Centralized Wideband Cooperative CRs Combined with PCA Anomaly Detector in the Presence of malicious Attacks

In this work, a centralized wideband cooperative compressive sampling (CWCCS) scheme based sub-Nyquist sampling technique combined with principal components analysis (PCA) anomaly patterns detection problem is presented. Anomaly detection problem is considered as a promising solution in the area of cognitive communications and networks-based threshold value. In the presence of jammer attacks and noise supposed Additive White Gaussian (AWGN). Two hypotheses: H
0
(means absence of jammers), and H
1
(means presence of jammers) are considered in this paper. The received primary wideband analog signal at each CR receiver transmitted by primary user (PU) is transformed in to a digital signal using an Analog-to-Information Converter (AIC) based on the sub-Nyquist sampling theory via centralized collaborative strategy and then all CR receiver give minimum number of samples denoted N
1
. All these compressed measurements from each CR are collected in the form of compressed sampling matrix which is considered directly as the input of PCA detector. The multivariate principal components analysis anomaly detector proposed in the level of Fusion Center (FC) is based on the characteristics of principal components. The simulation gives us good results in the presence of different jammers; in addition, we get low computation complexity, the consumption energy is reduced by each CR.