In this paper the analytical and simulation results of probability of detection\nand false alarm of a co-operative cognitive radio network are compared under\nboth awgn and Rayleigh fading environment. After getting the confidence\nlevel of above 95% from the simulation, a neural network (NN) is trained\nwith simulation data where the analytical result is given as the target of the\nNN. Finally the results are verified with the profile of MSE (mean square error)\nof three data set (train, validation and test), regression on data set, confusion\nmatrices and error histogram. Here we use Backpropagation algorithm\nand Hopfield model, all the results yield error of less than 4.5%. The concept\nof paper is applicable at fusion center (FC) to make proper judgment of\npresence of primary user (PU).
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