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

Abstract

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 (γ c ) 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 ≤ γ c ), throughput is maximum with constant false-alarm rate (CFAR) threshold selection approach in the cooperative scenario while in the high SNR region (γ > γ c ), 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 ≤ γ c . 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.

Optimisation of censoring‐based cooperative spectrum sensing approach with multiple antennas and imperfect reporting channel scenarios for cognitive radio network

“…From Fig. 6, it is clear that the proposed approach with optimal K provides less sensing error as compared to that of the majority rule employed in [26] and also improvement with respect to OR and AND rule when CFAR approach is employed. However, MEP approach provides nearly same sensing error with both the majority and our proposed optimal rule selection schemes.…”

“…However, in CSS, Atapattu et al [25] have employed OR cooperative rule and minimised the sensing error under different fading channels. Further, an improvement in the sensing error is achieved by Kumar et al in [26] while considering the majority cooperative fusion rule at FC under the perfect reporting channel.…”

Spectral efficient designs of MIMO‐based CR‐NOMA for Internet of Things Networks

“…The potential technology that transforms the DSA into reality is cognitive radio (CR), which comprises four steps, namely, the spectrum sensing, spectrum analysis and decision, spectrum sharing, and spectrum mobility. [17][18][19][20][21] The CU senses the radio-frequency spectrum and then starts communication on the idle sensed channels. During the CU communication, it is possible that the PU will come back for communication, at that time the CU needs to switch its communication on other available channel, and this process is known as spectrum mobility.…”

“…This fact opens the door of DSA, which is a technique that allows the unlicensed/cognitive users (CUs) to access the spectrum of licensed primary users (PUs) under the constraint that the PU communication remains unaffected. The potential technology that transforms the DSA into reality is cognitive radio (CR), which comprises four steps, namely, the spectrum sensing, spectrum analysis and decision, spectrum sharing, and spectrum mobility 17–21 . The CU senses the radio‐frequency spectrum and then starts communication on the idle sensed channels.…”