Real-time blind spectrum sensing using USRP

Srivastava, Saket, Hashmi, Mohammad, Das, Supratim and Barua, Dibakar (2015) Real-time blind spectrum sensing using USRP. In: Circuits and Systems (ISCAS), 2015 IEEE International Symposium on, 24 - 27 May 2015, Lisbon.

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Item Type:Conference or Workshop contribution (Paper)
Item Status:Live Archive


Efficient spectrum usage is an issue that has been inviting a lot of interest and research in recent times, due to the omnipresence of wireless technologies all around us. Spectrum sensing is a key step towards efficient spectrum usage. Energy detection is a fast and simple method for spectrum sensing, but the sensing precision is limited by the dependency on a threshold value. This paper reports a novel real time energy detection based spectrum sensing technique using a logistic regression classifier. The implementation is done using USRP and GNU-Radio, and achieves a classification accuracy of 98.6% on a dataset that was collected over commercial FM band.

Keywords:Cognitive radio, USRP, Software Defined Radio, GNU-radio, Spectrum sensing, logistic regression, Energy detection
Subjects:G Mathematical and Computer Sciences > G400 Computer Science
H Engineering > H690 Electronic and Electrical Engineering not elsewhere classified
H Engineering > H600 Electronic and Electrical Engineering
G Mathematical and Computer Sciences > G420 Networks and Communications
H Engineering > H640 Communications Engineering
H Engineering > H610 Electronic Engineering
Divisions:College of Science > School of Engineering
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ID Code:19212
Deposited On:23 Oct 2015 14:37

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