MAC protocol classification in a cognitive radio network

Zhuo Yang, Yu Dong Yao, Sheng Chen, Haibo He, Di Zheng

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

22 Scopus citations

Abstract

Most media access control (MAC) protocols can be classified as contention based or controlled based according to their transmission mechanisms. To classify contention based or control based MAC protocols in an unknown primary network, we choose received power mean and variance as two features for support vector machines (SVMs) in a machine learning based algorithm. The data consisting of these two features are collected from two primary network models based on time division multiple access (control based) and slotted Aloha (contention based), respectively. In the training process, data along with their identification class labels (say, 1 denotes time division multiple access, and -1 stands for slotted Aloha) are used to train the SVMs. After training, contention or control based MAC protocols can be effectively determined by the trained SVMs embedded in a cognitive radio terminal of a secondary network.

Original languageEnglish
Title of host publicationWOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference
Subtitle of host publicationConverging Communications Around the Pacific
DOIs
StatePublished - 2010
Event19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific - Shanghai, China
Duration: 14 May 201015 May 2010

Publication series

NameWOCC2010 Technical Program - The 19th Annual Wireless and Optical Communications Conference: Converging Communications Around the Pacific

Conference

Conference19th Annual Wireless and Optical Communications Conference, WOCC2010: Converging Communications Around the Pacific
Country/TerritoryChina
CityShanghai
Period14/05/1015/05/10

Keywords

  • Capture effect
  • MAC protocol classification
  • Machine learning
  • Rayleigh fading

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