Spectrum Sharing for Unlicensed Bands Raul Etkin, Abhay Parekh, and David Tse Dept of EECS U.C. Berkeley Project supported by NSF ITR ANI grant DySPAN 2005, Nov. 10, 2005

Spectrum Sharing for Unlicensed Bands 1 Problem: Spectrum Sharing Can multiple heterogeneous wireless systems coexist and share spectrum in a fair and efficient manner? Unlicensed setting Equal rights Different goals Introduction

Spectrum Sharing for Unlicensed Bands 2 Main Goals Find spectrum sharing rules that are: –Efficient –Fair –Robust against selfish behavior Study how to obtain good performance without cooperation. Introduction

Spectrum Sharing for Unlicensed Bands 3 The Model Flat Fading Systems use Gaussian signals with PSD {p i (f)}. Power constraint for each system. Total bandwidth W. Interference treated as noise. Design choice: power allocations over frequency. Introduction C 1,1 C 2,2 C 1,2 C 2,1 N0N0 N0N0 noiseinterference

Spectrum Sharing for Unlicensed Bands 4 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 R i. All parameters ({c i,j },{P i },N 0 ) are common knowledge. Players select their actions simultaneously. Non-cooperative Scenarios

Spectrum Sharing for Unlicensed Bands 5 Static Game Analysis Non-cooperative Scenarios full spread Nash equilibrium Achievable rates proportional fair orthogonal Unique if X Xinterference limited noise limited price of anarchy

Spectrum Sharing for Unlicensed Bands 6 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

Spectrum Sharing for Unlicensed Bands 7 Example A Non-cooperative Scenarios asymmetry in power and gains bluetooth full spread N.E. proportional fair

Spectrum Sharing for Unlicensed Bands 8 Example B Non-cooperative Scenarios asymmetry in power bluetooth full spread N.E. proportional fair Q: Can be achieved with other self enforcing strategies ? No ! best PF self enforcing point

Spectrum Sharing for Unlicensed Bands 9 Asymmetry and Fairness Non-cooperative Scenarios No Loss

Spectrum Sharing for Unlicensed Bands 10 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

Spectrum Sharing for Unlicensed Bands 11 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