An evaluation framework integrating sensing and transmission in cognitive radio networks

Cognitive radio technology provides a potential solution to the growing demand for radio spectrum resources. However, evaluating the differences between channel theoretical models in various application scenarios is a complex and critical challenge in cognitive radio technology. To address this issue, the authors propose a framework for evaluating performance that integrates spectrum sensing, allocation, and data transmission, and a mathematical derivation of how the parts are connected is given. The framework is capable of analyzing the sensing and transmission performance of different fading channel models. It enables the assessment of transmission performance for each heterogeneous secondary user (SU) across various transmission environments and decision thresholds, including parameters such as throughput, queue length, and packet rejection rate. Additionally, a performance metric is proposed to measure the impact of fading channel models on the primary user (PU). The simulation results show that the quantitative performance difference between the Rayleigh channel model and its improved Nakagami channel model in different environments can be obtained using the proposed evaluation framework. The proposed framework can improve the reliability and effectiveness of implementing cognitive radio networks in cross-application scenarios.