Exploiting multiple antennas for spectrum sensing in cognitive radio networks

Abstract

Spectrum sensing in wireless communications is provided to identify utilized and/or unutilized frequency bands reserved for primary users using a cyclostationary beamforming approach. An adaptive cross self-coherent restoral (ACS) algorithm can be utilized to extract signals of interest (SOI) at unique cycle frequencies related to primary and/or secondary users from an antenna array measurement. Based on the SOI, one or more users of the spectrum can be identified or the spectrum can be regarded as vacant; this can be based on lobe identification in the frequency spectrum of the SOI, in one example. This mechanism is less complex than traditional cyclic spectrum analysis methods. The cyclostationary beamforming based approach is more effective than the energy detection method. Also, the need for quiet periods in spectrum sensing is eliminated when using this mechanism such that signals can be transmitted simultaneously with receiving signals over the antenna array.