Andrew lippman lip@mit edu october 2004
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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.

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Andrew Lippman [email protected] October, 2004

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Andrew lippman lip@mit edu october 2004

Viral Radio

Andrew Lippman

[email protected]

October, 2004


Andrew lippman lip mit 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

Viral Radio

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


Network co generation

Network Co-generation

Delivers realtime information by using intelligent RF

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


Andrew lippman lip mit october 2004

Radio Magic

Radios costing less than radio waves (Breadcrumbs)

There are no receivers (Receiving costs more than transmitting)

Collaboration makes it work


Andrew lippman lip mit october 2004

Cooperative Propagation

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

Direct Multi-hop Cooperative

(Special case of co-op)

“Wireless Broadcast Advantage”

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

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

Aggelos Bletsas, 2004


Andrew lippman lip mit october 2004

Propagation Space

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…

Aggelos Bletsas, 2004


Andrew lippman lip mit october 2004

RTS

CTS

Test Case

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)…

Aggelos Bletsas, 2004


Andrew lippman lip mit october 2004

Local Space and Time

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”)…

Aggelos Bletsas, 2004


Andrew lippman lip mit october 2004

Radio Magic


Andrew lippman lip mit october 2004

Radio Magic


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