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| Roberto Airoldi, Omer Anjum, Fabio Garzia, Alexander Wyglinski, Jari Nurmi, "Energy-Efficient Fast Fourier Transforms for Cognitive Radio Systems," IEEE Micro, vol. 30, no. 6, pp. 66-76, November/December, 2010. | |||
| BibTex | x | ||
| @article{ 10.1109/MM.2010.84, author = {Roberto Airoldi and Omer Anjum and Fabio Garzia and Alexander Wyglinski and Jari Nurmi}, title = {Energy-Efficient Fast Fourier Transforms for Cognitive Radio Systems}, journal ={IEEE Micro}, volume = {30}, number = {6}, issn = {0272-1732}, year = {2010}, pages = {66-76}, doi = {http://doi.ieeecomputersociety.org/10.1109/MM.2010.84}, publisher = {IEEE Computer Society}, address = {Los Alamitos, CA, USA}, } | |||
| RefWorks Procite/RefMan/Endnote | x | ||
| TY - MGZN JO - IEEE Micro TI - Energy-Efficient Fast Fourier Transforms for Cognitive Radio Systems IS - 6 SN - 0272-1732 SP66 EP76 EPD - 66-76 A1 - Roberto Airoldi, A1 - Omer Anjum, A1 - Fabio Garzia, A1 - Alexander Wyglinski, A1 - Jari Nurmi, PY - 2010 KW - multiprocessor system on chip KW - energy efficiency KW - cognitive radio KW - NC-OFDM KW - FFT pruning KW - parallel algorithms. VL - 30 JA - IEEE Micro ER - | |||
An energy-efficient fast Fourier transform (FFT) algorithm for cognitive radio communication systems uses a homogeneous multiprocessor system on chip. The algorithm allows for pruning of inputs such that algorithm complexity can be reduced whenever several of the FFT inputs are zero. Results show that the pruning algorithm significantly reduces energy consumption compared to a nonpruned version.
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