<p>FFT is one of the most active blocks in digital signal processing and in various field of communication systems. FFT has received significant attention over the past years to increase its capability and versatility. This paper describes an extensive study on trade-off of different radices with different computational elements of butterfly such as adders and multipliers. Finding an efficient radix along with computational elements is the key point to find best suite i.e. high precision, low power and low area applications like radar, filtering, image compression etc. The work also considers the precision and the data format to represent constant value such as Q-point. The proposed FFT architectures not only uphold better solutions for low power and high-performance application systems, but also open up a new research lines. This paper demonstrates that radix-2^3 consumes 43% less LUTs and 17% less power consumption, 40% increase of frequency in radix-2^2 in comparison with radix- 2 algorithm for the combination of CSA with modified booth multiplier and the increment of frequency about 19%, 26% less LUTs consumption and 26% less power in Radix-2^2 when compared to radix-4 with various combination of adder and multiplier. In this work we have used Xilinx 14.7 XST for synthesis and the target device used is Spartan6 XC6SLX100. Simulation is carried out in Xilinx ISIM and also performed timing analysis and generated post-place and route.</p>
Low power and high performance FFT with different radices