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The presence of the primary signal changes not only the signal energy but also the correlation structure, a new spectrum sensing algorithm based on the determinant of the sample covariance matrix is then introduced. The new algorithm utilizes the fact that the determinant of the sample covariance matrixes of received signals is different from that of noise samples with high probability to detect whether...
In this letter, a new blind sensing method based on the Cholesky factorization of the sample covariance matrix is presented for cognitive radios (CR). The proposed method overcomes the noise uncertainty problem of the energy detector (ED) and can also perform well without information about the channel, the primary signal and the noise power. Most importantly, unlike other detectors based on the sample...
The anisotropic deformation of nucleosome DNA during its bending into a superhelix implies that its constituent parts have different geometrical settings. In order to establish the relationship between the position and deformation characteristics, a nucleosome structural database is constructed and studied using principal component analysis to obtain the principal conformational subspace (PCS). For...
Energy detection based collaborative spectrum sensing algorithm is recently studied widely for primary signals detection in cognitive radio. However, one major disadvantage of those detectors is that their performance degrades in the presence of noise uncertainty which is inevitable in practical system. In this paper, we introduce a novel statistical covariance matrix based collaborative spectrum...
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