An important and widely considered signal identification technique for cognitive radios is cyclostationarity-based feature detection because this method does not require time and frequency synchronization and prior information except for information concerning cyclic autocorrelation features of target signals. This paper presents the development and experimental evaluation of cyclostationarity-based signal identification equipment. A spatial channel emulator is used in conjunction with the equipment that provides an environment to evaluate realistic spectrum sharing scenarios. The results reveal the effectiveness of the cyclostationarity-based signal identification methodology in realistic spectrum sharing scenarios, especially in terms of the capability to identify weak signals.

We provide a theoretical analysis of the capacity achievable by an open/closed-access cognitive radio system, where the system uses spectrum resources primarily allocated to a macro cellular system. For spectrum sharing, we consider two methods based on listen-before-talk and adaptive transmit power control principles. Moreover, outdoor and indoor installations of CRS stations are investigated. We have also taken the effect of antenna heights into consideration. Numerical results reveal the capacities possible from CRS base stations installed within the coverage area of the macro cell system. We show numerical examples that compare the capacities achievable by open-access and closed access cognitive radio systems.