Introduction Secondary Users (SUs) Primary Users (PUs)

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Presentation transcript:

Introduction Secondary Users (SUs) Primary Users (PUs)

Introduction Problem Contribution 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

Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

System Model Primary Network Secondary Network N Poisson distributed PUs with density of λp Transmission and interference radii: R and RI 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 rI The secondary network is connected and dense scaling

Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

Centrality Score of PUs Motivation: local and global activity behavior of PUs Centrality score of a PU Si The betweenness centrality of Si: the number of shortest paths passing Si Expected # of active PUs The # of shortest paths in the primary network The average # of PUs on shortest paths

Centrality Score of PUs Centrality score of a PU Si The average # of active PUs on each shortest path The weight of a PU on each shortest path to be active The normalized weight of Si to be active

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

Whitespace Analysis i.i.d. activity The lower and upper bounds of the centrality score of PU Si The lower and upper bounds of the active probability of PU Si The lower and upper bounds of the available spectrum whitespace for a secondary link

Whitespace Analysis Poisson distributed pattern Gaussian distributed pattern

Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

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 su A high implies su has more neighbors and high available spectrum whitespace to its neighbors on average

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

Virtual Backbone (VB) Construction Correctness analysis of SAVB Performance analysis of SAVB

Outline Introduction System Model PUs’ Social Attributes and Whitespace Analysis Virtual Backbone (VB) construction Simulation Conclusion

Simulation Settings Comparison 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

Simulation Whitespace estimation Successful delivery ratio

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

Thank you! Shouling Ji sji@gatech.edu http://users.ece.gatech.edu/sji/