Eigenvalue-based Cyclostationary Spectrum Sensing Using Multiple Antennas

摘要: In this paper, we propose a signal-selective spectrum sensing method for cognitive radio networks and specifically targeted receivers with multiple-antenna capability. This is used detecting the presence or absence of primary users based on eigenvalues cyclic covariance matrix received signals. particular, correlation significance test to detect specific signal-of-interest by exploiting knowledge its frequencies. The analytical threshold achieving constant false alarm rate using detection presented, verified through simulations, shown be independent both number samples noise variance, effectively eliminating dependence accurate estimation. proposed also shown, numerical outperform existing cyclostationary-based algorithms under quasi-static Rayleigh fading channel, in spatially correlated uncorrelated environments. algorithm has significantly lower computational complexity than these other approaches.