of California at San Diego

Understanding the space resource

Space is a capacity bearing object

Geometry plays a fundamental role in determining the number of degrees of freedom and hence the information capacity

Page 21: MASSIMO FRANCESCHETTI University of California at San Diego

Geometrical configurations

In 2D the network capacity scales with the perimeter boundary of the network

In 3D the network capacity scales with the surface boundary of the network

Page 22: MASSIMO FRANCESCHETTI University of California at San Diego

A different configuration

Distribute nodes in a 3D volume of size

Nodes are placed uniformly on a 2D surface inside the volume

Page 23: MASSIMO FRANCESCHETTI University of California at San Diego

Different configurations

Page 24: MASSIMO FRANCESCHETTI University of California at San Diego

The endless enigma (Salvador

Dali)

A hope beyond a shadow of a dream (John Keats)

To be continued…