DocumentCode
2715760
Title
Blind Bandwidth Shape Recognition for Standard Identification Using USRP Platforms and SDR4all Tools
Author
Wang, H. ; Jouini, W. ; Hachemani, R. ; Palicot, J. ; Cardoso, L.S. ; Debbah, M.
Author_Institution
SUPELEC, Cesson-Sevigne, France
fYear
2010
fDate
9-15 May 2010
Firstpage
147
Lastpage
152
Abstract
In this paper a blind standard bandwidth shape sensor is implemented on a USRP (Universal Software Radio Peripheral) platform using SDR4all tools. This sensor is a fundamental part of the so-called Blind Standard Recognition Sensor. The blind standard bandwidth sensor is based on a Radial Basis Function Neuronal Network designed in Matlab. The SDR4all driver offers a simple yet efficient interface between the Matlab signal processing codes and the USRP transmitting and receiving platforms. To the best of our knowledge, it is the first time that simple and easily accessible software defined radio tools were used to design and implement this sensor. Although the experiments were realized under line-of-sight transmission conditions the results show that the designed system is indeed able to discriminate several standard-like spectrums under real transmission conditions using their different bandwidth shapes.
Keywords
cognitive radio; image sensors; radial basis function networks; shape recognition; signal processing; software radio; SDR4all tools; USRP platforms; blind bandwidth shape recognition; cognitive radio; radial basis function neuronal network; signal processing; standard identification; universal software radio peripheral; Bandwidth; Biological neural networks; Chromium; Cognitive radio; Shape; Signal analysis; Signal processing; Software radio; Software standards; Telecommunication standards; Blind Standard Identification Sensor; Cognitive Radio; SDR4all; Sensorial Cognitive Radio Bubble; USRP; Universal Software Defined Peripheral;
fLanguage
English
Publisher
ieee
Conference_Titel
Telecommunications (AICT), 2010 Sixth Advanced International Conference on
Conference_Location
Barcelona
Print_ISBN
978-1-4244-6748-8
Type
conf
DOI
10.1109/AICT.2010.41
Filename
5489864
Link To Document