Verification analysis for the reliable analytical multi-taper detector in next generation network

Abstract

Multi-taper method (MTM) acts as an effective detector of spectrum sensing in Cognitive radio networks. In this paper, an analytical study was proposed in which reliable, simple, and computationally efficient mathematical terms for the mean and variance of the probability density function (PDF) were derived using the MTM technique. The closed-form expressions for the probability of detection and false alarm for the MTM detector were obtained accordingly. The proposed analytical study was evaluated by intensive simulations using MATLAB. Different simulation techniques were proposed to verify the derived analysis. The existence of White Gaussian Noise was assumed. Important aspects of spectrum detection in cognitive radio networks were included such as, receiver operating characteristics, detection rate versus signal to noise ratio (SNR), and the minimum desired sample points for a specific performance. A comparison was completed with the energy detection technique and all of the results suggested that the proposed paradigm is both credible and powerful under all the parameters considered in the simulation.

5G cognitive radio system design with new algorithm asynchronous spectrum sensing

“…The received signal crosses the threshold when there is only noise present and the error probability of the detector to detect a user when there isn't one is given by . The simulation result shows that at 0.1 the is 0.88666 for -10 dB SNR, for -15 dB SNR the is 0.42349 and for -20dB SNR the is 0.24957 for the same which meets our requirement compared with the result in [29].…”

“…Figure 3 shows the accuracy of the relation between and that was tested by evaluating the theoretical ROC energy detection curve for different SNR values. Based on [29] and using the same simulation parameters, the simulation results of the proposed algorithm for , and shows high and accurate compatibility with false alarm conditions and other system parameters. The detection is achieved by comparing the received signal r(t) to the threshold .…”