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Multi-cycle cyclostaionary spectrum sensing using canonical correlation analysis

Canonical correlation analysis is a powerful statistical tool to measure the relationship between two sets of variables. This paper proposes an algorithm that combines multi-cycle cyclostationary spectrum sensing technique and the canonical correlation analysis tool. The proposed algorithm can be applied to both multiple antenna systems and single antenna systems. The probability of detection of this algorithm is better than other cyclostationary algorithms that are based on canonical correlation analysis. Furthermore, the proposed algorithm has less computational complexity compared to the existing algorithms.