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2048-Point Fast Fourier Transform Processing Based on Twiddle Factor Reduction and Dynamic Data Scaling

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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.
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Keywords: Data Scaling; FFT (Fast Fourier Transform); Pipelined Processing

Document Type: Research Article

Affiliations: 1: Department of Electronics Engineering, Chungnam National University, Daejeon, 34134, Republic of Korea 2: Department of Electrical and Information Engineering, Seoul National University of Science and Technology, Seoul, 01811, Republic of Korea

Publication date: November 1, 2016

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  • ADVANCED SCIENCE LETTERS is an international peer-reviewed journal with a very wide-ranging coverage, consolidates research activities in all areas of (1) Physical Sciences, (2) Biological Sciences, (3) Mathematical Sciences, (4) Engineering, (5) Computer and Information Sciences, and (6) Geosciences to publish original short communications, full research papers and timely brief (mini) reviews with authors photo and biography encompassing the basic and applied research and current developments in educational aspects of these scientific areas.
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