An F-Test Based Approach for Spectrum Sensing in Cognitive Radio

Spectrum sensing is a key task in cognitive radio networks. Traditional sensing techniques such as energy detector suffer from noise uncertainty problem or require high computational complexity. In this paper, we propose a novel sensing technique using F-test by considering a multiple antenna cognitive radio system. This method is insensitive to noise uncertainty and easy to implement. It requires the channel state information (CSI) as prior knowledge. Based on statistical properties of F-distribution, we shall derive the test threshold and probability of detection, respectively. In addition, the performance of the proposed approach under imperfect channel information will be discussed. Simulation results show that the proposed F-test based detector achieves significant performance improvement compared with several popular detectors and offers robustness against noise uncertainty.

[1]  Masoumeh Nasiri-Kenari,et al.  Multiple antenna spectrum sensing in cognitive radios , 2010, IEEE Transactions on Wireless Communications.

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

[3]  Caijun Zhong,et al.  Distribution of the Ratio of the Largest Eigenvalue to the Trace of Complex Wishart Matrices , 2012, IEEE Transactions on Signal Processing.

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

[5]  Jean-Paul M. G. Linnartz,et al.  Performance Analysis of Primary User Detection in a Multiple Antenna Cognitive Radio , 2007, 2007 IEEE International Conference on Communications.

[6]  Henk Wymeersch,et al.  Synchronization at low SNR : performance bounds and algorithms , 2004 .

[7]  Zhong Chen,et al.  Sensing orthogonal frequency division multiplexing systems for cognitive radio with cyclic prefix and pilot tones , 2012, IET Commun..

[8]  Yonghong Zeng,et al.  Eigenvalue-based spectrum sensing algorithms for cognitive radio , 2008, IEEE Transactions on Communications.

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

[10]  R.W. Brodersen,et al.  Spectrum Sensing Measurements of Pilot, Energy, and Collaborative Detection , 2006, MILCOM 2006 - 2006 IEEE Military Communications conference.

[11]  Robert H. Shumway,et al.  Replicated time-series regression: An approach to signal estimation and detection , 1983 .

[12]  Yonghong Zeng,et al.  GLRT-Based Spectrum Sensing for Cognitive Radio , 2008, IEEE GLOBECOM 2008 - 2008 IEEE Global Telecommunications Conference.

[13]  Simon Haykin,et al.  Spectrum Sensing for Cognitive Radio , 2009, Proceedings of the IEEE.

[14]  Abbas Jamalipour,et al.  Wireless communications , 2005, GLOBECOM '05. IEEE Global Telecommunications Conference, 2005..

[15]  H. Vincent Poor,et al.  Autocorrelation-Based Decentralized Sequential Detection of OFDM Signals in Cognitive Radios , 2009, IEEE Transactions on Signal Processing.

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

[17]  Alan J. Lee,et al.  Linear Regression Analysis: Seber/Linear , 2003 .

[18]  Geoffrey Ye Li,et al.  Soft Combination and Detection for Cooperative Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE GLOBECOM 2007 - IEEE Global Telecommunications Conference.

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

[20]  Pascal Bianchi,et al.  Performance of Statistical Tests for Single-Source Detection Using Random Matrix Theory , 2009, IEEE Transactions on Information Theory.

[21]  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.

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

[23]  Hai Lin,et al.  Low SNR Timing and Frequency Synchronization for PIP-OFDM System , 2010, 2010 IEEE 71st Vehicular Technology Conference.

[24]  Norman C. Beaulieu,et al.  Optimal Wideband Spectrum Sensing Framework for Cognitive Radio Systems , 2011, IEEE Transactions on Signal Processing.

[25]  Ronald W. Butler,et al.  Calculating the density and distribution function for the singly and doubly noncentral F , 2002, Stat. Comput..

[26]  Caijun Zhong,et al.  On the Performance of Eigenvalue-Based Spectrum Sensing for Cognitive Radio , 2010, 2010 IEEE Symposium on New Frontiers in Dynamic Spectrum (DySPAN).

[27]  N. L. Johnson,et al.  Continuous Univariate Distributions. , 1995 .

[28]  Brian M. Sadler,et al.  Pilot-assisted wireless transmissions: general model, design criteria, and signal processing , 2004, IEEE Signal Processing Magazine.

[29]  H. Vincent Poor,et al.  Optimal Multiband Joint Detection for Spectrum Sensing in Cognitive Radio Networks , 2008, IEEE Transactions on Signal Processing.