Bitwidth-Optimized Energy-Efficient FFT Design via Scaling Information Propagation

The Fast Fourier Transform (FFT) is an efficient algorithm widely used in digital signal processing to transform between the time domain and the frequency domain. For fixed-point VLSI implementations, dynamic range growth inevitably occurs at each stage of the FFT operation. However, current methods...

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Vydané v:2021 58th ACM/IEEE Design Automation Conference (DAC) s. 613 - 618
Hlavní autori: Liu, Xinzhe, Chen, Fupeng, Muhamad, Raees Kizhakkumkara, Blinder, David, Nikolova, Dessislava, Schelkens, Peter, Catthoor, Francky, Ha, Yajun
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Jazyk:English
Vydavateľské údaje: IEEE 05.12.2021
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Abstract The Fast Fourier Transform (FFT) is an efficient algorithm widely used in digital signal processing to transform between the time domain and the frequency domain. For fixed-point VLSI implementations, dynamic range growth inevitably occurs at each stage of the FFT operation. However, current methods either waste bitwidth or consume excessive resources when dealing with the dynamic range growth issue. To address this issue, we propose an efficient scaling method called Scaling Information Propagation (SIP) to alleviate the problem of dynamic range growth, which makes full use of bitwidth with much less extra area consumed than the state-of-the-art solutions. In two consecutive transform operations, the SIP method extracts scaling information and makes scaling decisions in the former transform, then executes those in the latter one. We implement the FFT's VLSI architecture in the orthogonal frequency division multiplexing (OFDM) and the holographic video compression (HVC) systems to verify the SIP method. Compared to the state-of-the-art, experimental results after VLSI synthesis show that our method achieves 9.38% energy reduction and 8.36% area savings when requiring 1.02 × 10 -7 bit error ratio (BER) of the OFDM system, and 33.47% energy reduction and 30.98% area savings when requiring 20dB signal-to-noise ratio (SNR) of the HVC system, respectively.
AbstractList The Fast Fourier Transform (FFT) is an efficient algorithm widely used in digital signal processing to transform between the time domain and the frequency domain. For fixed-point VLSI implementations, dynamic range growth inevitably occurs at each stage of the FFT operation. However, current methods either waste bitwidth or consume excessive resources when dealing with the dynamic range growth issue. To address this issue, we propose an efficient scaling method called Scaling Information Propagation (SIP) to alleviate the problem of dynamic range growth, which makes full use of bitwidth with much less extra area consumed than the state-of-the-art solutions. In two consecutive transform operations, the SIP method extracts scaling information and makes scaling decisions in the former transform, then executes those in the latter one. We implement the FFT's VLSI architecture in the orthogonal frequency division multiplexing (OFDM) and the holographic video compression (HVC) systems to verify the SIP method. Compared to the state-of-the-art, experimental results after VLSI synthesis show that our method achieves 9.38% energy reduction and 8.36% area savings when requiring 1.02 × 10 -7 bit error ratio (BER) of the OFDM system, and 33.47% energy reduction and 30.98% area savings when requiring 20dB signal-to-noise ratio (SNR) of the HVC system, respectively.
Author Muhamad, Raees Kizhakkumkara
Chen, Fupeng
Catthoor, Francky
Liu, Xinzhe
Blinder, David
Nikolova, Dessislava
Ha, Yajun
Schelkens, Peter
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  surname: Ha
  fullname: Ha, Yajun
  email: hayj@shanghaitech.edu.cn
  organization: ShanghaiTech University,School of Information Science and Technology,China
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Snippet The Fast Fourier Transform (FFT) is an efficient algorithm widely used in digital signal processing to transform between the time domain and the frequency...
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StartPage 613
SubjectTerms Bitwidth-optimized
Dynamic range
Energy efficiency
energy-efficient
FFT design
OFDM
scaling information propagation
Signal processing algorithms
Transforms
Very large scale integration
Video compression
Title Bitwidth-Optimized Energy-Efficient FFT Design via Scaling Information Propagation
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