Performance of Blind Cooperative Spectrum Sensing under Nonuniform Signal and Noise Powers

This paper addresses the performance, the reporting channel traffic and the computational complexity of two blind centralized cooperative spectrum sensing schemes under the effect of unequal noise and received signal powers. The first one is the generalized likelihood ratio test with decision fusion, and with weighted and non-weighted data fusion of samples and eigenvalues. The second scheme is the circular folding cooperative power spectral density split cancellation method with data fusion. A total of eight techniques arose from variations of these two in terms of the different fusion and combining rules. It is demonstrated that different configurations of the system parameters may influence the above three metrics in different extents, meaning that none of the techniques is capable of overcoming the others in all metrics simultaneously. This indicates that the choice of the most suitable technique must be carefully made to match the specific scenario to which the technique is intended to be applied. The results presented in this paper serve as guidelines for assisting this choice.

[1]  Lamiaa Khalid,et al.  Reliability-based decision fusion scheme for cooperative spectrum sensing , 2014, IET Commun..

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

[3]  Thomas Kailath,et al.  Detection of signals by information theoretic criteria , 1985, IEEE Trans. Acoust. Speech Signal Process..

[4]  Caijun Zhong,et al.  On the Performance of Eigenvalue-Based Cooperative Spectrum Sensing for Cognitive Radio , 2011, IEEE Journal of Selected Topics in Signal Processing.

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

[6]  Dayan A. Guimarães,et al.  Cooperative Spectrum Sensing Using Eigenvalue Fusion for OFDMA and Other Wideband Signals , 2013, J. Sens. Actuator Networks.

[7]  Georgios B. Giannakis,et al.  Compressed Sensing for Wideband Cognitive Radios , 2007, 2007 IEEE International Conference on Acoustics, Speech and Signal Processing - ICASSP '07.

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

[10]  Tamer Khattab,et al.  Eigenvalue-Based Multiple Antenna Spectrum Sensing: Higher Order Moments , 2017, IEEE Transactions on Wireless Communications.

[11]  Dayan Adionel Guimarães.  Digital Transmission: A Simulation-Aided Introduction with VisSim/Comm , 2010 .

[12]  Myungsik Yoo,et al.  An Effective MIMO-OFDM Transmission Scheme for IEEE 802.22 WRAN Systems , 2007, 2007 2nd International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[13]  Dan McCloskey,et al.  Chicago spectrum occupancy measurements & analysis and a long-term studies proposal , 2006, TAPAS '06.

[14]  Dayan A. Guimarães,et al.  On the Probability of False Alarm of the Power Spectral Density Split Cancellation Method , 2016, IEEE Wireless Communications Letters.

[15]  Tamer Khattab,et al.  Correlated Multiple Antennas Spectrum Sensing Under Calibration Uncertainty , 2015, IEEE Transactions on Wireless Communications.

[16]  Roberto Garello,et al.  Performance of Eigenvalue-Based Signal Detectors with Known and Unknown Noise Level , 2011, 2011 IEEE International Conference on Communications (ICC).

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

[18]  Julius O. Smith,et al.  Introduction to Digital Filters: with Audio Applications , 2007 .

[19]  Dayan A. Guimarães,et al.  Performance-traffic tradeoff in eigenvalue fusion and decision fusion for spectrum sensing of OFDMA signals under errors in the reporting channel , 2016, Telecommun. Syst..

[20]  Rudolf Mathar,et al.  Performance limits of cooperative eigenvalue-based spectrum sensing under noise calibration uncertainty , 2016, 2016 Eighth International Conference on Ubiquitous and Future Networks (ICUFN).

[21]  Sachin Chaudhari,et al.  BEP walls for cooperative Bayesian detection with reporting channel errors , 2012, 2012 IEEE 23rd International Symposium on Personal, Indoor and Mobile Radio Communications - (PIMRC).

[22]  Zhe Chen,et al.  A Unified Multi-Functional Dynamic Spectrum Access Framework: Tutorial, Theory and Multi-GHz Wideband Testbed , 2009, Sensors.

[23]  H. Vincent Poor,et al.  BEP walls for cooperative sensing in cognitive radios using K-out-of-N fusion rules , 2013, Signal Process..

[24]  Sachin Chaudhari,et al.  On the BEP walls for soft decision based cooperative sensing in cognitive radios , 2013, 2013 IEEE International Conference on Communications (ICC).

[25]  William A. Gardner,et al.  Signal interception: a unifying theoretical framework for feature detection , 1988, IEEE Trans. Commun..

[26]  Ranjan K. Mallik,et al.  Cooperative Spectrum Sensing in Multiple Antenna Based Cognitive Radio Network Using an Improved Energy Detector , 2012, IEEE Communications Letters.

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

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

[29]  Zan Li,et al.  A Robust Cooperative Spectrum Sensing Method in Cognitive Radio Networks , 2014, IEEE Communications Letters.

[30]  Haiming Wang,et al.  Eigenvalues based spectrum sensing against untrusted users in cognitive radio networks , 2009, 2009 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[31]  Lei Huang,et al.  Gerschgorin disk-based robust spectrum sensing for cognitive radio , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[32]  Roberto López-Valcarce,et al.  Detection of Rank- $P$ Signals in Cognitive Radio Networks With Uncalibrated Multiple Antennas , 2011, IEEE Transactions on Signal Processing.

[33]  Ian F. Akyildiz,et al.  Cooperative spectrum sensing in cognitive radio networks: A survey , 2011, Phys. Commun..

[34]  Sachin Chaudhari,et al.  BEP walls for collaborative spectrum sensing , 2011, 2011 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).

[35]  Georgios B. Giannakis,et al.  A Wavelet Approach to Wideband Spectrum Sensing for Cognitive Radios , 2006, 2006 1st International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[36]  Dayan Adionel Guimaraes,et al.  Comparison between eigenvalue fusion and decision fusion for spectrum sensing of OFDMA signals under errors in the control channel , 2014, 2014 International Telecommunications Symposium (ITS).

[37]  Zan Li,et al.  Maximum-Eigenvalue-Based Sensing and Power Recognition for Multiantenna Cognitive Radio System , 2016, IEEE Transactions on Vehicular Technology.

[38]  Dayan A. Guimarães,et al.  Circular Folding Cooperative Power Spectral Density Split Cancellation Algorithm for Spectrum Sensing , 2017, IEEE Communications Letters.

[39]  Lucas dos Santos Costa,et al.  Performance and Reporting Channel Traffic of Eigenvalue Fusion and Block-coded Decision Fusion for Spectrum Sensing of OFDMA Signals , 2016 .

[40]  Hai Jiang,et al.  Energy Detection Based Cooperative Spectrum Sensing in Cognitive Radio Networks , 2011, IEEE Transactions on Wireless Communications.

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