Spectrum Sensing Using Principal Components for Multiple Antenna Cognitive Radios

This chapter presents an experimental comparative analysis of the well-known Covariance-Based Detection (CBD) techniques, which include Covariance Absolute Value (CAV), Maximum-Minimum Eigenvalue (MME), Energy with Minimum Eigenvalue (EME), and Maximum Eigenvalue Detection (MED). CBD techniques overcome the noise uncertainty issue of the Energy Detector (ED) and can even outperform ED in the case of correlated signals. They can perform accurate blind detection given sufficient number of signal samples. This chapter also presents a novel CBD algorithm that is based on Principal Component (PC) analysis. A Software-Defined Radio (SDR)-based multiple antenna system is used to evaluate the detection performance of the considered algorithms. The PC algorithm significantly outperforms the MED and EME algorithms and it also outperforms MME and CAV algorithms in certain cases.

[1]  R. Radhakrishnan,et al.  Simple Interference Cancellation Technique for Multicarrier DS-CDMA , 2007, Int. J. Bus. Data Commun. Netw..

[2]  Ying-Chang Liang,et al.  Covariance Based Signal Detections for Cognitive Radio , 2007, 2007 2nd IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks.

[3]  Mickaël Raulet,et al.  Classification of Dataflow Actors with Satisfiability and Abstract Interpretation , 2012, Int. J. Embed. Real Time Commun. Syst..

[4]  Debashis Saha,et al.  Web-Based Multimedia Advancements in Data Communications and Networking Technologies , 2012 .

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

[6]  Yonghong Zeng,et al.  Spectrum-Sensing Algorithms for Cognitive Radio Based on Statistical Covariances , 2008, IEEE Transactions on Vehicular Technology.

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

[8]  Leon Bieber.  Wireless Radio Frequency Standards And System Design Advanced Techniques , 2016 .

[9]  Samir Chatterjee,et al.  International Journal of Business Data Communications and Networking , 2010 .

[10]  John Soldatos,et al.  Open Source Object Directory Services for Inter-Enterprise Tracking and Tracing Applications , 2015 .

[11]  Alan Burns,et al.  Schedulability Analysis for Real Time On-Chip Communication with Wormhole Switching , 2010, Int. J. Embed. Real Time Commun. Syst..

[12]  M. Turk,et al.  Eigenfaces for Recognition , 1991, Journal of Cognitive Neuroscience.

[13]  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).

[14]  Ahmed El Oualkadi.  Sigma-Detla Fractional-N Phase-Locked Loop Design Using HDL and Transistor-Level Models for Wireless Communications , 2012 .

[15]  Donald A. Jackson.  STOPPING RULES IN PRINCIPAL COMPONENTS ANALYSIS: A COMPARISON OF HEURISTICAL AND STATISTICAL APPROACHES' , 1993 .

[16]  Alan D. Smith,et al.  Linking the Popularity of Online Trading with Consumers' Concerns for Reputation and Identity Theft , 2011, Int. J. Bus. Data Commun. Netw..

[17]  R. Cattell.  The Scree Test For The Number Of Factors. , 1966, Multivariate behavioral research.

[18]  Debashis Saha,et al.  Emerging Areas of Research in Business Data Communications , 2011, Int. J. Bus. Data Commun. Netw..

[19]  Stephen J. Shellhammer,et al.  Performance of power detector sensors of DTV signals in IEEE 802.22 WRANs , 2006, TAPAS '06.

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

[21]  Roberto Garello,et al.  Exact non-asymptotic threshold for eigenvalue-based spectrum sensing , 2009, 2009 4th International Conference on Cognitive Radio Oriented Wireless Networks and Communications.

[22]  H. Hotelling.  Analysis of a complex of statistical variables into principal components. , 1933 .

[23]  Kevin W. Sowerby,et al.  Spectrum sensing using principal component analysis , 2012, 2012 IEEE Wireless Communications and Networking Conference (WCNC).

[24]  Afifa Ghenai,et al.  Hybrid Simulation Based Approach for Embedded Systems Reliability Analysis , 2013, Int. J. Embed. Real Time Commun. Syst..

[25]  Yonghong Zeng,et al.  Maximum Eigenvalue Detection: Theory and Application , 2008, 2008 IEEE International Conference on Communications.

[26]  Yonghong Zeng,et al.  Robust spectrum sensing in cognitive radio , 2010, 2010 IEEE 21st International Symposium on Personal, Indoor and Mobile Radio Communications Workshops.

[27]  Srishti Shaw,et al.  Fuzzy Logic-based Mobility Metric Clustering Algorithm for MANETs , 2011, Int. J. Bus. Data Commun. Netw..

[28]  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.

[29]  Ecehan B. Pehlivanoglu,et al.  Sensing coverage and connectivity in cognitive radio sensor networks , 2014 .

[30]  Yonghong Zeng,et al.  Maximum-Minimum Eigenvalue Detection for Cognitive Radio , 2007, 2007 IEEE 18th International Symposium on Personal, Indoor and Mobile Radio Communications.

[31]  Yasir Faheem,et al.  Cognitive Radio Sensor Networks: Applications, Architectures, and Challenges , 2014 .

[32]  Tibor Dulai,et al.  Advanced Communication Protocol Technologies: Solutions, Methods, and Applications , 2011 .