基于Wishart矩阵特征值的频谱感知算法

doi:10.11959/j.issn.1000-0801.2017255

Abstract

Abstract:

In order to improve the spectrum sensing performance and overcome the shortcomings of the classical algorithm,a new cooperative spectrum sensing algorithm based on Wishart random matrix theory was proposed.According to the logarithmic distribution characteristics of the sampled covariance matrix eigenvalues and using the ratio of maximum eigenvalue and geometric mean eigenvalue,a simple closed-form threshold expression could be obtained,and the spectrum sensing decision could be performed depend on the threshold.The simulation results show that the proposed algorithm can get better sensing performance even under the conditions of a few number of cooperative users,low signal to noise ratio and a few samples.It is less affected by false-alarm probability and the extreme values,and has better detection performance than similar algorithms.

Key words: spectrum sensing, Wishart random matrix, sample covariance matrix, geometric mean eigenvalue

CLC Number:

TN925

Xuemei YANG,Xi HE,Jiapin XU. Spectrum sensing algorithm based on the eigenvalue of Wishart random matrix[J]. Telecommunications Science, 2017, 33(9): 69-75.

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References 17

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M	N	SNR/dB	P_d
5	100	-6	0.94
5	200	-8	0.92
5	500	-10	0.94
10	100	-9	0.96
10	200	-11	0.94
10	500	-13	0.96

算法	Δ (正值偏差)
MGME	0.025
AME	0.032
DSCM	0.123
AMME	0.178
LED	0.573

Spectrum sensing algorithm based on the eigenvalue of Wishart random matrix

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