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

A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems

Vol. 6, No. 9, September 25, 2012
10.3837/tiis.2012.09.012, Download Paper (Free):

Abstract

Traffic classification seeks to assign packet flows to an appropriate quality of service (QoS) class based on flow statistics without the need to examine packet payloads. Classification proceeds in two steps. Classification rules are first built by analyzing traffic traces, and then the classification rules are evaluated using test data. In this paper, we use self-organizing map and K-means clustering as unsupervised machine learning methods to identify the inherent classes in traffic traces. Three clusters were discovered, corresponding to transactional, bulk data transfer, and interactive applications. The K-nearest neighbor classifier was found to be highly accurate for the traffic data and significantly better compared to a minimum mean distance classifier.


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Cite this article

[IEEE Style]
D. hwan.Lim and B. Ho.Rhee, "A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems," KSII Transactions on Internet and Information Systems, vol. 6, no. 9, pp. 2191-2201, 2012. DOI: 10.3837/tiis.2012.09.012.

[ACM Style]
Dai hwan.Lim and Byung Ho.Rhee. 2012. A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems. KSII Transactions on Internet and Information Systems, 6, 9, (2012), 2191-2201. DOI: 10.3837/tiis.2012.09.012.

[BibTeX Style]
@article{tiis:20171, title="A Low Complexity PTS Technique using Threshold for PAPR Reduction in OFDM Systems", author="Dai hwan.Lim and Byung Ho.Rhee and ", journal="KSII Transactions on Internet and Information Systems", DOI={10.3837/tiis.2012.09.012}, volume={6}, number={9}, year="2012", month={September}, pages={2191-2201}}