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Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

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Page 1: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

Interference Avoidance and Control

Ramki Gummadi (MIT)

Joint work with Rabin Patra (UCB)

Hari Balakrishnan (MIT)

Eric Brewer (UCB)

Page 2: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 2

Interference-limited networks

Interference: Fundamental consequence of resource sharing• Wireless LANs

• 3G, WiMax

• Mesh networks

Increasingly interference-limited, not noise-limited

Page 3: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 3

Interference: Friend or foe?

Challenges: Interference is time-varying• Bursty data traffic, not predictable voice traffic

• Radio propagation hard to model or predict

Opportunity: Unlike noise, interference isn’t random• If strong enough, understand and cancel it

• Avoid or control internal interference

• So, treating interference as noise is inefficient

Page 4: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 4

Goal: Improve aggregate throughput

Concurrent transmissions improve throughput• More total received power

But they also increase interference• Eliminate interference, maintaining concurrency?

Page 5: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 5

VWID: Variable WIDth channels

Interferers in orthogonal channels

Variable widths for heterogeneous SINRs and bursty demands

Page 6: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 6

Key questions (and talk outline)

How does VWID compare analytically to:• TDMA?

• CSMA?

How much improvement in practice?

Page 7: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 7

Capacity of variable-width channels

Multiple transmitters, one receiver Radios have a power limit Single antenna at a node Channel doesn’t vary in frequency or time

• Restriction removed in implementation

Additive White Gaussian Noise (AWGN)

Page 8: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 8

Two-transmitter capacity region

R1

R2

(bits/s/Hz)

(bits/s/Hz)

R1 < log2(1+P1

N) bits/ s/Hz;

R2 < log2(1+P2

N) bits/ s/Hz;

R1 + R2 < log2(1+P1 + P2

N) bits/ s/ Hz:

log2(1+ P1N )

log2(1+ P2N )

Optim

um sum

-capacity

Transmitter 1’s Rate

Page 9: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 9

VWID throughput

R1

R2

(bits/s/Hz)

(bits/s/Hz)

A

B

Optimum throughput at ®=

P1

P1+P

2

log2(1+ P2N )

log2(1+ P1N )

R1 < ®log2(1+P1

®N) bits/ s/ Hz;

R2 < (1¡ ®) log2(1+P2

(1¡ ®)N) bits/ s/ Hz:

log2(1+ P2N )

log2(1+ P1N )

®=0

®=1

Page 10: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 10

TDMA throughput: VWID throughput:

Improvement higher for smaller allocations, due to additional in vs.

VWID vs. TDMA: Two-node case

log2(1+P®N ) log2(1+

PN )

C1+C22 ;C1= log2(1+

P1N );C2= log2(1+

P2N )

®

> C1+C22

log2(2C1 +2C2 ¡ 1)

VWID

TDMA

R1

R2(bits/s/Hz)

A

B

log2(1+P1N )

VWIDlog2(1+P2N )

Page 11: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 11

VWID vs. TDMA: n-node case

VWID improves throughput by bits/s/Hz with n transmitters• vs.

SINRs show large variation With n weak nodes and one

strong node, aggregate TDMA throughput

VWID throughput

Rel

ativ

e th

roug

hput

6th node SINR (dB)

5 transmitters at 10 dB SINR

log2(1+nPN ) log2(1+

PN )

µ(log2(n))

! log2(1+PweakN )

! log2(1+Pstrong+nPweak

N )

VWID improves throughputlinearly with power (dB) of stronger node

VWID improves throughputlinearly with power (dB) of stronger node

Page 12: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 12

Time to send two bits at rates

CSMA node throughput:

• Hurts stronger node

VWID aggregate throughput improves with the total received power

VWID vs. CSMA: Two-node case

R1, R2:1R1+ 1R2

Rel

ativ

e th

roug

hput

2nd node SINR (dB)

Two transmitters, one at 10 dB SINR

11

R 1+ 1

R 2

= R1R2R1+R2 · minfR1;R2gVWID improves aggregate throughput

linearly with total received power (dB)VWID improves aggregate throughput linearly with total received power (dB)

Page 13: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 13

Key questions (and talk outline)

How does VWID compare analytically to:• TDMA?

• CSMA?

How much improvement in practice?

Page 14: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 14

VWID design

Channel assignment algorithm• 5,10 or 20 MHz variable-width sub-channels

• Maximize measured aggregate throughput

• Fairness: Don’t degrade link throughput

• Exhaustive search for sub-channels Accounts for frequency-selective fading Worst-case exponential in interferers

Page 15: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 15

Evaluation testbed

Outdoor testbed• Worst-case scenario (unequal

SINRs)

10 links (2-4 km), 25 dBi antennas, 5.3 GHz, Atheros

Point-point and point-multipoint topologies

CSMA MAC• Higher throughput than TDMA if

traffic is bursty

Unidirectional UDP traffic

E21,

Page 16: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 16

Point-point throughput improvement

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12

Throughput (Mbps)

CD

F

VWID Point-PointVWID Point-Point

No VWID, Point-Point

Median link throughput improves by 50%Median link throughput improves by 50%

Page 17: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 17

Point-Multipoint throughput improvement

0

10

20

30

40

50

60

70

80

90

100

0 2 4 6 8 10 12

Throughput (Mbps)

CD

F

VWID Point-Point

No VWID, Point-Point

Worst link throughput improves by 2xWorst link throughput improves by 2x

Page 18: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 18

Related Work

Interference cancellation• Decode colliding transmissions jointly• Signals typically differ by large SINR or coding rates

ZigZag decoding

• No coordination, but no net concurrency increase

1st timeslot2nd timeslot

Page 19: Interference Avoidance and Control Ramki Gummadi (MIT) Joint work with Rabin Patra (UCB) Hari Balakrishnan (MIT) Eric Brewer (UCB)

HotNets 2008 19

Conclusions

Increase concurrency, total received power Throughput improvements ~ 50-100% over

TDMA and CSMA Weakness: Inter-AP coordination (tomorrow) Future work: Practical implementation