EFFICIENT ARCHITECTURE MAPPING OF FFT/IFFT FOR COGNITIVE RADIO NETWORKS

Cognitive radio networks require flexibility to support a variety of wireless communication system standards. Many modern systems utilize some form of orthogonal frequency division multiplexing (OFDM) and single-carrier frequency-division multiple access (SC-FDMA) often augmented with multiple input multiple output (MIMO) antenna schemes. A common module in these standards is the fast Fourier trans-form (FFT) and its inverse. Although many architectures ex-ist for traditional power-of-two FFT lengths, the recent 3GPP LTE standards define non- power-of-two transform lengths. The various FFT and IFFT lengths for both the uplink and downlink processing require support for radix-2, radix-3, and radix-5 modules. In this paper, we propose a highly flexi-ble FFT/IFFT architecture that can support a broad variety of transform sizes and efficient mapping to programmable testbed platforms for cognitive radio networks. This novel ar-chitecture will provide a range of transform sizes of the gen-eral form (2n3k5l), and for use in emerging algorithms for massive MIMO detectors. Index Terms—Discrete Fourier transform, FFT/IFFT, 3GPP LTE/LTE-Advanced, VLSI architecture, pipelined ar-chitecture. 1