1. Whitespace Measurement and Virtual Backbone Construction for Cognitive Radio Networks: From the Social Perspective Shouling Ji and Raheem Beyah Georgia Institute of Technology Zhipeng Cai and Meng Han Georgia State University

2. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Introduction Primary Users (PUs) Secondary Users (SUs)

3. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Introduction Problem –Systematically analyze the spectrum whitespace in CRNs from a social network perspective Contribution –Propose a novel metric named centrality score to measure the active weights of PUs by considering each PU’s topological importance and the global primary network running and traffic information –Analyzed the whitespace for SUs under three primary activity social patterns: i.i.d. distribution, Poisson distribution, and Gaussian distribution –Propose a Spectrum Altitudes based Virtual Backbone (SAVB) construction algorithm

4. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

5. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction System Model Primary Network –N Poisson distributed PUs with density of λ p –Transmission and interference radii: R and R I –The network time is slotted with each time slot of length τ –The licensed spectrum bandwidth W –The primary network is dense scaling Secondary Network –n randomly deployed SUs –Transmission and interference radii: r and r I –The secondary network is connected and dense scaling

6. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

7. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Centrality Score of PUs Motivation: local and global activity behavior of PUs Centrality score of a PU S i Expected # of active PUs The betweenness centrality of S i : the number of shortest paths passing S i The # of shortest paths in the primary networkThe average # of PUs on shortest paths

8. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Centrality Score of PUs Centrality score of a PU S i The average # of active PUs on each shortest path The normalized weight of S i to be active The weight of a PU on each shortest path to be active

9. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Social Activity Pattern of PUs By recent empirical studies –i.i.d. activity pattern –Poisson distribution pattern, e.g., the GSM90 uplink service –Gaussian distribution pattern, e.g., cell phone users, cellular network users, mobile device holders, WiFi users

10. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Whitespace Analysis i.i.d. activity –The lower and upper bounds of the centrality score of PU S i –The lower and upper bounds of the active probability of PU S i –The lower and upper bounds of the available spectrum whitespace for a secondary link

11. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Whitespace Analysis Poisson distributed pattern Gaussian distributed pattern

12. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

13. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Virtual Backbone (VB) Construction Definition of VB –A VB B of the secondary network is a subset of SUs such that (i) every SU is either in B or has some neighbor in B; and (ii) B is connected. Objective –Seek a VB with small size –Seek a VB with more spectrum bandwidth available Spectrum altitude –Measures the average available whitespace at SU s u –A high implies s u has more neighbors and high available spectrum whitespace to its neighbors on average

14. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Virtual Backbone (VB) Construction Seek a Maximal Independent Set (MIS) M of the secondary network Final a minimal set C of connectors to connect the independent nodes in M

15. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Virtual Backbone (VB) Construction Correctness analysis of SAVB Performance analysis of SAVB

16. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

17. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Simulation Settings –Time is slotted with each time slot is normalized to one –The primary bandwidth is normalized to 100 –Examine the unicast throughput under different primary activity distributions Comparison –US (Journal of Combinatorial Optimization, 2013): a VB is first constructed on top of a cell-based network partition; then, the unicast is carried out on the VB

18. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Simulation Whitespace estimation Successful delivery ratio

19. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Conclusion –We provide a mathematical framework for deriving the whitespace for SUs With local and global primary activity consideration With typical primary social patterns consideration –Propose a spectrum altitude based virtual backbone construction algorithm

20. S. Ji, Z. Cai, M. Han, and R. BeyahWhitespace Measurement and VB Construction Thank you! Shouling Ji sji@gatech.edu http://users.ece.gatech.edu/sji/