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Exploiting Diversity in Wireless Networks

Nitin H. VaidyaUniversity of Illinois at Urbana-Champaign

www.crhc.uiuc.edu/wireless

Presentation at Mesh Networking SummitSnoqualmie, WA, June 23-24, 2004

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Capacity of Wireless Networks

Limited by

Interference Available spectrum

Need to find ways to get most out of availablespectrum

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Diversity / Multiplicity / Heterogeneity

Diversity provides flexibility in using available resources

Can help improve performance

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Diversity / Multiplicity / Heterogeneity

Research Agenda

Abstractions that capture diversity

Protocols that exploit diversity

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Diversity / Heterogeneity

Many dimensions:

Physical layer

Architecture

Upper layer

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Channel Diversity

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Channel Diversity

Multiple channels can help improve performance

Obvious approaches:

•Exploit diversity to choose channel with best gain

•Use multiple channels simultaneously to improve capacity

Developing practical protocols for the “obvious” approaches is still a challenge

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Alternative Approach

Exploit protocol characteristics to benefit from the diversity

Examples:•Pipelining

•Backup routes

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Backoff Data / ACKRTS/CTS

Channel contention resolved using backoff(and optional RTS/CTS)

IEEE 802.11

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Backoff Data / ACKRTS/CTS

Unproductive

Backoff keeps channel idle unproductive Most protocols have such idle contention periods

Simple Observation

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Data / ACK

Backoff RTS/CTS Backoff RTS/CTS RTS/CTSBackoff

Data / ACK

Pipelining Using Multiple Channels

Control Channel: Backoff and RTS/CTS Data Channel: Data and ACK

Stage 1

Stage 2

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Pipelining works well only if pipeline stages are balanced !

Data / ACK

Backoff RTS/CTS Backoff RTS/CTS RTS/CTSBackoff

Data / ACK

Control Channel

Data Channel

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Solution: Partial Pipelining

Only partially resolve channel contention in the pipelined stage

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Partial Pipelining

Stage 1: Narrow-Band Busy Tone Channel Stage 2: Data channel

Backoff phase 1 Backoff phase 1 Backoff phase 1

Data/ACKRTS/CTSBackoff phase 2

Data/ACKRTS/CTSBackoff phase 2

This slide contained an error in the set of slides used at the Mesh Networking Summit.The error has been corrected in this version.

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Partial Pipelining

No packets transmitted on busy tone channel

Bandwidth can be small

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Partial Pipelining

By migrating backoff to a narrow-band channel, cost of backoff is reduced

Data Channel Bandwidth

Busy Tone Channel Bandwidth Backoff Duration

Area = cost of backoff

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Moral of the Story

Looking beyond physical layerdiversity exploitation schemes helps

Protocol characteristics can be exploited

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Another Example

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Multiple Interfaces

Consider devices equipped with both 802.11a and b

802.11a 802.11b

Higher max rate Lower max rate

Lower range Higher range

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Channel Diversity

802.11b “network”

denser than the 802.11a network but provides lower rate

Example approach:

Use 802.11a as primary network

Use 802.11b network to provide backup routes when 802.11a routes fail

– The 802.11b network could be used for other things too

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Protocol Interactions

For TCP, route failure more painful than a degradation in available capacity

The backup routes can avoid a route failure

Benefits of added capacity can be magnified by exploiting protocol behavior

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Research Agenda

Develop practical protocols that can exploit diversity

Pay attention to protocol characteristics

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Antenna Heterogeneity

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Antenna Heterogeneity

“Fixed beam” antennas prevalent on mobile devices Omnidirectional antennas (often with diversity)

Other antennas likely to become more prevalent Switched, steered, adaptive, smart …

– Can form narrow beamforms, which may be changed over time

Re-configurable antennas– Beamforms can be changed over time by reconfiguring

the antenna, but not necessarily narrow beams

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Antenna Heterogeneity

Beamforms: All antennas are not made equal

Timescale: Can beamforms be changed at packet timescales?

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Protocol Design

Protocols designed for “fixed” beam antennas inadequate with “movable” beam antennas

State of the art

MAC Protocols for specific antenna capabilities

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Research Challenge

How to design “antenna-adaptive” protocols ?

Need to develop suitable antenna abstractions that span a range of antenna designs

Forces us to think about essential characteristics of antennas

– Example: Variability of beamforms a more fundamental property than directionality

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Diversity / Heterogeneity

Many dimensions:

Physical layer

Architecture

Upper layer

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Pure Ad Hoc Networks

No “infrastructure” All communication over (one or more) wireless

hops

EA

B CD

X

Z

Ad hoc connectivity

Y

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Hybrid Networks

Infrastructure + Ad hoc connectivity

EA

B CD

AP1 AP2

X

Z

infrastructure

Ad hoc connectivity

Y

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Hybrid Networks

Infrastructure may include wireless relays

A

CD

AP1 AP2

X

Z

infrastructure

Ad hoc connectivity

Y

B

RP

R

R

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Hybrid Networks

Heterogeneity Some hosts connected to a backbone, most are not Access points/relays may have more processing

capacity, energy

A

CD

AP1 AP2

X

Z

infrastructure

Ad hoc connectivity

Y

B

RP

R

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Heterogeneity Beneficial

Infrastructure provides a frame of reference– Provide location-aware services– Reduce route discovery overhead

AP0 AP1 AP2 AP3

A

B DR2R1 R3

A

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Heterogeneity Beneficial

Reduce diameter of the network Lower delay Potentially greater per-flow throughput

A

CD

AP1 AP2

X

Z

infrastructure

Ad hoc connectivity

Y

B

RP

R

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Infrastructure Facilitates New Trade-Offs (hypothetical curves)

User density distributionaffects the trade-off

Ad hoc-ness

co

nn

ec

tiv

ity

ov

erh

ea

d

Poor Man’s Ad Hoc Network

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Research Issues

How to trade “complexity” with “performance” ?

– Parameterize ad hoc-ness ?

Should the spectrum be divided between infrastructure and ad hoc components?

What functionality for relays / access points?

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Misbehavior

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Misbehavior

Misbehavior occurs with limited resources

Violating protocol specifications benefits misbehaving hosts

Example: Small backoffs in 802.11 higher throughput

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Research Agenda

Protocols that maximize performance while discouraging/penalizing misbehavior

Challenge: Wireless channel prone to temporal and spatial

variations Different players see different channel state Impossible to detect misbehavior 100% reliably

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Conclusions

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Conclusions

Diversity/Heterogeneity natural to wireless networks

Need better abstractions to capture the diversity

Need protocols that can exploit available diversity

Need to be able to survive misbehavior

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Other Research

Distributed algorithms for multi-hop wireless networks

Clock synchronization Message ordering Leader election Mutual exclusion

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Thanks! www.crhc.uiuc.edu/wireless

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