Adaptive Spectrum Sensing Algorithm Under Different Primary User Utilizations

Spectrum sensing is one of the key technologies to realize dynamic spectrum access in cognitive radio (CR) systems. In this letter, a novel adaptive threshold spectrum sensing algorithm is proposed to achieve an efficient trade-off between the detection and false alarm probability. The proposed adaptive threshold algorithm demonstrates a better spectrum efficiency for both primary users (PUs) and secondary users (SUs) in comparison with the conventional fixed one. A closed-from expression between PUs' spectrum utilization ratio and the proposed adaptive threshold is derived and simplified.

[1]  Ying-Chang Liang,et al.  Optimization for Cooperative Sensing in Cognitive Radio Networks , 2007, 2007 IEEE Wireless Communications and Networking Conference.

[2]  Erik G. Larsson,et al.  Spectrum sensing for cognitive radio : State-ofthe-art and recent advances , 2012 .

[3]  Yue Gao,et al.  Optimal Threshold of Welch's Periodogram for Sensing OFDM Signals at Low SNR Levels , 2013, EW.

[4]  Erik G. Larsson,et al.  Linköping University Post Print Optimal and Sub-optimal Spectrum Sensing of Ofdm Signals in Known and Unknown Noise Variance Optimal and Sub-optimal Spectrum Sensing of Ofdm Signals in Known and Unknown Noise Variance , 2022 .

[5]  Danijela Cabric,et al.  Experimental study of spectrum sensing based on energy detection and network cooperation , 2006, TAPAS '06.

[6]  Shibing Zhang,et al.  An Adaptive Spectrum Sensing Algorithm under Noise Uncertainty , 2011, 2011 IEEE International Conference on Communications (ICC).

[7]  Madjid Merabti,et al.  An improved energy detection scheme for cognitive radio networks in low SNR region , 2012, 2012 IEEE Symposium on Computers and Communications (ISCC).

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

[9]  Erik G. Larsson,et al.  Spectrum Sensing for Cognitive Radio : State-of-the-Art and Recent Advances , 2012, IEEE Signal Processing Magazine.

[10]  Maziar Nekovee Impact of Cognitive Radio on Future Management of Spectrum , 2008, 2008 3rd International Conference on Cognitive Radio Oriented Wireless Networks and Communications (CrownCom 2008).

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

[12]  Gokhan Memik,et al.  Energy Detection Using Estimated Noise Variance for Spectrum Sensing in Cognitive Radio Networks , 2008, 2008 IEEE Wireless Communications and Networking Conference.

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

[14]  Anant Sahai,et al.  Some Fundamental Limits on Cognitive Radio , 2004 .