Filter bank based spectrum sensor for cognitive radios

Cognitive radios are wireless communication networks that are able to reliably sense the spectral environment over a wide bandwidth. These radios are lower priority unlicensed users, which exploit cognitive radio techniques, to ensure non-interfering co-existence with the licensed users. Spectrum se...

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Bibliographic Details
Main Author: Kua, Hui Xian.
Other Authors: Vinod Achutavarrier Prasad
Format: Final Year Project
Language:English
Published: 2010
Subjects:
Online Access:http://hdl.handle.net/10356/39915
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Institution: Nanyang Technological University
Language: English
Description
Summary:Cognitive radios are wireless communication networks that are able to reliably sense the spectral environment over a wide bandwidth. These radios are lower priority unlicensed users, which exploit cognitive radio techniques, to ensure non-interfering co-existence with the licensed users. Spectrum sensing is one of the most important attributes of cognitive radios. This is because unlicensed users must be able to detect the unused frequency spectrum efficiently to minimize interference to other users. In this report, we study the application of filter bank based spectrum sensor for cognitive radios. It has been known that discrete Fourier transform filter bank (DFTFB) is an efficient method for implementing the spectrum sensor for cognitive radio. Therefore, by building the DFT processor using fast Fourier transform (FFT) algorithm, a four-point DFTFB is implemented. In order to investigate the performance of a higher order spectrum sensor, we expanded the four-point filter bank into an eight-point filter bank. As the DFTFB requires polyphase components to be implemented for the prototype digital filter, careful consideration is made to the designs of it. The spectrum sensing approach used in this project is energy detection because of its simplicity. The performance analysis of four-point and eight-point DFTFB based spectrum sensors is presented by giving different input signals. It is shown that higher order spectrum sensor is a better option when the input signals are closely located or the vacant spectrum is narrow. A more reliable method of spectrum sensing is identified as the cooperative sensing technique which can be used to further enhance the system.