Cyclostationary feature based multiresolution spectrum sensing approach for DVB-T and wireless microphone signals

The demand for wireless communication has grown remarkably in the last year, consequently raising the problem of spectrum scarcity. In this context, cognitive radio is an emerging technology that aims to overcome that scarcity which is one of the most challenging problems in modern wireless communication. Among its fundamental function, the most important is the spectrum sensing which require precise accuracy and low complexity. Thus, various signal detection methods have been proposed for multiresolution spectrum sensing (MRSS). None of these techniques have been used in a wavelet based cyclostationary feature detector. To achieve that we suggest a cyclostationary feature based MRSS in the context of IEEE 802.22 Wireless Regional Area Network (WRAN) for cognitive radio to classify and identify the primary signal either Digital Video Broadcasting- Terrestrial (DVB-T) or wireless microphone signal. This knowledge of identifying primary signals can help cognitive radio to use fraction of TV band when only a wireless microphone signal is present in the channel. The performance of the proposed scheme is evaluated by probability of correct classification. The result indicates that better performance can be achieved by the proposed scheme especially in a low SNR environment.

[1]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

[2]  Qiwei Zhang,et al.  An efficient multi-resolution spectrum sensing method for cognitive radio , 2008, 2008 Third International Conference on Communications and Networking in China.

[3]  Joy Laskar,et al.  A wideband analog multi-resolution spectrum sensing (MRSS) technique for cognitive radio (CR) systems , 2006, 2006 IEEE International Symposium on Circuits and Systems.

[4]  Joseph Mitola,et al.  Cognitive radio: making software radios more personal , 1999, IEEE Wirel. Commun..

[5]  Michael J. Devaney,et al.  Power measurement using the wavelet transform , 1998, IEEE Trans. Instrum. Meas..

[6]  David J. Allstot,et al.  A Parallel, Multi-Resolution Sensing Technique for Multiple Antenna Cognitive Radios , 2007, 2007 IEEE International Symposium on Circuits and Systems.

[7]  R. WilliamA.GARDNE THE SPECTRAL CORRELATION THEORY OF CYCLOSTATIONARY TIME-SERIES , 2003 .

[8]  C. Cordeiro,et al.  IEEE 802.22: the first worldwide wireless standard based on cognitive radios , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..