Robust cooperative spectrum sensing in cognitive radio networks under multiple smart primary user emulation attacks

2014 ◽  
Author(s):  
Mohammad Javad Saber ◽  
Seyed Mohammad Sajad Sadough
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Radio Networks ◽  
Primary User Emulation

Spectrum Sensing with Clustering in Cognitive Radio Networks

2014 ◽  
Vol 651-653 ◽  
pp. 1941-1944
Author(s):  
Jie Guo ◽  
Da Hai Jing ◽  
Yan Gu
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Fusion Rule ◽  
Primary User ◽  
Radio Networks ◽  
Main Task ◽  
Sensing Model ◽  
Spectrum Band

The main task of spectrum sensing in cognitive radio network is to decide whether the primary user is occupying the specific spectrum band or not. So the main purpose of spectrum sensing is to design a detector with better detection performance. This paper studies a spectrum sensing method with clustering under cognitive radio networks. We studied the cooperative spectrum sensing model with clustering by hard fusion rule, and also proposed the simulation model and steps of this cluster-based spectrum sensing problem under Majority rule. Simulation results show that the spectrum sensing method with clustering has better performance than the other methods.

scholarly journals A Correlation-Based Sensing Scheme for Outlier Detection in Cognitive Radio Networks

2021 ◽  
Vol 11 (5) ◽  
pp. 2362
Author(s):  
Muhammad Sajjad Khan ◽  
Mohammad Faisal ◽  
Su Min Kim ◽  
Saeed Ahmed ◽  
Marc St-Hilaire ◽  
...  
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Networks ◽  
Cooperative Spectrum Sensing ◽  
Primary User ◽  
Radio Networks ◽  
Fusion Center ◽  
Average Value ◽  
Whisker Plot ◽  
Hard Decision

Cooperative spectrum sensing (CSS) is a vital part of cognitive radio networks, which ensures the existence of the primary user (PU) in the network. However, the presence of malicious users (MUs) highly degrades the performance of the system. In the proposed scheme, each secondary user (SU) reports to the fusion center (FC) with a hard decision of the sensing energy to indicate the existence of the PU. The main contribution of this work deals with MU attacks, specifically spectrum sensing data falsification (SSDF) attacks. In this paper, we propose a correlation-based approach to differentiate between the SUs and the outliers by determining the sensing of each SU, and the average value of sensing information with other SUs, to predict the SSDF attack in the system. The FC determines the abnormality of a SU by determining the similarity for each SU with the remaining SUs by following the proposed scheme and declares the SU as an outlier using the box-whisker plot. The effectiveness of the proposed scheme was demonstrated through simulations.

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