Maximum Likelihood Ratio Spectrum Detection Model for Multicarrier Modulation Based Cognitive Radio Systems

In this paper, we first discuss multicarrier modulation (MCM) based cognitive radio (CR) systems. A maximum likelihood ratio spectrum detection model is then presented to detect the occurrence and spectrum gap of licensed users (LUs) signals. Next, we theoretically study the proposed model by deducing an optimal decision region and the detection probability and false alarm probability. Simulation results validate the derived performances of the proposed model for MCM based CR systems.

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

[2]  Ian F. Akyildiz,et al.  NeXt generation/dynamic spectrum access/cognitive radio wireless networks: A survey , 2006, Comput. Networks.

[3]  D. A. Chaturvedi.  Cooperative Spectrum Sensing for Cognitive Radio , 2008 .

[4]  J. Woods,et al.  Probability and Random Processes with Applications to Signal Processing , 2001 .

[5]  G. Ganesan,et al.  Cooperative spectrum sensing in cognitive radio networks , 2005, First IEEE International Symposium on New Frontiers in Dynamic Spectrum Access Networks, 2005. DySPAN 2005..

[6]  Mohamed-Slim Alouini,et al.  Detection of known and unknown signals, over fading channels , 2003, GLOBECOM '03. IEEE Global Telecommunications Conference (IEEE Cat. No.03CH37489).

[7]  Friedrich Jondral,et al.  Calculation of detection and false alarm probabilities in spectrum pooling systems , 2005, IEEE Communications Letters.

[8]  Zhou Xianwei,et al.  Cooperative Spectrum Sensing in Cognitive Radio Networks , 2008 .

[9]  Friedrich Jondral,et al.  Spectrum pooling: an innovative strategy for the enhancement of spectrum efficiency , 2004, IEEE Communications Magazine.