A New Cooperative Spectrum Sensing Algorithm Based on Double Threshold

S185 the traditional double-threshold spectrum sensing algorithm cannot take full advantage of the information of cognitive users, in the paper, we proposed an adaptive-step in turn combination cooperative spectrum sensing technique considering double-threshold. When the signal energy received by cognitive users falls into the mid-value of the two thresholds, our algorithm sends information to the fusion center rather than giving the judgement result directly. In accordance with the change of Signal-to-Noise Ratio received by cognitive users, the number of cognitive users can be adjusted automatically in order to decrease the system overhead in the cognitive radio network. Simulation result shows that the detection probability of our method is higher than the traditional double-threshold spectrum sensing algorithm. Moreover, the average data overhead to the fusion center is reduced compared to the traditional equal gain combining (EGC) cooperative spectrum sensing method.

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

[2]  R.W. Brodersen,et al.  Implementation issues in spectrum sensing for cognitive radios , 2004, Conference Record of the Thirty-Eighth Asilomar Conference on Signals, Systems and Computers, 2004..

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

[4]  Vladimir I. Kostylev,et al.  Energy detection of a signal with random amplitude , 2002, 2002 IEEE International Conference on Communications. Conference Proceedings. ICC 2002 (Cat. No.02CH37333).

[5]  Gongjun Yan,et al.  Spectrum Sensing in Cognitive Radio Networks , 2012 .

[6]  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.

[7]  Anant Sahai,et al.  Cooperative Sensing among Cognitive Radios , 2006, 2006 IEEE International Conference on Communications.

[8]  Linda Doyle,et al.  Cyclostationary Signatures in Practical Cognitive Radio Applications , 2008, IEEE Journal on Selected Areas in Communications.

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

[10]  Amir Ghasemi,et al.  Spectrum sensing in cognitive radio networks: requirements, challenges and design trade-offs , 2008, IEEE Communications Magazine.

[11]  A. Ghasemi,et al.  Collaborative spectrum sensing for opportunistic access in fading environments , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..