• KSII Transactions on Internet and Information Systems
    Monthly Online Journal (eISSN: 1976-7277)

Polygon Approximation Based Cognitive Information Delivery in Geo-location Database Oriented Spectrum Sharing

Vol. 11, No. 6, June 29, 2017
10.3837/tiis.2017.06.007, Download Paper (Free):

Abstract

In geo-location database oriented spectrum sharing system, the entire geographic area is divided into meshes to classify, store and delivery the cognitive information. In this paper, we propose a flexible polygon mesh division scheme to reduce the number of meshes. Hence the cognitive information can be reduced correspondingly. Besides, polygon mesh can approximate the real environment and reduce the error of cognitive information because the edges of polygon are selected along the boundaries of the networks. We have designed the polygon approximation algorithm and have analyzed the relation between the error and the number of polygon’s edges. Finally, the simulation results are provided to verify the algorithm and analysis. The polygon mesh division scheme in this paper provides an efficient approach for cognitive information organization in database oriented spectrum sharing system.


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Cite this article

[IEEE Style]
Z. Wei, H. Wu, Z. Feng, "Polygon Approximation Based Cognitive Information Delivery in Geo-location Database Oriented Spectrum Sharing," KSII Transactions on Internet and Information Systems, vol. 11, no. 6, pp. 2926-2945, 2017. DOI: 10.3837/tiis.2017.06.007.

[ACM Style]
Zhiqing Wei, Huici Wu, and Zhiyong Feng. 2017. Polygon Approximation Based Cognitive Information Delivery in Geo-location Database Oriented Spectrum Sharing. KSII Transactions on Internet and Information Systems, 11, 6, (2017), 2926-2945. DOI: 10.3837/tiis.2017.06.007.

[BibTeX Style]
@article{tiis:21472, title="Polygon Approximation Based Cognitive Information Delivery in Geo-location Database Oriented Spectrum Sharing", author="Zhiqing Wei and Huici Wu and Zhiyong Feng and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2017.06.007}, volume={11}, number={6}, year="2017", month={June}, pages={2926-2945}}