Dynamic partial reconfigurable FFT/IFFT pruning for OFDM based Cognitive radio

Cognitive Radio is an application in which Spectrum utilization can be improved by allowing secondary users to use the spectrum when it is not used by licensed primary users. An adaptive OFDM system for Cognitive radio has the ability to nullify unnecessary individual carriers and avoid interference to licensed primary users. A Fast Fourier Transform (FFT) block forms the core of OFDM design. But, the zero valued inputs outnumber the non-zero valued inputs in the FFT block making the standard FFT algorithms computationally inefficient due to wasted operation on zero values. To overcome this problem, several pruning algorithms have been developed. But many of them are architecturally inefficient for FPGA implementation due to complexity of the overhead operations. Moreover, these algorithms are not suitable for applications like Cognitive radio which has zero inputs in arbitrary distributions making hardware implementation to be complex. This paper presents a novel and efficient dynamically partial reconfigurable (DPR) Transform Decomposition (TD) FFT and Radix 2 based IFFT pruning for OFDM based Cognitive Radio on FPGA. Tested FPGA results on XC2VP30 for the DPR method show the configuration time improvement, good area and power efficiency.