Efficient FFT Algorithms for Mobile Devices

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Journal Title
Journal ISSN
Volume Title
Sähkötekniikan korkeakoulu | Master's thesis
Date
2016-10-27
Department
Major/Subject
Signal Processing
Mcode
S3013
Degree programme
TLT_2
Language
en
Pages
40
Series
Abstract
Increased traffic on wireless communication infrastructure has exacerbated the limited availability of radio frequency ({RF}) resources. Spectrum sharing is a possible solution to this problem that requires devices equipped with Cognitive Radio ({CR}) capabilities. A widely employed technique to enable {CR} is real-time {RF} spectrum analysis by applying the Fast Fourier Transform ({FFT}). Today’s mobile devices actually provide enough computing resources to perform not only the {FFT} but also wireless communication functions and protocols by software according to the software-defined radios paradigm. In addition to that, the pervasive availability of mobile devices make them powerful computing platform for new services. This thesis studies the feasibility of using mobile devices as a novel spectrum sensing platform with focus on {FFT}-based spectrum sensing algorithms. We benchmark several open-source {FFT} libraries on an Android smartphone. We relate the efficiency of calculating the {FFT} to both algorithmic and implementation-related aspects. The benchmark results also show the clear potential of special {FFT} algorithms that are tailored for sparse spectrum detection.
Description
Supervisor
Wichman, Risto
Thesis advisor
Di Francesco, Mario
Kortoci, Pranvera
Keywords
cognitive radios, software-defined radio, spectrum sensing, fast fourier transform, sparse FFT, crowdsourcing
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