An improved cyclostationary feature detection based on the selection of optimal parameter in cognitive radios

Spectrum sensing is an important part of cognitive radio systems to find spectrum hole for transmission which enables cognitive radio systems coexist with the authorized radio systems without harmful interference. In this paper, an improved cyclostationary feature detection method is proposed to reduce computational complexity without loss of good performance based on the optimal parameter selection strategy for choosing detection parameters of cyclic frequency and lag. Taking binary phase shift keying (BPSK) and quadrature phase shift keying (QPSK) signals as examples, the theoretical analyses are presented for choosing the optimal parameters. Simulation results are given to certify the correctness of the proposed parameter selection strategy and show the performance of the proposed method.