Cognitive Radio Network with Wideband Spectrum Sensing and Reliable Data Transmission

2018 ◽  
Author(s):  
Aswathy G.P. ◽  
K. Gopakumar
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Data Transmission ◽  
Cognitive Radio Network ◽  
Reliable Data ◽  
Radio Network ◽  
Wideband Spectrum Sensing

scholarly journals Bayesian Compressive Sampling Based Wideband Spectrum Sensing in Cognitive Radio Network using Wavelet Transform

2019 ◽  
Vol 8 (4) ◽  
pp. 1412-1419
Keyword(s):  
Wavelet Transform ◽  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Cognitive Radio Network ◽  
Primary User ◽  
Compressive Sampling ◽  
Signal Recovery ◽  
Radio Network ◽  
Recovery Algorithm ◽  
Wideband Spectrum Sensing

This paper deals with the implementation of sub Nyquist sampling for the efficient wideband spectrum sensing in cognitive radio network. Cognitive radio is a very promising technology in the field of wireless communication which has drastically changed the spectral dynamics through the opportunistic utilization of frequency band by the secondary users when it is not utilized by the primary users. The complexity of spectral detection strategy is reduced using the compressive sensing method. Bayesian technique is utilized in the compressive sampling to deal with uncertainty of the process and increase the speed of detection. This technique recovers the wideband signals even with few measurements via Laplace prior and Toeplitz matrix. Sparse signal recovery algorithm is used for the extraction of primary user frequency location. The condition of the detection of primary user even in the low regulated transmission from unlicensed user is been resolved in this paper through Wavelet transform. This approach enables the evaluation of all possible hypotheses simultaneously in the global optimization framework. Simulation analysis is performed to verify the effectiveness of the proposed technique over the cognitive radio network.

scholarly journals Goodness-of-Fit Based Secure Cooperative Spectrum Sensing for Cognitive Radio Network

2014 ◽  
Vol 2014 ◽  
pp. 1-6
Author(s):  
Hiep Vu-Van ◽  
Insoo Koo
Keyword(s):  
Cognitive Radio ◽  
Spectrum Sensing ◽  
Goodness Of Fit ◽  
Cognitive Radio Network ◽  
Cooperative Spectrum Sensing ◽  
Harmful Effect ◽  
Radio Network ◽  
Measured Distance ◽  
Simulation Results ◽  
Sample Set

Cognitive radio (CR) is a promising technology for improving usage of frequency band. Cognitive radio users (CUs) are allowed to use the bands without interference in operation of licensed users. Reliable sensing information about status of licensed band is a prerequirement for CR network. Cooperative spectrum sensing (CSS) is able to offer an improved sensing reliability compared to individual sensing. However, the sensing performance of CSS can be destroyed due to the appearance of some malicious users. In this paper, we propose a goodness-of-fit (GOF) based cooperative spectrum sensing scheme to detect the dissimilarity between sensing information of normal CUs and that of malicious users, and reject their harmful effect to CSS. The empirical CDF will be used in GOF test to determine the measured distance between distributions of observation sample set according to each hypothesis of licensed user signal. Further, the DS theory is used to combine results of multi-GOF tests. The simulation results demonstrate that the proposed scheme can protect the sensing process against the attack from malicious users.

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