2048-point fast Fourier transform processing based on twiddle factor reduction and dynamic data scaling

Bang Chul Jung, Choul Young Kim, Hyoungho Ko, Ji Hoon Kim

Research output: Contribution to journalArticlepeer-review


In this paper, we present a new fast Fourier transform (FFT) algorithm to reduce the table size of twiddle factors required in pipelined FFT processing. The proposed algorithm can reduce the table size to half, compared to the radix-22 algorithm, while retaining the simple structure. In addition, a new dynamic data scaling approach is presented to reduce hardware complexity without degrading signal-to-quantization-noise ratio (SQNR). To verify the proposed algorithm, a 2048-point pipelined FFT processor is designed using a 0.18 μm CMOS process. By combining the proposed algorithm and the radix-22 algorithm, the table size is reduced to 35% and 53% compared to the radix-2 and radix-22 algorithms, respectively. The FFT processor occupies 1.95 mm2 and achieves SQNR of more than 55 dB without increasing the internal wordlength progressively using the proposed dynamic data scaling.

Original languageEnglish
Pages (from-to)3662-3666
Number of pages5
JournalAdvanced Science Letters
Issue number11
StatePublished - Nov 2016

Bibliographical note

Funding Information:
This study was supported by the Research Program funded by the Seoul National University of Science and Technology.

Publisher Copyright:
© 2016 American Scientific Publishers. All rights reserved.


  • Data scaling
  • FFT (Fast fourier transform)
  • Pipelined processing


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