Hi all,I am working on FPGA Implementation of fixed-point FFT and trying to minimize resources.I have 4 parallel samples coming from ADC into FPGA. I want to calculate 1024-point FFT of the input stream...
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Hi all, I am working on FPGA Implementation of fixed-point FFT and trying to minimize resources. I have 4 parallel samples coming from ADC into FPGA. I want to calculate 1024-point FFT of the input stream. To do this, I have 4 FFT's of 256-point running in parallel. I am planning on multiplying the input stream with necessary twiddle factors before I send it to the 4 FFT's running in parallel. My main questions is that: 1) Xilinx FFT Cores expose real an imaginary input for each of the FFT. Since my input stream is real, instead of tying the imaginary component to zero, I want to use it. I want to compute Real FFT using Complex FFT Cores provided by Xilinx. By doing so, I can reduce the required parallel FFT's from 4 to 2 (50% reduction in FPGA resources). This is similar to App Note described by TI: http://processors.wiki.ti.com/index.php/Efficient_FFT_Computation_of_Real_Input 2) If I configure the FFT Core as Fixed-Point, Unscaled Output. Can I feed two real inputs to Real, Imaginary part of Xilinx Core and later perform math to get real FFT. I read somewhere if the Core is configured as Single-Precision FFT, there won't be rounding issues. With Fixed-Point, Unscaled Output, will be there be any rounding issues? Any thoughts/ suggestions are greatly appreciated. Feel free to post any questions if I am not clear. rakumarudu______________________________