Cooperative Bayesian‐based detection framework for spectrum sensing in cognitive radio networks

Maleki, Alireza; Mirzahosseini, Davood; Moghaddam, Naser Ahmadi

doi:10.1049/iet-com.2019.0353

Cited by 4 publications

(2 citation statements)

References 15 publications

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“…Also, the proposed system achieves a better performance in terms of the required number reporting secondary users compared to other techniques for the same probability of detection which compensates for the higher complexity of the system. Also, Averaging (17) over h 2 SU1 distribution, and with assumbtion that all channels are Rayleigh flat fading channels with AWGN, (25) where Z 1 = h 2 SU1 γ F C , and…”

Section: Discussionmentioning

confidence: 99%

“…The authors of [25] proposed a cooperative blind Bayesian-based detection framework for spectrum sensing in CR networks to overcome the noise variance uncertainty problem which severely degrades the performance of the ED. In [25], M SUs calculate the power of observed signals and forward it to the FC. Then, the FC utilizes the proposed algorithm to blindly make the final decision about the existence of the primary user.…”

Section: Related Workmentioning

confidence: 99%

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Cooperative Spectrum Sensing Using Maximum a Posteriori as a Detection Technique for Dynamic Spectrum Access Networks

et al. 2020

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Over the past few years, dynamic spectrum access has been gaining an increasing attention as a solution to the spectrum scarcity problem. In this paper, a primary user detection technique based on Maximum A Posteriori estimation is proposed for dynamic spectrum access networks. In the proposed technique, a set of secondary users acting as sensing nodes send their individual decisions about the existence of the primary user to a central fusion center. The fusion center uses the received data to form a codeword then, applies the maximum a posteriori estimation rule to make a final decision regarding the presence of the primary user. The proposed technique takes into consideration the accuracy of the local decisions provided by the secondary users when making a final decision. In this paper, we analyze the performance of the proposed scheme and derive closed-form expressions for the upper bounds of the false alarm and misdetection probabilities. The results show that the proposed technique outperforms other combining techniques in terms of its ability to detect the primary user and, accordingly, minimizes the harmful interference to the licensed network. Moreover, the proposed technique achieves better performance at a lower number of reporting secondary users which compensates for the complexity of the maximum a posteriori estimation.

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Section: Discussionmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%