Cooperative Spectrum Sensing Algorithm Based on Double Eigenvalue Limiting Distribution

Abstract

A spectrum sensing algorithm using double eigenvalue limiting（DEL）distributions was presented. The difference between the maximum and the minimum eigenvalue was exploited as the test statistic. The double eigenvalue were used to estimate a threshold based on the double eigenvalue limiting distributions to heighten an accuracy of the threshold. Compared with the algorithm of single eigenvalue, the theoretical analyses demonstrate that the threshold estimated by DEL was less than its threshold and the performance of DEL was improved. In addition, simulations results show the proposed algorithm needs neither the prior acknowledge of the signal transmitted from primary user, nor the noise power in advance, and gains better performance against the short of sampling number than the difference between the maximum and the minimum eigenvalue（DMM）algorithm.

Keywords

• spectrum sensing;random matrix theory;double eigenvalue limiting distribution;threshold estimation