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Intelligent threshold selection in fading environment of cognitive radio network: Advances in throughput and total error probability

One of the main challenges of spectrum sensing (SS) in the cognitive radio network (CRN) is selection of threshold for captivating the sensing decision, and such an issue becomes more challenging especially at low signal‐to‐noise ratio (SNR) because it affects the sensing performance and throughput of cognitive user (CU). However, the sensing decision of individual CU may not be accurate due to fading effects in the sensing environment, and significant improvement is accomplished with the cooperation of users. Therefore, in this paper, we have investigated the performance of energy detector SS (EDSS) technique in the CRN under fading environment with cooperative and noncooperative SS scenario. Further, we have introduced the concept of critical SNR (γc) to select the appropriate threshold and based on which the algorithms are proposed to enhance the throughput and reduce the total error (sensing error) probability of CU at different SNR (γ). From the results, we have accomplished that at the low SNR region (γ ≤ γc), throughput is maximum with constant false‐alarm rate (CFAR) threshold selection approach in the cooperative scenario while in the high SNR region (γ > γc), its value is maximum with minimizing the error probability (MEP) threshold selection approach in the noncooperative scenario. Moreover, the sensing error is reduced with cooperation, and threshold selection with MEP approach outperforms CFAR approach for γ ≤ γc. Further, the proposed approach outperforms the other approaches in terms of throughput and sensing error (total error) probability in the Rayleigh and Nakagami‐m fading environments.