Sequential single symbol differential voting for cooperative spectrum sensing in the presence of byzantine attack and imperfect reporting channels

2021 ◽  
Author(s):  
Jun Wu ◽  
Pei Li ◽  
Zehao Chen ◽  
Chen Ze ◽  
Jianrong Bao
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Reporting Channels

Cooperative spectrum sensing under unreliable reporting channels

2014 ◽  
Vol 20 (6) ◽  
pp. 1399-1407 ◽  
Author(s):  
Amanda de Paula ◽  
Cristiano Panazio
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Reporting Channels

Soft Cooperative Spectrum Sensing Performance Under Imperfect and Non Identical Reporting Channels

2015 ◽  
Vol 19 (2) ◽  
pp. 227-230 ◽  
Author(s):  
Mahdi Ben Ghorbel ◽  
Haewoon Nam ◽  
Mohamed-Slim Alouini
Keyword(s):  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Sensing Performance ◽  
Reporting Channels

Cooperative Spectrum Sensing with Censoring of Cognitive Radios and MRC-Based Fusion in Fading and Shadowing Channels

2015 ◽  
pp. 38-67
Author(s):  
Srinivas Nallagonda ◽  
Sanjay Dhar Roy ◽  
Sumit Kundu ◽  
Gianluigi Ferrari ◽  
Riccardo Raheli
Keyword(s):  
Channel Estimation ◽  
Spectrum Sensing ◽  
Cooperative Spectrum Sensing ◽  
Minimum Mean Square Error ◽  
Cognitive Radios ◽  
Decision Fusion ◽  
Soft Data ◽  
Fading And Shadowing ◽  
Log Normal ◽  
Reporting Channels

In this chapter, the authors study the performance of Cooperative Spectrum Sensing (CSS) with soft data fusion, given by Maximal Ratio Combining (MRC)-based fusion with Weibull faded channels, and Log-normal shadowed channels. More precisely, they evaluate the performance of a MRC-based CSS with Cognitive Radios (CRs) censored on the basis of the quality of the reporting channels. The performance of CSS with two censoring schemes, namely rank-based and threshold-based, is studied in the presence of Weibull fading, Rayleigh fading, and Log-normal shadowing in the reporting channels, considering MRC fusion. The performance is compared with those of schemes based on hard decision fusion rules. Furthermore, depending on perfect or imperfect Minimum Mean Square Error (MMSE) channel estimation, the authors analyze the impact of channel estimation strategy on the censoring schemes. The performance is studied in terms of missed detection probability as a function of several network, fading, and shadowing parameters.

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