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

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 x 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.