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Abstract
This research work presents the design and implementation of a FFT pruning block, which is an extension to the FFT core for OFDM demodulation, enabling run-time
8
pruning of the FFT algorithm, without any restrictions on the distribution pattern of the active/inactive sub-carriers. The design and implementation of FFT processor core is not the part of this work. The whole design was prototyped on an ALTERA STRATIX V FPGA to evaluate the performance of the pruning engine. Synthesis and simulation results showed that the logic overhead introduced by the pruning block is limited to a 10% of the total resources utilization. Moreover, in presence of a medium-high scattering of the sub-carriers, power and energy consumption of the FFT core were reduced by a 30% factor.
Abstract
This research work presents the design and implementation of a FFT pruning block, which is an extension to the FFT core for OFDM demodulation, enabling run-time
8
pruning of the FFT algorithm, without any restrictions on the distribution pattern of the active/inactive sub-carriers. The design and implementation of FFT processor core is not the part of this work. The whole design was prototyped on an ALTERA STRATIX V FPGA to evaluate the performance of the pruning engine. Synthesis and simulation results showed that the logic overhead introduced by the pruning block is limited to a 10% of the total resources utilization. Moreover, in presence of a medium-high scattering of the sub-carriers, power and energy consumption of the FFT core were reduced by a 30% factor.
Tipologia del documento
Tesi di laurea
(Laurea magistrale)
Autore della tesi
Cucchi, Manuele
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Cognitive Radio, FFT pruning, FPGA
Data di discussione della Tesi
21 Marzo 2013
URI
Altri metadati
Tipologia del documento
Tesi di laurea
(?? magistrale ??)
Autore della tesi
Cucchi, Manuele
Relatore della tesi
Correlatore della tesi
Scuola
Corso di studio
Ordinamento Cds
DM270
Parole chiave
Cognitive Radio, FFT pruning, FPGA
Data di discussione della Tesi
21 Marzo 2013
URI
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