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A Novel Memory-Based FFT Architecture for Real-Valued Signals Based on a Radix-2 Decimation-In-Frequency Algorithm

This brief presents a novel architecture for memory-based fast Fourier transform (FFT) computation for real-valued signals based on radix-2 decimation-in-frequency algorithm. A superior strategy of stage partition for the real FFT (RFFT) is proposed to minimize the computation clock cycles and maximize the utilization of the processing element (PE). The PE employed in our RFFT architecture can process four inputs in parallel by using two radix-2 butterflies and only two multiplexers. The proposed memory-addressing scheme and control of the multiplexers can be expressed in terms of a counter according to the RFFT computation stage. Furthermore, the proposed RFFT architecture can support more PEs in two dimensions as well. Compared with prior works, the proposed RFFT processors have the advantages of fewer computation cycles and lower hardware usage. The experiment shows that the proposed processor reduces the computation cycles by a factor of 17.5% for a 32-point RFFT computation compared with a recently presented work while maintaining lower hardware usage and complexity in the PE design.