Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the primary signal at a low signal to noise ratio (SNR). At a low SNR, the variance of noise fluctuates due to noise uncertainty. Detection of the primary signal will be difficult especially for blind spectrum sensing methods that rely on the variance of noise for their threshold setting, such as energy detection. Instead of using the energy difference, we propose a spectrum sensing method based on the distribution difference. When the channel is occupied, the distribution of the received signal, which propagates under a wireless fading channel, will have a non-Gaussian distribution. This will be different from the Gaussian noise when the channel i...
In this letter, a blind spectrum sensing method based on goodness-of-fit (GoF) test using likelihood...
The inability to perfectly know the system noise properties to infinite precision, referred to as no...
Abstract—The inability to perfectly know the system noise properties to infinite precision, referred...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
<p align="JUSTIFY">Spectrum sensing for cognitive radio is a challenging task since it has to be abl...
Abstract—Despite its simplicity, drawback for the application of energy detection for spectrum sensi...
Energy detection is among the most popular spectrum sensing method for spectrum sensing due its low ...
In cognitive radio, spectrum sensing is one of the most important tasks. In this article, a blind sp...
Abstract—In cognitive radio, spectrum sensing is one of the most important tasks. In this article, a...
Blind spectrum sensing in cognitive radio is being addressed in this thesis. Particular emphasis is ...
Spectrum sensing, in particular, detecting the presence of incumbent users in licensed spectrum, is ...
The performance of the existing spectrum sensing algorithms based on goodness of fit (GoF) tests are...
In this letter, a blind spectrum sensing method based on goodness-of-fit (GoF) test using likelihood...
The inability to perfectly know the system noise properties to infinite precision, referred to as no...
Abstract—The inability to perfectly know the system noise properties to infinite precision, referred...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
Spectrum sensing for cognitive radio is a challenging task since it has to be able to detect the pri...
<p align="JUSTIFY">Spectrum sensing for cognitive radio is a challenging task since it has to be abl...
Abstract—Despite its simplicity, drawback for the application of energy detection for spectrum sensi...
Energy detection is among the most popular spectrum sensing method for spectrum sensing due its low ...
In cognitive radio, spectrum sensing is one of the most important tasks. In this article, a blind sp...
Abstract—In cognitive radio, spectrum sensing is one of the most important tasks. In this article, a...
Blind spectrum sensing in cognitive radio is being addressed in this thesis. Particular emphasis is ...
Spectrum sensing, in particular, detecting the presence of incumbent users in licensed spectrum, is ...
The performance of the existing spectrum sensing algorithms based on goodness of fit (GoF) tests are...
In this letter, a blind spectrum sensing method based on goodness-of-fit (GoF) test using likelihood...
The inability to perfectly know the system noise properties to infinite precision, referred to as no...
Abstract—The inability to perfectly know the system noise properties to infinite precision, referred...