Achievable Outage Rates in Cognitive Radio Networks under Imperfect Spectrum Sensing

In this paper, we aim at deriving the outage rates achieved by the primary user due to spectrum sensing in a cognitive radio network, that we call sensing-induced primary outage rates. To reach this goal, in the first step, instead of classical spectrum sensing techniques that evaluate sensing performance only based on correct detection of the presence of the primary user’s signal, we propose a modified framework that also takes into account the correct detection of the absence of primary user’s signal for spectrum sensing performance evaluation. In a second step, we derive the information rates achieved by the coexistence of a primary and a cognitive network. In the last step, assuming slowfading sensing channels, we derive the sensing-induced primary outage rates, i.e., outage rates achieved by the primary network in the presence of a CR with imperfect spectrum sensing, characterized by a given miss-detection probability. Numerical results show that the proposed spectrum sensing outperforms conventional spectrum sensing techniques in terms of primary signal outage rates and total achievable throughputs, without any increase in the cognitive radio complexity.