Research Article
Blind standard identification with bandwidth shape and GI recognition using USRP platforms and SDR4all tools
@INPROCEEDINGS{10.4108/ICST.CROWNCOM2010.9181, author={H. Wang and W. Jouini and A. Nafkha and J. Palicot and L. S. Cardoso and M. Debbah}, title={Blind standard identification with bandwidth shape and GI recognition using USRP platforms and SDR4all tools}, proceedings={5th International ICST Conference on Cognitive Radio Oriented Wireless Networks and Communications}, publisher={IEEE}, proceedings_a={CROWNCOM}, year={2010}, month={9}, keywords={Blind Standard Identification Sensor Cognitive Radio SDR4all Sensorial Radio Bubble USRP}, doi={10.4108/ICST.CROWNCOM2010.9181} }- H. Wang
W. Jouini
A. Nafkha
J. Palicot
L. S. Cardoso
M. Debbah
Year: 2010
Blind standard identification with bandwidth shape and GI recognition using USRP platforms and SDR4all tools
CROWNCOM
IEEE
DOI: 10.4108/ICST.CROWNCOM2010.9181
Abstract
In this paper, focusing on identifying standards blindly, we propose a bandwidth shape sensor and a GI (guard interval) sensor using USRP (Universal Software Radio Peripheral) platforms and SDR4all tools. These sensors are fundamental parts 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. We have presented first experience of using blind standard bandwidth sensor in a previous work. We will provide in this paper further details on the results of this sensor (simulations, preliminary implementations and validations). The GI sensor is implemented in order to improve the detection performance in the case of two identical bandwidth shapes. The SDR4all driver offers a simple yet efficient interface between the Matlab signal processing codes and the USRP transmitting and receiving platforms. These simple and easily accessible software defined radio tools were used to design and implement two sensors. The inducted simulations and experiments show that the designed system is indeed able to discriminate three standard-like spectrums (e.g., GSM-like, UMTS-like and OFDM-like) under simple yet real transmission conditions using their different bandwidth shapes and to identify a GI-OFDM-like system using cyclic autocorrelation method.
