Improved spectrum sensing and achieved throughputs in cognitive radio networks

State of the art spectrum sensing methods evaluate sensing performance only based on correct detection of the presence of the primary user´s signal. As a first step, we propose a more realistic framework that also takes the correct detection of the absence of primary user´s signal into account for spectrum sensing performance evaluation. More precisely, by using the above framework, we select energy detection spectrum sensing parameters so as to minimize a cost function leading to an optimal operating point over the widely-used receiver operating characteristic curve. In a second step, by using the parameters obtained in the first step, we calculate the information rates achieved by both the cognitive and the primary users. These rates are compared to those provided by an ideal (interference-free) spectrum sensing. Numerical results show that the proposed improved spectrum sensing outperforms conventional spectrum sensing techniques in terms of total achievable throughputs, without any increase in the cognitive radio complexity.