Collaborative autocorrelation-based spectrum sensing of OFDM signals in cognitive radios

A simple and efficient spectrum sensing scheme for Orthogonal Frequency Division Multiplexing (OFDM) signals of primary user in cognitive radio systems is proposed in this paper. A detector exploiting the well-known autocorrelation property of cyclic prefix (CP) based OFDM signals is developed. The proposed scheme is then extended to the case of many secondary users collaborating in order to detect the primary user in the face of shadowing and fading. The amount of information each user sends to other users or fusion center is constrained by censoring scheme where only informative decision statistics are sent. Censoring allows reducing the power consumption in battery operated mobile terminals. The statistical properties of the decision statistics are established. Limits on the censoring region are found under constraints on false-alarm and transmission rates. The distribution of the test statistics for cooperative detection with censoring is approximated using characteristic functions. The performance of the scheme is studied by simulations.