SPECTRUM SENSING IN COGNITIVE RADIO NETWORKS WITH KERNEL LEAST MEAN SQUARE

   This project is designed based on the paper "Cooperative Spectrum Sensing in Cognitive Radio Networks with Kernel Least Mean Square".Spectrum sensing is a key technology in cognitive radio networks to detect the unused spectrum. Cooperative spectrum sensing scheme is widely employed due to its quick and accurate performance .This design use the same scheme in the reference paper but for different adaptive filter as listed below.
A.    KLMS
B.    LMS
C.    NLMS
D.    RLS
E.    KRLS
F.    KalmanFilter

Simulation results based on Learning curves, Probability of detection for (KLMS, NLMS, LMS, RLS, KRLS, Kalman,) and three other decision fusion methods: AND, OR, and Majority Rules.Finally Probability of Detection for different users SNR and user numbers.

Reference Paper-1: Cooperative Spectrum Sensing in Cognitive Radio Networks with Kernel Least Mean Square

Author’s Name: Xiguang Xu, Hua Qu, Jihong Zhao and Badong Chen

Source: IEEE -5th International Conference on Information Science and Technology (ICIST)

Year:2015

Reference Paper-2: A Novel Adaptive Fusion Scheme For Cooperative Spectrum Sensing

Author’s Name: Imen NASR and Sofiane CHERIF

Source: 2012 IEEE Vehicular Technology Conference (VTC Fall)

Year:2012

Request design files for academic purpose,contact sales@verilogcourseteam.com.

SIMULATION VIDEO DEMO                                                                                                                                     


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