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Journal ArticleDOI

A low-power, high-performance, 1024-point FFT processor

Bevan M. Baas
- 01 Mar 1999 - 
- Vol. 34, Iss: 3, pp 380-387
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TLDR
This paper presents an energy-efficient, single-chip, 1024-point fast Fourier transform (FFT) processor, which has been fabricated in a standard 0.7 /spl mu/m CMOS process and is fully functional on first-pass silicon.
Abstract
This paper presents an energy-efficient, single-chip, 1024-point fast Fourier transform (FFT) processor. The 460000-transistor design has been fabricated in a standard 0.7 /spl mu/m (L/sub poly/=0.6 /spl mu/m) CMOS process and is fully functional on first-pass silicon. At a supply voltage of 1.1 V, it calculates a 1024-point complex FFT in 330 /spl mu/s while consuming 9.5 mW, resulting in an adjusted energy efficiency more than 16 times greater than the previously most efficient known FFT processor. At 3.3 V, it operates at 173 MHz-which is a clock rate 2.6 times greater than the previously fastest rate.

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Citations
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Journal ArticleDOI

FPGA implementations of fast Fourier transforms for real-time signal and image processing

TL;DR: The design and realisation of a high level framework for the implementation of 1-D and 2-D FFTs for real-time applications and an FPGA-based parametrisable environment based on 2- D FFT is presented as a solution for frequency-domain image filtering application.
Journal ArticleDOI

A 2.4-GS/s FFT Processor for OFDM-Based WPAN Applications

TL;DR: A novel simplification method to reduce the hardware cost in multiplication units of the multiple-path FFT approach is proposed and a multidata scaling scheme to reduce wordlengths while preserving the signal-to-quantization-noise ratio is presented.
Journal ArticleDOI

New continuous-flow mixed-radix (CFMR) FFT Processor using novel in-place strategy

TL;DR: A new continuous-flow mixed-radix (CFMR) fast Fourier transform (FFT) processor that uses the MR (radix-4/2) algorithm and a novel in-place strategy that can reduce hardware complexity and computation cycles compared with existing FFT processors is proposed.
Book ChapterDOI

Mode Coupling and its Impact on Spatially Multiplexed Systems

TL;DR: This chapter provides an in-depth description of mode coupling, including its physical origins, its effect on modal dispersion (MD) and mode-dependent loss or gain (MDL), and the resulting impact on system performance and implementation complexity.
Journal ArticleDOI

Power and Area Minimization of Reconfigurable FFT Processors: A 3GPP-LTE Example

TL;DR: A design methodology for power and area minimization of flexible FFT processors based on the power-area tradeoff space obtained by adjusting algorithm, architecture, and circuit variables is presented.
References
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Book

Computer Architecture: A Quantitative Approach

TL;DR: This best-selling title, considered for over a decade to be essential reading for every serious student and practitioner of computer design, has been updated throughout to address the most important trends facing computer designers today.
Book

Discrete-Time Signal Processing

TL;DR: In this paper, the authors provide a thorough treatment of the fundamental theorems and properties of discrete-time linear systems, filtering, sampling, and discrete time Fourier analysis.
Book

Theory and application of digital signal processing

TL;DR: Feyman and Wing as discussed by the authors introduced the simplicity of the invariant imbedding method to tackle various problems of interest to engineers, physicists, applied mathematicians, and numerical analysts.
Journal ArticleDOI

Low-power CMOS digital design

TL;DR: In this paper, techniques for low power operation are presented which use the lowest possible supply voltage coupled with architectural, logic style, circuit, and technology optimizations to reduce power consumption in CMOS digital circuits while maintaining computational throughput.
Journal Article

Low-Power CMOS Digital Design

TL;DR: An architecturally based scaling strategy is presented which indicates that the optimum voltage is much lower than that determined by other scaling considerations, and is achieved by trading increased silicon area for reduced power consumption.