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Spectrum Sharing for Unlicensed Bands
Spectrum Sharing for Unlicensed Bands
Raul Etkin, Abhay Parekh, and David TseDept of EECSU.C. Berkeley
Project supported by NSF ITR ANI-0326503 grant
DySPAN 2005, Nov. 10, 2005
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2Spectrum Sharing for Unlicensed Bands
Problem: Spectrum SharingCan multiple heterogeneous wireless systems coexist and
share spectrum in a fair and efficient manner?
•Unlicensed setting
•Equal rights
•Different goals
Introduction
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3Spectrum Sharing for Unlicensed Bands
Main Goals
• Find spectrum sharing rules that are:– Efficient– Fair– Robust against selfish behavior
• Study how to obtain good performance without
cooperation.
Introduction
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4Spectrum Sharing for Unlicensed Bands
The Model• Flat Fading• Systems use Gaussian signals with
PSD {pi(f)}.
• Power constraint for each system.
• Total bandwidth W.
• Interference treated as noise.
• Design choice: power allocations over frequency.
Introduction
C1,1
C2,2
C1,2
C2,1
N0
N0
noise interference
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5Spectrum Sharing for Unlicensed Bands
Static Gaussian Interference Game
• M Players: the M systems
• Strategy of system: power allocation satisfying power
constraint
• Utility of system i non-decreasing, concave on Ri.
• All parameters ({ci,j},{Pi},N0) are common knowledge.
• Players select their actions simultaneously.
Non-cooperative Scenarios
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6Spectrum Sharing for Unlicensed Bands
Static Game Analysis
Non-cooperative Scenarios
full spread Nash equilibrium
Achievable rates
proportional fair
orthogonal
Unique if
XXinterference
limited
noise limited
price of anarchy
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7Spectrum Sharing for Unlicensed Bands
Dynamic Game• What rate vectors are achievable as a N.E. in the dynamic game ?
Non-cooperative Scenarios
achievable with self enforcing strategies
Punishment strategies: encourage cooperation by threatening to spread
good behavior
punishment
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8Spectrum Sharing for Unlicensed Bands
Example A
Non-cooperative Scenarios
asymmetry in power and gains
802.11 bluetooth
full spread N.E.
proportional fair
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9Spectrum Sharing for Unlicensed Bands
Example B
Non-cooperative Scenarios
asymmetry in power
802.11
bluetooth
full spread N.E.
proportional fairQ: Can be achieved with other self enforcing strategies ?
No !
best PF self enforcing point
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10Spectrum Sharing for Unlicensed Bands
Asymmetry and Fairness
Non-cooperative Scenarios
No Loss
No Loss
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11Spectrum Sharing for Unlicensed Bands
Conclusions• With complete information and moderate asymmetry it is
possible to find policies that are fair, efficient and robust against selfish behavior.
• Results can be extended to:– Non-Gaussian signals– Any achievable rate region (with interference cancellation, etc.)
• Future research: – Find distributed algorithms that do not require complete
information and approximate the performance predicted here.– Investigate how to deal with cases of extreme asymmetry.
Conclusions
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12Spectrum Sharing for Unlicensed Bands
Related Work
• Distributed optimization of power spectral allocations for DSL using
iterative waterfilling [Cioffi, et al. 2001]
• Use of Game Theory to analyze outcomes of iterative waterfilling
algorithm [Cioffi, et al., 2002]
• Iterative waterfilling may lead to poor performance. Signal space
partitioning often leads to better results. [Popescu, Rose &
Popescu, 2004]
• Use of genetic algorithms to find good strategies in repeated games
with small strategy space. [Clemens & Rose, DySPAN 05]
Introduction