串并联混合结构FFT处理器

Hua Jiang, Wenkai Xu
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摘要

采用串并联混合结构实现了定点2次十进制快速傅里叶变换(R2DIT)处理器。将64点FFT分解为8通道8点FFT结构。每个通道是一个串行8点FFT,使用8点全并行结构。计算垂直8通道8点FFT,然后将结果乘以WNn1k2。然后,计算水平8通道8点FFT。这样,64点FFT计算被分解为两个全并行的8点FFT计算。基于EP2S130F1020C3芯片的64点FFT计算在100 MHz下的处理时间约为1.96 μs。从第一数据到最后数据的输出时间约为0.76 μs。然后将64点FFT简化为相同串并联混合结构的16点FFT,下载到DE2 FPGA开发板的EP2C35F-672C6芯片上。然后用SignalTap II工具提取信号。实验值与Matlab计算的理论值进行了比较。将其转换为十进制分数后,绝对误差小于0.2。另外,在100mhz频率下,从数据输入到第一个数据输出大约需要9.8 μs。从第一个数据输出到最后一个数据输出的总输出约为3 μs。与全并行FFT相比,串并联混合结构方案有效地解决了基于FPGA的速度与资源利用率之间的矛盾。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A Series-parallel Mixed Structure FFT Processor
The proposed fixed-point radix-2 decimation-in-time Fast Fourier Transform (R2DIT FFT) processor is implemented by the series-parallel mixed structure. The 64-point FFT is decomposed into 8-channel 8-point FFT structure. Each channel is a serial 8-point FFT which uses an 8-point full-parallel structure. The vertical 8-channel 8-point FFT is calculated, then the result is multiplied by WNn1k2. After that, the horizontal 8-channel 8-point FFT is calculated. In this way, the 64-point FFT calculation is decomposed into two full-parallel 8-point FFT calculations. The processing of the 64-point FFT calculation takes about 1.96 μs at 100 MHz based on EP2S130F1020C3 chip. And the output from the first data to the last data spends about 0.76 μs. Then, the 64-point FFT is simplified to the 16-point FFT with the same series-parallel mixed structure and downloaded to the EP2C35F-672C6 chip of the DE2 FPGA development board. Then the signal is extracted with the SignalTap II tool. Experimental values are compared with theoretical values calculated by Matlab. After converting them to decimal fractions, the absolute error is less than 0.2. In addition, it takes about 9.8 μs from the data input to the first data output at 100 MHz. And the total output from the first data output to the last data output is about 3 μs. Compared with the full-parallel FFT, the series-parallel mixed structure scheme achieves an effective solution for the contradiction between speeds and resource utilizations based on FPGA.
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