andrew lippman lip@mit october, 2004

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Andrew Lippman [email protected] October, 2004 Viral Radio

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Viral Radio. Andrew Lippman [email protected] October, 2004. Viral Innovation. Scalable Incremental Contributory. Viral systems are innovative through modularity and distribution of capability -- the intelligence is at the ends e.g.: Fax machines, Internet. Viral Radio. - PowerPoint PPT Presentation

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Page 1: Andrew Lippman lip@mit October, 2004

Andrew Lippman

[email protected], 2004

Viral Radio

Page 2: Andrew Lippman lip@mit October, 2004

Scalable

Incremental

Contributory

Viral Innovation

Viral systems are innovative through modularity and distribution of capability -- the intelligence is at the ends

e.g.: Fax machines, Internet

Page 3: Andrew Lippman lip@mit October, 2004

Viral Radio

CapacityBandwidth/Noden

CapacityBandwidth/Node

~nn

Open systems such as PCs gain capacity with more units, traditional communications systems divide fixed capacity among elements.

Can we make communications systems (telephones, networks) that are viral and economic?

Social Context

Page 4: Andrew Lippman lip@mit October, 2004

Network Co-generation

Delivers realtime information by using intelligent RF

Scales adhoc networks by limiting radiation to nodes in between two parties

Page 5: Andrew Lippman lip@mit October, 2004

Radios costing less than radio waves (Breadcrumbs)

There are no receivers (Receiving costs more than transmitting)

Radio Magic

Collaboration makes it work

Page 6: Andrew Lippman lip@mit October, 2004

Wireless = Broadcast (it makes it hard… it makes it challenging…)

“Wireless Broadcast Advantage”

Antenna Sharing: exploits observation of a common “property” across different users (antennas) in space…

Our contribution: distributed, “adaptive” algorithmsapplicable in practice…

Direct Multi-hop Cooperative

(Special case of co-op)

Cooperative Propagation

Aggelos Bletsas, 2004

Page 7: Andrew Lippman lip@mit October, 2004

Closer is not always the better… fading is not always harmful (MIMO results)…

Instantaneous wireless channel conditions matter (not only average) -

Algorithms should adapt to wireless propagation “instantaneously” (within channel coherence time) - no need for topology estimation…

Propagation Space

Aggelos Bletsas, 2004

Page 8: Andrew Lippman lip@mit October, 2004

Method of distributed timers = opportunistic relaying

Mapping channel conditions to time!

Exploiting RTS/CTS packets of MAC and reciprocity…best path = relay that expires first…

Collision probability depends on λ (user defined)…

RTS

CTS

Test Case

Aggelos Bletsas, 2004

Page 9: Andrew Lippman lip@mit October, 2004

Antenna sharing for cooperative position estimation

Estimate your location relatively to neighbors with “good” signal paths (high SNR measurements).

Prior art found in protein structure determination(“molecular distance geometry problem”)…

Local Space and Time

Aggelos Bletsas, 2004

Page 10: Andrew Lippman lip@mit October, 2004

Radio Magic

Page 11: Andrew Lippman lip@mit October, 2004

Radio Magic

Page 12: Andrew Lippman lip@mit October, 2004