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Wireless standard classification in cognitive radio networks using self-organizing maps

Research output: Chapter in Book/Report/Conference proceedingConference paper

Original languageEnglish
Title of host publicationProceedings of the International Symposium on Wireless Communication Systems
PublisherIEEE Computer Society Press
Pages115-119
Number of pages5
ISBN (Print)9783800735297
Publication statusPublished - 2013
Event10th IEEE International Symposium on Wireless Communication Systems 2013, ISWCS 2013 - Ilmenau, Germany
Duration: 27 Aug 201330 Aug 2013

Conference

Conference10th IEEE International Symposium on Wireless Communication Systems 2013, ISWCS 2013
CountryGermany
CityIlmenau
Period27/08/201330/08/2013

King's Authors

Abstract

Radio access technology (RAT) recognition can be an important technique to facilitate spectrum sharing, interference avoidance, and cooperation among cognitive radios. As one example among its very many possible uses and benefits, RAT recognition might allow Secondary Users (SUs) to differentiate between the transmissions of Primary Users (PUs) and other SUs, such that SUs might contend for a spectrum band fairly, only not transmitting when they detect the PUs as having started to transmit in the same band. In this work, a practical testbed made up of software defined radio transceivers and computing units has been assembled, and used to transmit and receive extensive samples of representative RATs. A Self-Organizing Map (SOM) with Support Vector Machine (SVM) clustering and classification technique has been developed via a semi-supervised learning, to operate on these received samples. Finally, performance metrics have been presented showing almost 100% classification performance at -20dB Signal-to-Noise Ratio (SNR). This demonstrates the efficiency of this technique.

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