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Cluster mechanism for sensing data report using robust collaborative distributed spectrum sensing

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Abstract

In cooperative mobile communications, spectrum sensing performance may encounter difficulties, which alert with many reporting errors, especially in dense network scenarios. In such networks, the decision fusion process for cooperating users becomes very complex, which requires sensing heavy traffic that needs a large bandwidth. To enhance the reliability of robust cooperative spectrum sensing, the paper proposed a new data fusion scheme based on clustering algorithm and distributed detection, in addition to an adapted threshold based on controlled false alarm probability. The proposed algorithm is dedicated to a highly Rayleigh faded environment to improves the channel errors. The results show that the use of two stages process of distribution clusters and selection fusion node (FN)s gives 0.42 error improvement. The results of the receiver operating characteristic (ROC) curve show an improvement in both false alarms and detection probabilities. Moreover, the sensitivity is also enhanced by 0.95.

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Availability of data and material

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

Availability of code

The code generated during the current study are available from the corresponding author on reasonable request.

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Funding

This research was supported by Taif University Researchers Supporting Project number (TURSP-2020/216), Taif University, Taif, Saudi Arabia.

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Conceptualization, RAM, RAS. Data curation, HA, RAS, SA-K. Formal analysis, RAM, HA. Funding acquisition, RAS, HA, SA-K. The investigation, All Authors. Methodology, RAM, RAS, MK. Project administration, All Authors. Resources, RAM, RAS, SA-K. Software, all authors. Supervision, RAS, HA. Validation, HA, RAS, SA-K. Visualization, RAM, RAS, MK. Writing—original draft, all authors. Writing—review editing—all authors.

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Correspondence to S. Abdel-Khalek.

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Mokhtar, R.A., Saeed, R.A., Alhumyani, H. et al. Cluster mechanism for sensing data report using robust collaborative distributed spectrum sensing. Cluster Comput 25, 2541–2556 (2022). https://doi.org/10.1007/s10586-021-03363-8

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