Performance Analysis of Spectrum Sensing for Mobile Cognitive Radio Networks

An overwhelming majority of the existing work on spectrum sensing assumes that secondary users (SUs) are stationary. However, mobility is an essential property of wireless networks. In this paper, we analyze the performance of spectrum sensing by mobile SUs. Four performance metrics, i.e. detection, miss detection, false alarm and error probabilities, are thoroughly investigated. A critical variable for spectrum sensing in mobile cognitive radio networks (CRNs) is the received primary user signal power (RPUP) by a mobile SU. We model this power mathematically, and then derive its probability distribution and mathematical expectation. At last, the expressions are derived for those four performance metrics. We perform extensive numerical simulations, finding out that the results are consistent with our theoretical analysis. It is concluded that the SU mobility has significant effects on the detection, miss detection and error probabilities, but dose not affect the false alarm probability.

[1]  Ian F. Akyildiz,et al.  Primary-user mobility impact on spectrum sensing in Cognitive Radio networks , 2011, 2011 IEEE 22nd International Symposium on Personal, Indoor and Mobile Radio Communications.

[2]  Yichen Wang,et al.  Delay and Throughput Oriented Continuous Spectrum Sensing Schemes in Cognitive Radio Networks , 2012, IEEE Transactions on Wireless Communications.

[3]  Chunsheng Xin,et al.  Performance analysis of spectrum sensing with mobile SUs in cognitive radio networks , 2014, 2014 IEEE International Conference on Communications (ICC).

[4]  Wei Cheng,et al.  Trusted Collaborative Spectrum Sensing for Mobile Cognitive Radio Networks , 2013, IEEE Trans. Inf. Forensics Secur..

[5]  Constantine A. Balanis,et al.  Antenna Theory: Analysis and Design , 1982 .

[6]  Dong-Ho Cho,et al.  Enhanced Spectrum Sensing Scheme in Cognitive Radio Systems With MIMO Antennae , 2011, IEEE Transactions on Vehicular Technology.

[7]  Baber Aslam,et al.  Reputation Aware Collaborative Spectrum Sensing for Mobile Cognitive Radio Networks , 2013, MILCOM 2013 - 2013 IEEE Military Communications Conference.

[8]  H. L. Dryden,et al.  Investigations on the Theory of the Brownian Movement , 1957 .

[9]  C. K. Michael Tse,et al.  Optimal quantisation bit budget for a spectrum sensing scheme in bandwidth-constrained cognitive sensor networks , 2011, IET Wirel. Sens. Syst..

[10]  Zhu Han,et al.  Collaborative Compressive Sensing Based Dynamic Spectrum Sensing and Mobile Primary User Localization in Cognitive Radio Networks , 2011, 2011 IEEE Global Telecommunications Conference - GLOBECOM 2011.

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

[12]  Kang G. Shin,et al.  Impact of mobility on spectrum sensing in cognitive radio networks , 2009, CoRoNet '09.

[13]  Ragnar Thobaben,et al.  Impact of mobility in cooperative spectrum sensing: Theory vs. simulation , 2012, 2012 International Symposium on Wireless Communication Systems (ISWCS).

[14]  Stefan Mangold,et al.  Cognitive Radio and Dynamic Spectrum Access , 2009 .

[15]  Prasant Mohapatra,et al.  Trusted collaborative spectrum sensing for mobile cognitive radio networks , 2012, 2012 Proceedings IEEE INFOCOM.

[16]  Xiuzhen Cheng,et al.  Dynamic spectrum access: from cognitive radio to network radio , 2012, IEEE Wireless Communications.

[17]  Konstantinos N. Plataniotis,et al.  Two-stage spectrum detection in cognitive radio networks , 2010, 2010 IEEE International Conference on Acoustics, Speech and Signal Processing.