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

2. Interference-limited networks
Interference: Fundamental consequence of resource sharing
Wireless LANs
3G, WiMax
Mesh networks
Increasingly interference-limited, not noise-limited
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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
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4. Goal: Improve aggregate throughput
Concurrent transmissions improve throughput
More total received power
But they also increase interference
Eliminate interference, maintaining concurrency?
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5. VWID: Variable WIDth channels
Interferers in orthogonal channels
Variable widths for heterogeneous SINRs and bursty demands
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6. Key questions (and talk outline)
How does VWID compare analytically to:
TDMA?
CSMA?
How much improvement in practice?
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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)
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8. Two-transmitter capacity region
Optimum sum-capacity R2
(bits/s/Hz) l o g 2 ( 1 + P N ) R1
(bits/s/Hz) l o g 2 ( 1 + P N ) P
Transmitter 1’s Rate 1 R
< l ( 1 + ) b o g i t / / H 1 s s z 2 N ; P ( 2 R l 1 + )
< b i o g t / / H 2 2 s s z N ; P + P R + R
< l ( 1 2 ) b o g 1 + i t / / s s H 1 2 z 2 N :
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9. VWID throughput ® = 1 ® = l o g ( 1 + ) l o g ( 1 + ) ® = l o g ( 1 +
(bits/s/Hz)
Optimum throughput at A l o g 2 ( 1 + P N ) l o g 2 ( 1 + P N ) = B = P 1 + 2 R1
(bits/s/Hz) = 1 l o g 2 ( 1 + P N ) l o g 2 ( 1 + P N ) R 1
< l o g 2 ( + P N ) b i t s / H z ; R 2
< ( 1 ) l o g + P N b i t s / H z :
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10. VWID vs. TDMA: Two-node case
TDMA throughput:
VWID throughput:
Improvement higher for smaller allocations, due to additional in
vs. C 1 + 2 ; = l o g ( P N )
VWID
TDMA R1 R2
(bits/s/Hz) A B l o g 2 ( 1 + P N ) l o g 2 ( C 1 + )
> C 1 + 2 l o g 2 ( 1 + P N ) l o g 2 ( 1 + P N ) l o g 2 ( 1 + P N )
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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
Relative throughput
6th node SINR (dB)
5 transmitters at 10 dB SINR ( l o g 2 n ) l o g 2 ( 1 + n P N ) l o g 2 ( 1 + P N )
VWID improves throughput
linearly with power (dB) of stronger node ! l o g 2 ( 1 + P w e a k N ) ! l o g 2 ( 1 + P s t r n w e a k N )
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12. VWID vs. CSMA: Two-node case
Time to send two bits at rates
CSMA node throughput:
Hurts stronger node
VWID aggregate throughput improves with the total received power
Relative throughput
2nd node SINR (dB)
Two transmitters, one at 10 dB SINR 1 R + 2 R 1 , 2 : 1 R + 2 =
VWID improves aggregate throughput
linearly with total received power (dB) m i n f R 1 ; 2 g
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13. Key questions (and talk outline)
How does VWID compare analytically to:
TDMA?
CSMA?
How much improvement in practice?
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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
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15. Evaluation testbed Outdoor testbed1,
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
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16. Point-point throughput improvement
Median link throughput improves by 50%
VWID Point-Point
VWID Point-Point
No VWID, Point-Point
Label stuff, note median for pmp.
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17. Point-Multipoint throughput improvement
VWID Point-Point
No VWID, Point-Point
Worst link throughput improves by 2x
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18. Related Work Interference cancellation ZigZag decoding
Decode colliding transmissions jointly
Signals typically differ by large SINR or coding rates
ZigZag decoding
No coordination, but no net concurrency increase
2nd timeslot
1st timeslot
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19. Conclusions Increase concurrency, total received power
Throughput improvements ~ % over TDMA and CSMA
Weakness: Inter-AP coordination (tomorrow)
Future work: Practical implementation
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