whitespace measurement and virtual backbone construction for cognitive radio networks: from the...

Whitespace Measurement and Virtual Backbone Construction for Cognitive Radio

Networks: From the Social Perspective

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 HanGeorgia State University

S. Ji, Z. Cai, M. Han, and R. Beyah Whitespace Measurement and VB Construction

Introduction

Primary Users (PUs)

Secondary Users (SUs)


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


Outline

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


System Model• Primary 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



Centrality Score of PUs• Motivation: local and global activity behavior of PUs

• Centrality score of a PU Si

Expected # of active PUsThe betweenness centrality of Si: the number of

shortest paths passing Si

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 normalized weight of Si to be active

The weight of a PU on each shortest path 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



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



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


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

[email protected]

http://users.ece.gatech.edu/sji/

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