Efficient FPGA Implementation of Multi-Channel Pipelined Large FFT Architectures Based on SA-MDF Algorithm

Abstract

FPGA implementation of a multi-channel pipelined large FFT architecture is challenging due to its complex inter-channel data scheduling, high-throughput requirement, and resource-constrained hardware. By transforming to 2D-FFT implementation, investigating different binary tree schemes, and exploring various radices, butterflies, as well as data path structures, many hardware architectures have been designed to enhance single-channel large FFT or multi-channel medium-small size FFT performance. These designs fall short in addressing the demands of multi-channel pipelined and large FFT applications. In this article, a self-attention multipath delay feedback (SA-MDF) algorithm is proposed to analyze and identify the most critical bottleneck, then automatically pay attention to improve it, and finally generate the optimal FFT framework by exhaustively exploring the design space. The proposed algorithm alleviates the design difficulties and speeds up the FPGA implementation. Furthermore, an approximate roofline model and a novel binary tree scheme are introduced to further minimize the utilization of on-chip memory. A comprehensive comparison in terms of principles, implementation methods, and optimization effects is conducted when compared with other multi-channel FFT architectures. Experimental results show that the proposed FFT architectures are superior to other FFT implementations in terms of channel count, FFT length, high-throughput data arrangement, and adaptability to diverse hardware platforms.