Blind Spectrum Sensing for Cognitive Radio Channels with Noise Uncertainty

In this letter, a blind spectrum sensing method is proposed which does not need any information of primary users and the noise power. For a given number of observation samples of primary channels, the spectrum sensing is reformulated into a Student's t-distribution testing problem. The analytical results of the blind spectrum sensing are given. It is shown that over flat fading channels in noise of uncertainty power the blind spectrum sensing greatly outperforms the energy detection at about 4 dB gain.

[1]  M. Stephens.  EDF Statistics for Goodness of Fit and Some Comparisons , 1974 .

[2]  Mohamed-Slim Alouini,et al.  On the Energy Detection of Unknown Signals Over Fading Channels , 2007, IEEE Transactions on Communications.

[3]  A. Sonnenschein,et al.  Radiometric detection of spreadspectrum signals in noise of uncertain power , 1992 .

[4]  R. Tandra,et al.  Fundamental limits on detection in low SNR under noise uncertainty , 2005, 2005 International Conference on Wireless Networks, Communications and Mobile Computing.

[5]  Russell V. Lenth,et al.  Cumulative Distribution Function of the Noncentral T Distribution , 1989 .

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

[7]  H. Urkowitz.  Energy detection of unknown deterministic signals , 1967 .

[8]  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..

[9]  Jun Fang,et al.  Multiantenna-Assisted Spectrum Sensing for Cognitive Radio , 2010, IEEE Transactions on Vehicular Technology.

[10]  Wei Zhang,et al.  Anderson-Darling Sensing of Existence of Unknown Signals in a Fading Channel , 2009, 2009 5th International Conference on Wireless Communications, Networking and Mobile Computing.

[11]  Yonghong Zeng,et al.  A Review on Spectrum Sensing for Cognitive Radio: Challenges and Solutions , 2010, EURASIP J. Adv. Signal Process..

[12]  Yonghong Zeng,et al.  Multi-antenna based spectrum sensing for cognitive radios: A GLRT approach , 2010, IEEE Transactions on Communications.

[13]  Haiquan Wang,et al.  Spectrum sensing in cognitive radio using goodness of fit testing , 2009, IEEE Transactions on Wireless Communications.

[14]  W. G. Cochran,et al.  The distribution of quadratic forms in a normal system, with applications to the analysis of covariance , 1934, Mathematical Proceedings of the Cambridge Philosophical Society.

[15]  Hüseyin Arslan,et al.  A survey of spectrum sensing algorithms for cognitive radio applications , 2009, IEEE Communications Surveys & Tutorials.

[16]  K. B. Letaief,et al.  Optimization of cooperative spectrum sensing with energy detection in cognitive radio networks , 2009, IEEE Transactions on Wireless Communications.

[17]  Wei Zhang,et al.  Cooperative spectrum sensing with transmit and relay diversity in cognitive radio networks - [transaction letters] , 2008, IEEE Transactions on Wireless Communications.

[18]  T. W. Anderson,et al.  Asymptotic Theory of Certain "Goodness of Fit" Criteria Based on Stochastic Processes , 1952 .