Energy Detection Based Spectrum Sensing for Cognitive Radios in Noise of Uncertain Power

Energy detection based spectrum sensing has been proposed and studied widely for primary user (PU) signal detection in the literature. With the help of multiple secondary users (SU) in the cognitive radio network, various cooperative sensing schemes are investigated to enhance the energy detection performance. However, the impacts of noise power fluctuating effects on the detection performance in multipath fading and user cooperative sensing scenarios are seldom evaluated in relevant literature. In this paper, a modified version of the classic energy detection model is presented, where the noise power uncertainty (U) is introduced into threshold setting. With a reasonable approximate derivation, we provide accurate predictions of SNRwall constraints imposed by U in Rayleigh fading environments. In addition, by employing a simple hard decision fusion rule, the collaborative gain in spectrum sensing performance is also quantified with respect to U. Our analysis and numerical results confirm that collaboration can significantly improve the spectrum sensing performance in a noise power fluctuating environment.

[1]  R. Viswanathan,et al.  Distributed detection of a signal in generalized Gaussian noise , 1989, IEEE Trans. Acoust. Speech Signal Process..

[2]  Amir Ghasemi,et al.  Impact of User Collaboration on the Performance of Sensing-Based Opportunistic Spectrum Access , 2006, IEEE Vehicular Technology Conference.

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

[4]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[5]  Ramanarayanan Viswanathan,et al.  Asymptotic performance of a distributed detection system in correlated Gaussian noise , 1992, IEEE Trans. Signal Process..

[6]  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.

[7]  Brian M. Sadler,et al.  A Survey of Dynamic Spectrum Access , 2007, IEEE Signal Processing Magazine.

[8]  Simon Haykin,et al.  Cognitive radio: brain-empowered wireless communications , 2005, IEEE Journal on Selected Areas in Communications.

[9]  Wenwu Cao,et al.  Applied Numerical Methods Using MATLAB®: Yang/Applied Numerical MATLAB , 2005 .

[10]  Ranjan K. Mallik,et al.  Cooperative Spectrum Sensing Optimization in Cognitive Radio Networks , 2008, 2008 IEEE International Conference on Communications.

[11]  Mohamed-Slim Alouini,et al.  On the energy detection of unknown signals over fading channels , 2003, IEEE International Conference on Communications, 2003. ICC '03..

[12]  R.F. Mills,et al.  A comparison of various radiometer detection models , 1996, IEEE Transactions on Aerospace and Electronic Systems.

[13]  Shuguang Cui,et al.  Optimal Linear Cooperation for Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE Journal of Selected Topics in Signal Processing.

[14]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[15]  H. Saarnisaari,et al.  Spectrum Sensingwith Forward Methods , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.