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New directions in cognitive radio and spectrumsharing
Anant Sahaipresenting joint work with:
Danijela Cabric Mubaraq Mishra Rahul TandraArash Parsa Amin Gohari Kristen Woyach
George Atia Saligrama Venkatesh
BWRC and Wireless Foundations CenterU.C. Berkeley
Major support from the National Science Foundation
IEEE Workshop on Networking Technologies for SDR Networks
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 1 / 40
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Spectrum, spectrum, everywhere, but . . .
Available spectrum looks scarce.
Measurements suggest the allocated spectrum is vastly underutilized.
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 2 / 40
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Examine the problem from first principles
What is the deep reason for the existing waste?
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Examine the problem from first principles
What is the deep reason for the existing waste?3R’s: Rate,Reliability, andRobustness
◮ Rate and Reliability: our usual focus⋆ Fighting ergodic uncertainty⋆ Shannon capacity limits⋆ Error correcting codes
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 3 / 40
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Examine the problem from first principles
What is the deep reason for the existing waste?3R’s: Rate,Reliability, andRobustness
◮ Rate and Reliability: our usual focus⋆ Fighting ergodic uncertainty⋆ Shannon capacity limits⋆ Error correcting codes
◮ Robustness: the rest⋆ “Outage” within a system⋆ Coexistence with other systems⋆ Traditional approach: static guard bands (“frequency plans”)
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 3 / 40
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Examine the problem from first principles
What is the deep reason for the existing waste?3R’s: Rate,Reliability, andRobustness
◮ Rate and Reliability: our usual focus⋆ Fighting ergodic uncertainty⋆ Shannon capacity limits⋆ Error correcting codes
◮ Robustness: the rest⋆ “Outage” within a system⋆ Coexistence with other systems⋆ Traditional approach: static guard bands (“frequency plans”)
Separation of time and space scales◮ Years/decades: frequency planning◮ ms/minutes: actual use
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 3 / 40
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Examine the problem from first principles
What is the deep reason for the existing waste?3R’s: Rate,Reliability, andRobustness
◮ Rate and Reliability: our usual focus⋆ Fighting ergodic uncertainty⋆ Shannon capacity limits⋆ Error correcting codes
◮ Robustness: the rest⋆ “Outage” within a system⋆ Coexistence with other systems⋆ Traditional approach: static guard bands (“frequency plans”)
Separation of time and space scales◮ Years/decades: frequency planning◮ ms/minutes: actual use
In the future, technical solutions must bridge these scales!Rethinkrobustness architecture to enable rate/reliability gains.
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The basic policy alternatives for sharing
A new comprehensive commons — eliminate legacy users entirely.
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The basic policy alternatives for sharing
A new comprehensive commons — eliminate legacy users entirely.
Eliminate some legacy users and reallocate their spectrum.
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 4 / 40
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The basic policy alternatives for sharing
A new comprehensive commons — eliminate legacy users entirely.
Eliminate some legacy users and reallocate their spectrum.Preserve some priority for “primary users”
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets UWBSecondary must take care Denials Opportunistic
Current ultra-wideband: blanket permission◮ “Speak softly, but use a wideband”◮ Energy limited regime — works because most bands are not used
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The basic policy alternatives for sharing
A new comprehensive commons — eliminate legacy users entirely.
Eliminate some legacy users and reallocate their spectrum.Preserve some priority for “primary users”
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets UWBSecondary must take care Denials Opportunistic
Current ultra-wideband: blanket permission◮ “Speak softly, but use a wideband”◮ Energy limited regime — works because most bands are not used◮ Not future-proof!
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 4 / 40
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The basic policy alternatives for sharing
A new comprehensive commons — eliminate legacy users entirely.
Eliminate some legacy users and reallocate their spectrum.Preserve some priority for “primary users”
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets UWBSecondary must take care Denials Opportunistic
Current ultra-wideband: blanket permission◮ “Speak softly, but use a wideband”◮ Energy limited regime — works because most bands are not used◮ Not future-proof!
Even future “licensed” systems will likely haveopportunisticfeatures.
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Layering revisited
PHY
MAC
Regulatory
Application
Networking
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
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Sensing the primary’s presence
fc+W/2fc−W/2
UnknownActivity
UnknownActivityBand of Interest
Spectrum picture
Look for the primary in the ‘band of interest’Within band model:
◮ Primary signal:X(t)◮ Background and receiver noise:W(t)
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Impact of uncertainty: energy detector
Actual noise power,σ
2a ∈ [ 1
ασ
2n, ασ
2n]
If
P + σ2a ≤ ασ
2n
⇒ P ≤α
2 − 1α
σ2n
Energy detector fails to detectthe signal
UncertaintyZone
Signalpresent
TargetSensitivity
σ 2nα
σ 2n1/α ����������������������
����������������������
}Impossible
Noise power
Test statistic
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SNR wall for energy detector
−40 −35 −30 −25 −20 −15 −10 −5 00
2
4
6
8
10
12
14
Nominal SNR
log 10
N
x = 0.1 dBx = 0.001 dB x = 1 dB
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SNR wall for energy detector
0 0.5 1 1.5 2 2.5 3−14
−12
−10
−8
−6
−4
−2
0
2Position of SNR wall for radiometer
Noise uncertainty x (in dB)
SN
Rw
all (
in d
B)
−3.3 dB
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Primary structure vs environmental uncertainty
Primary Detector Key Uncertainty
Constellation any Noise distributionPilot coherent Phase-coherence timePilot any Noise color
Pulse-shape cyclostationary Delay-coherence time
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Primary structure vs environmental uncertainty
fc+W/2fc−W/2
UnknownActivity
UnknownActivity
Pilot tone
Spectrum picture
Band of Interest
Primary Detector Key Uncertainty
Constellation any Noise distributionPilot coherent Phase-coherence timePilot any Noise color
Pulse-shape cyclostationary Delay-coherence time
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Primary structure vs environmental uncertainty
UnknownActivity
Pilot
tone
−W/2fc f
c+W/2
Noise +Interferencelevel
MeasurementZone
UnknownActivity Band of Interest
}Primary Detector Key Uncertainty
Constellation any Noise distributionPilot coherent Phase-coherence timePilot any Noise color
Pulse-shape cyclostationary Delay-coherence time
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Primary structure vs environmental uncertainty
X(t)
t
Primary Detector Key Uncertainty
Constellation any Noise distributionPilot coherent Phase-coherence timePilot any Noise color
Pulse-shape cyclostationary Delay-coherence time
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Primary structure vs environmental uncertainty
T (Y )1 T (Y )2 T (Y )3 T (Y )4 T (Y )
5
H ( f )1 H ( f )
3H ( f )4H ( f )2 H ( f )
5
t
Primary Detector Key Uncertainty
Constellation any Noise distributionPilot coherent Phase-coherence timePilot any Noise color
Pulse-shape cyclostationary Delay-coherence time
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Detector robustness with coherence time
100
101
102
103
104
105
106
−60
−50
−40
−30
−20
−10
0
10
20
Coherence time, Nc samples
SN
R (i
n dB
)Location of SNR wall for various detectors
Modified feature detectorEnergy detectorPilot detector, 10% pilot powerCompletely known signal
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Are we just being paranoid?
Experimental validationUsed BEE2 and 2.4 GHz radio front-ends
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Are we just being paranoid?
Experimental validationUsed BEE2 and 2.4 GHz radio front-ends
Noise levels move around over a day.
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Are we just being paranoid?
Experimental validationUsed BEE2 and 2.4 GHz radio front-ends
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 12 / 40
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Are we just being paranoid?
Experimental validationUsed BEE2 and 2.4 GHz radio front-ends
The spectral correlation function shows spectral redundancy in a transformeddomain.
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Are we just being paranoid?
Experimental validationUsed BEE2 and 2.4 GHz radio front-ends
But this redundancy is blurred away by fast fading.
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
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How to model the requirement of safety
ON ON
Consider time-domain
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How to model the requirement of safety
ONSense
Use Band ON
Consider time-domain
Can sense a whitespace and use it.
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How to model the requirement of safety
ONSense
Use BandInterference
safe again
Consider time-domain
Can sense a whitespace and use it.
Some interference unavoidable.
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How to model the requirement of safety
ONSense
Use BandInterference
safe again
Consider time-domain
Can sense a whitespace and use it.
Some interference unavoidable.
Otherwisefear of return makes it impossible to recover.
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Consider strong primary transmitters
A
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Define a protected radius
B
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Mice can get close...
B
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But keep the lions far away!
B
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Fading
������
������
���� ��������������
������
0 5 10 15 20 25 30−50
−40
−30
−20
−10
0
10
20
30
40
50Maximum power for secondary transmitter
SNR margin ψ at secondary receiver (dB)
Max
sec
onda
ry p
ower
(dB
W)
No shadowing10 dB shadowing
10 dB
If you hear a weak signal, are you far away, or just locally faded?
The possibility of 10 dB of fading results in a 10 dB shift of the requireddetection margin
How to choose X dB of fading margin?
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The spatial equivalents�������������������������������������������� ����������(a)
(b)
Occupied Spectrum Hole Recovered Spectrum
time
TX 1
TX 2
TX 3
r p
r p
r p
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What are we giving up?
���� ��������������
������
������
������
Safe, but might be faded(fading uncertainty)
Will recover using diversity.
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What are we giving up?
���� ��������������
������
������
������
Safe, but might be faded(fading uncertainty)
Will recover using diversity.
Lights on, but no one home(receiver uncertainty)
Could be recovered using denials.But not worth it.
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What are we giving up?
���� ��������������
������
������
������
Safe, but might be faded(fading uncertainty)
Will recover using diversity.
Lights on, but no one home(receiver uncertainty)
Could be recovered using denials.But not worth it.
Safe, but not shadowed enough(symmetry uncertainty)Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 19 / 40
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Example Distribution of Primary Users
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Performance: Weighted Probability of Area Recovered
WPAR =
∫ ∞
rn
w(r)PFH(r) rdr
PFH(r) is the probability of finding a spectrum hole at distancer fromprimary.w(r) is a weighting function satisfying
∫ ∞
rnw(r) r dr = 1.
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Performance: Weighted Probability of Area Recovered
WPAR =
∫ ∞
rn
w(r)PFH(r) rdr
PFH(r) is the probability of finding a spectrum hole at distancer fromprimary.w(r) is a weighting function satisfying
∫ ∞
rnw(r) r dr = 1.
◮ More people are likely to be close to city centers
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Performance: Weighted Probability of Area Recovered
WPAR =
∫ ∞
rn
w(r)PFH(r) rdr
PFH(r) is the probability of finding a spectrum hole at distancer fromprimary.w(r) is a weighting function satisfying
∫ ∞
rnw(r) r dr = 1.
◮ More people are likely to be close to city centers◮ After enough distance, a new primary might exist.
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Performance: Weighted Probability of Area Recovered
WPAR =
∫ ∞
rn
w(r)PFH(r) rdr
PFH(r) is the probability of finding a spectrum hole at distancer fromprimary.w(r) is a weighting function satisfying
∫ ∞
rnw(r) r dr = 1.
◮ More people are likely to be close to city centers◮ After enough distance, a new primary might exist.
e.g. exponential:w(r) = K exp(−κr)
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What should the safety metric be?
Key issue: incentives and trust
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What should the safety metric be?
Key issue: incentives and trust◮ Probability of interference depends on the model.
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What should the safety metric be?
Key issue: incentives and trust◮ Probability of interference depends on the model.◮ Primary does not andshould not trust full model for:
⋆ Noise distribution
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What should the safety metric be?
Key issue: incentives and trust◮ Probability of interference depends on the model.◮ Primary does not andshould not trust full model for:
⋆ Noise distribution⋆ Secondary deployment assumptions
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What should the safety metric be?
Key issue: incentives and trust◮ Probability of interference depends on the model.◮ Primary does not andshould not trust full model for:
⋆ Noise distribution⋆ Secondary deployment assumptions⋆ Fading distribution
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What should the safety metric be?
Key issue: incentives and trust◮ Probability of interference depends on the model.◮ Primary does not andshould not trust full model for:
⋆ Noise distribution⋆ Secondary deployment assumptions⋆ Fading distribution
This fear must by accounted for:
FHI = sup0≤r≤rn
supFr∈Fr
PFr(D = 0|ractual = r)
whereFr is the uncertain distribution underlying algorithmD.
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The story so far in these metrics
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1Single Detector Performance
Wei
gh
ted
Pro
bab
ility
of
Fal
se A
larm
(W
PA
R)
Fear of Harmful Interference (FHI
)
Perfect detector, Number of Samples (N) = ∞Complete knowledge, Number of Samples (N) = 100Single Quantile knowledge, Number of Samples (N) = 100
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 23 / 40
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The story so far in these metrics
102
103
104
105
106
107
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
Gains from increasing the number of samples (FHI
= .1)
Wei
gh
ted
Pro
bab
ility
of
Are
a R
cove
red
(W
PA
R)
Number of samples (N)
Perfect detectorComplete knowledgeSingle quantile knowledge
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 23 / 40
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The story so far in these metrics
v
r n
Area never recoverd
Area recovered
No Noise uncertainty
v
r n
With Noise uncertainty
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 23 / 40
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The story so far in these metrics
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Fear of harmful interference (FHI
)
Wei
ghte
d P
roba
bilit
y of
Are
a R
ecov
ered
(W
PA
R)
Radiometer with noise uncertainty
No noise uncertainty (x=0)
1 dB noise uncertainty (x =1)
0.1 dB noise uncertainty (x=0.1)
0.01 dB noise uncertainty (x=0.01)
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 23 / 40
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 24 / 40
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Spatial domain: How can cooperation help?
It lessens the required detector performanceRough Analogy: Deck of cards wherered
cards signify bad fades.
Probability that I get aredcard: VeryHigh (50%)!
Probability that all users getredcards: Very Low
���������
���������
���� ����������������
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 25 / 40
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Spatial domain: How can cooperation help?
It lessens the required detector performanceRough Analogy: Deck of cards wherered
cards signify bad fades.
Probability that I get aredcard: VeryHigh (50%)!
Probability that all users getredcards: Very Low
���������
���������
���� ����������������
Multipath varies significantly on the scale ofλ
4 (10cm at 800MHz).Shadowing varies significantly on the scale 20-500m
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 25 / 40
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Spatial domain: How can cooperation help?
It lessens the required detector performanceRough Analogy: Deck of cards wherered
cards signify bad fades.
Probability that I get aredcard: VeryHigh (50%)!
Probability that all users getredcards: Very Low
���������
���������
���� ����������������
Multipath varies significantly on the scale ofλ
4 (10cm at 800MHz).Shadowing varies significantly on the scale 20-500m
Close enough to be relevant, far enough to be independent.
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 25 / 40
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Spatial domain: How can cooperation help?
It lessens the required detector performanceRough Analogy: Deck of cards wherered
cards signify bad fades.
Probability that I get aredcard: VeryHigh (50%)!
Probability that all users getredcards: Very Low
���������
���������
���� ����������������
Multipath varies significantly on the scale ofλ
4 (10cm at 800MHz).Shadowing varies significantly on the scale 20-500m
Close enough to be relevant, far enough to be independent.
It also increases robustness to the fading model.
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 25 / 40
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Does cooperation really work?
Experimental validation
Used BEE2 and 2.4 GHz radio front-ends
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 26 / 40
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Does cooperation really work?
Experimental validation
Used BEE2 and 2.4 GHz radio front-ends
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 26 / 40
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Time-domain: How can cooperation help?
Interference diversity!
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 27 / 40
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Cooperation story in correct metrics
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Wei
ghte
d P
roba
bilit
y of
Are
a R
ecov
ered
(W
PA
R)
Fear of Harmful Interference (FHI
)
ML cooperation
ML rule, 5 users (M=5)ML rule, 4 users (M=4)ML rule, 3 users (M=3)ML rule, 2 users (M=2)ML rule, 1 user (M=1)
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 28 / 40
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Cooperation story in correct metrics
100
101
102
103
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Wei
ghte
d P
roba
bilit
y of
Are
a R
ecov
ered
(W
PA
R)
Number of cooperating radios (M)
Multi−user cooperation: ML vs OR rule (FHI
= 10−2)
ML rule with complete knowledgeOR ruleOR rule with bounded single−quantile knowledgeML rule with single quantile knowledge
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 28 / 40
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Cooperation story in correct metrics
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Wei
ghte
d P
roba
bilit
y of
Are
a R
ecov
ered
(W
PA
R)
Fear of Harmful Interference (FHI
)
Two user (M=10) ML detector with varying correlation uncertainty
ρ
max =0
ρmax
=0.5
ρmax
=0.8
ρmax
=1
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 28 / 40
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Multiband detection: hope for the future
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Target PHI
Wei
ghte
d P
FH
Impact of GPS
Single radioSingle radio with GPS
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 29 / 40
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Multiband detection: hope for the future
10−5
10−4
10−3
10−2
10−1
100
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
1
Target PHI
Wei
ghte
d P
FH
MAP Cooperation with GPS
1 radio with GPS2 radios with GPS3 radios with GPS4 radios with GPS5 radios with GPS
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 29 / 40
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Multiband detection: hope for the future
Tower - A
Tower - B
r A
r B
r n
2r n + D
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 29 / 40
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Multiband detection: hope for the future
CR #2
CR #1 Tower A
Primary 1 Primary 2
Global Shadowing (S A )
Global Shadowing (S B )
Local Shadowing (L 2 )
Local Shadowing (L 1 )
Tower B Primary 3 Primary 4
Multipath (M 21 , M 22 , M 23 , M 24 )
Multipath (M 11, M 12 , M 13 , M 14 )
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 29 / 40
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Multiband detection: hope for the future
0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 10.65
0.7
0.75
0.8
0.85
0.9
0.95
1
Pro
babi
lity
of F
indi
ng a
Hol
e (P
FH
)
Normalized distance from tower A (r/rn)
Multiband, 1 radioSingleband, 1 radioMultiband, 2 radiosSingleband, 2 radios
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 29 / 40
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 30 / 40
![Page 76: New directions in cognitive radio and spectrum sharing](https://reader033.vdocument.in/reader033/viewer/2022050612/62743ca4206e013b820ce416/html5/thumbnails/76.jpg)
The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)◮ Pick “one true algorithm” and approve it: evolvability problems
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)◮ Pick “one true algorithm” and approve it: evolvability problems◮ Squeezes out innovation: return of “beauty contest”
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)◮ Pick “one true algorithm” and approve it: evolvability problems◮ Squeezes out innovation: return of “beauty contest”◮ Draconian Digital Restrictions Management
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)◮ Pick “one true algorithm” and approve it: evolvability problems◮ Squeezes out innovation: return of “beauty contest”◮ Draconian Digital Restrictions Management
Shift to somea posteriori enforcement
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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The regulatory challenge
Part-15-style device-certification would be great◮ Easy to enforce◮ Easy to generalize to single-user sensing◮ Terrible for QoS
Could attempta priori certification of cooperative algorithms◮ Undecidability? (Need a proof of cooperative correctness)◮ Pick “one true algorithm” and approve it: evolvability problems◮ Squeezes out innovation: return of “beauty contest”◮ Draconian Digital Restrictions Management
Shift to somea posteriori enforcement◮ Ideas already present in Coase ’59 and de Vany ’69.◮ Users incur liability for harmful interference and are punished
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 31 / 40
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A toy model
TX No TX
S2: Wait S
1: FA
S3: Illegal TX S
0: Legal TX
S4: Pen. Box S
5: Pen. Box
Primary Use
Secondary Use
p
q
S0
S0
S1 S
1S
2S
2
S3
S3
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
00.25
0.50.75
10
0.25
0.5
0.75
1
pP(Pri TX)
Uto
tal
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
00.25
0.50.75
10
0.25
0.5
0.75
1
pP(Pri TX)
p chea
t
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
00.25
0.50.75
10
0.25
0.5
0.75
1
pP(Pri TX)
Uco
llide
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
00.25
0.50.75
10
0.250.5
0.751
pP(Pri TX)
p chea
t
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
TX No TX
S2: Wait S
1: FA
S3: Illegal TX S
0: Legal TX
S4: Pen. Box S
5: Pen. Box
Primary Use
Secondary Use
p
q
S0
S0
S1 S
1S
2S
2
S3
S3
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
0
0.25
0.5
0.75
10
0.25
0.5
0.75
1
pP(Pri TX)
p chea
t
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
0 0.25 0.5 0.75 10
0.25
0.5
0.75
1P
(Pri
TX
)
p
β = 1.5β = 1.4β = 1.3β = 1.2β = 1.1A
B
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
0 0.2 0.4 0.6 0.8 10
1
2
3
4
5
ppen
β
pcatch
= .2
pcatch
= .4
pcatch
= .6
pcatch
= 1
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
00.25
0.50.75
1
00.25
0.50.75
10
0.25
0.5
0.75
1
pP(Pri TX)
Uto
tal
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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A toy model
TX No TX
S2: Wait S
1: FA
S3: Illegal TX S
0: Legal TX
S4: Pen. Box S
5: Pen. Box
Primary Use
Secondary Use
p
q
S0
S0
S1 S
1S
2S
2
S3
S3
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
![Page 96: New directions in cognitive radio and spectrum sharing](https://reader033.vdocument.in/reader033/viewer/2022050612/62743ca4206e013b820ce416/html5/thumbnails/96.jpg)
A toy model
0 0.2 0.4 0.6 0.8 10
2
4
6
8
10
12
14
pwrong
β
pcatch
= 0.2
pcatch
= 0.4
pcatch
= 0.6
pcatch
= 0.8
pcatch
= 1
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 32 / 40
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 33 / 40
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 34 / 40
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 34 / 40
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity
Anant Sahai (UC Berkeley) Cognitive Sharing 6/15/2008 34 / 40
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility⋆ Nonobvious catastrophic performance degradation for multiuser techniques.
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility⋆ Nonobvious catastrophic performance degradation for multiuser techniques.⋆ Doesn’t help with Trolls
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility⋆ Nonobvious catastrophic performance degradation for multiuser techniques.⋆ Doesn’t help with Trolls
◮ MAC-Layer Identity
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility⋆ Nonobvious catastrophic performance degradation for multiuser techniques.⋆ Doesn’t help with Trolls
◮ MAC-Layer Identity⋆ A signature that shows up in the pattern of interference
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Wireless + anonymity: a serious problem
Faulhaber’s “Hit and run radios” vs Hatfield’s “Spectrum trolls”What can we do about identity?
◮ PHY-Layer Identity⋆ Easy to think about: just transmit your name⋆ Obvious overhead: power in identity⋆ Removes flexibility⋆ Nonobvious catastrophic performance degradation for multiuser techniques.⋆ Doesn’t help with Trolls
◮ MAC-Layer Identity⋆ A signature that shows up in the pattern of interference⋆ What is the overhead?
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Trollsbane: No harm, no foul
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Trollsbane: No harm, no foul
0.1 0.12 0.14 0.16 0.18 0.2 0.22 0.24 0.26 0.28 0.30.75
0.8
0.85
0.9
0.95
1
∆=θ1−θ
0
Util
izat
ion
(1−
γ)
PF=15%, P
M=10%, T=280 slots
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Identity through superimposed codes
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Identity through superimposed codes
0.5 0.55 0.6 0.65 0.7 0.75 0.8 0.85 0.910
1
102
103
104
105
106
Utilization (p)
Tim
e to
Con
vict
ion
(Tc)
in s
lots
Information Theoretic LBRandom Coding UB found from UD codes propertiesRandom Coding UB found from the bipartite graph
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Identity through superimposed codes
102
103
104
105
106
107
108
109
102
103
104
105
106
Total Number of Systems (N)
Tim
e to
Con
vict
ion
T c in s
lots
Random Coding Upper BoundInformation Theoretic Lower Bound
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Outline
MotivationSpectrum sensing: uncertainty is key challenge
◮ Single-detector sensitivity◮ Overhead-oriented metrics◮ Cooperation and multiband sensing
Technical questions in regulation◮ A simple model ofa posteriori enforcement◮ Do you know who I am?
Conclusions
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Decouple sensor network and communication network
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets Spectrum MonitorsSecondary must take care Denials Opportunistic
Purely opportunistic useis harder than it looks.
Cooperation is just another word for “infrastructure”
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Decouple sensor network and communication network
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets Spectrum MonitorsSecondary must take care Denials Opportunistic
Purely opportunistic useis harder than it looks.
Cooperation is just another word for “infrastructure”Dedicatedsensor-networkinfrastructure
◮ Assume network nodes know where they are◮ Assume large spatial extent beyond primary user scale◮ Construct primary usage map on slower time-scale
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Decouple sensor network and communication network
Interference management is Interference management notprimary’s responsibility primary’s responsibility
Secondary has permission Markets Spectrum MonitorsSecondary must take care Denials Opportunistic
Purely opportunistic useis harder than it looks.
Cooperation is just another word for “infrastructure”Dedicatedsensor-networkinfrastructure
◮ Assume network nodes know where they are◮ Assume large spatial extent beyond primary user scale◮ Construct primary usage map on slower time-scale
Coordinate secondary radios by giving explicit permission.
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“Disneyland” vs “Yosemite”
Owner controls access topreserve QoS
“Band-managers” own the bandand leases it out to users.
Monopoly
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“Disneyland” vs “Yosemite”
Owner controls access topreserve QoS
“Band-managers” own the bandand leases it out to users.
Monopoly
Public owns and sets broadguidelines for use
Unlicensed users are on theirown.
Competition
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“Disneyland” vs “Yosemite”
Owner controls access topreserve QoS
“Band-managers” own the bandand leases it out to users.
Monopoly
Public owns and sets broadguidelines for use
Unlicensed users are on theirown.
Competition
“Spectrum tour guide” can coordinate users without owning bands.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Sounds familiar: Rhetoric around the Internet boom in the 90s. . .
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Sounds familiar: Rhetoric around the Internet boom in the 90s. . .But what actually happened?
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Sounds familiar: Rhetoric around the Internet boom in the 90s. . .But what actually happened?
◮ Many smaller niche applications were enabled.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Sounds familiar: Rhetoric around the Internet boom in the 90s. . .But what actually happened?
◮ Many smaller niche applications were enabled.◮ But big players got bigger — used the new technology tocut costs and
further exploit economies of scale.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Observation:carriers are users of spectrum, not mere holders.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Observation:carriers are users of spectrum, not mere holders.Why pay for spectrum when you could just take it?
◮ Achieve ubiquitous coverage through opportunistic use!◮ Pay only when truly scarce.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Observation:carriers are users of spectrum, not mere holders.Why pay for spectrum when you could just take it?
◮ Achieve ubiquitous coverage through opportunistic use!◮ Pay only when truly scarce.
Carriers can build and update the sensor network infrastructure.
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Speculation: who benefits from cognitive radio?
Conventional answer: new entrants and other small players denied accessto spectrum by the existing regime.
Observation:carriers are users of spectrum, not mere holders.Why pay for spectrum when you could just take it?
◮ Achieve ubiquitous coverage through opportunistic use!◮ Pay only when truly scarce.
Carriers can build and update the sensor network infrastructure.
Cheap devices will win out over more expensive ones.
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