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Dynamic Spectrum Leasing with User-determined Traffic Segmentation

Dynamic Spectrum Leasing with User-determined Traffic Segmentation. Xiaojun Feng , Qian Zhang Hong Kong University of Science and Technology IEEE ICC 2013. Outline. Background System Model and Problem Formulation Simulation Results Conclusions. Spectrum Scarcity and Underutilization.

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Dynamic Spectrum Leasing with User-determined Traffic Segmentation

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  1. Dynamic Spectrum Leasing with User-determined Traffic Segmentation XiaojunFeng, Qian Zhang Hong Kong University of Science and Technology IEEE ICC 2013

  2. Outline • Background • System Model and Problem Formulation • Simulation Results • Conclusions

  3. Spectrum Scarcity and Underutilization • We almost run out of Radio spectrum • Most spectrum is underutilized actually

  4. Spectrum Leasing • To increase spectrum utilization, the spectrum owners lease their unused band to secondary operators

  5. Business Model • For the spectrum owner • Make profit when leasing the unused spectrum • For the secondary operator • Deploy service on the leased band and also make money • Win-Win!

  6. Existing Works • [2] J. Zhang and Q. Zhang, “Stackelberg game for utility-based cooperative cognitive ratio networks,” in ACM MobiHoc, 2009. • [3] L. Duan, J. Huang, and B. Shou, “Cognitive mobile virtual mobile network operator: optimal investment and pricing with unreliable supply,” in IEEE INFOCOM, 2010. • [4] Y. Yi, J. Zhang, Q. Zhang, T. Jiang, “Spectrum Leasing to FemtoService Provider with Hybrid Access,” in IEEE INFOCOM, 2012.

  7. Our New Observations • Secondary service deployment with hybrid spectrum • Secondary operators can use both the leased spectrum and unlicensed band (e.g. WiFi, TV white space) to deploy service • Users can determine the traffic on different band • Users can decide which band to transmit traffic

  8. Serve with Hybrid Spectrum

  9. User-determined Traffic • When to transmit data, users can also determine which band they want to use

  10. Contributions • We are the first to consider user-determined traffic segmentation in spectrum leasing • We propose the optimal spectrum investment and pricing strategy for the secondary operator under this new scenario. • We derive optimal strategies for the spectrum owner and the end users via game theoretical analysis.

  11. Outline • Background • System Model and Problem Formulation • Simulation Results • Conclusions

  12. Scenario • One spectrum owner • Lease a total bandwidth of with price per MHz • One secondary operator • Buy spectrum of bandwidth • Charge the end users with per Mbps for the licensed band and for the unlicensed band • end users: • has a total traffic of MB to transmit • decides the ratio of the traffic transmitted on the licensed band

  13. Utility Functions • Spectrum owner • Secondary operator //leasing price // unlicensed band // licensed band

  14. Utility Functions • End user’s utility • : the QoS-aware user satisfaction from the traffic • More traffic on licensed band, higher satisfaction • : the price charged by the secondary operator

  15. Pricing Procedure

  16. Game Analysis • We leverage backward induction to derive the optimal strategies. • Stage IV: of each end user will be first derived • Stage III : The transmission price will be determined according to the users’ traffic segmentation choice • In Stage II: will be determined by the secondary operator to optimize its utility. • Stage I: The best leasing price is obtained based on the equilibrium of the sub-game

  17. Outline • Background • System Model and Problem Formulation • Simulation Results • Conclusions

  18. Impact of • Physical meaning of • With larger , the utility gain of the end users by transmitting traffic on the licensed band is higher • Setting • Fix MHz, , • Vary in the range of [1.1,3.0] • The total demand of the end users is in the range of [50, 300] Mbps

  19. Impact of

  20. Benefit of Spectrum Leasing • Spectrum owner, secondary operator can benefit from spectrum leasing • Setting • Fix • Vary in the range [0, 30]

  21. Benefit of Spectrum Leasing

  22. Outline • Background • System Model and Problem Formulation • Simulation Results • Conclusions

  23. Conclusions • It is the first work considering user-determined traffic segmentation in spectrum leasing scenario. • We model and derive optimal strategies of the spectrum owner, secondary operator and end users. • We show with both analysis and extensive simulations that the utility of both the secondary operator and the end users can be increased with the proposed framework and the spectrum owner can also make a profit.

  24. Thanks! Dynamic Spectrum Leasing with User-determined Traffic Segmentation XiaojunFeng xfeng@cse.ust.hk

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