Design of 16-point Radix-4 Fast Fourier Transform in 0.18µm CMOS Technology

Abstract

This paper introduces detail design of semi-custom CMOS Fast Fourier Transform (FFT) architecture for computing 16-point radix-4 FFT. FFT is one of the most widely used algorithms in digital signal processing. It is used in many signal processing and communication application as an important block for various multi-carrier systems such as for WLAN (Wireless local area network). This paper describes the design of an ASIC (Application Specific Integrated Circuit) CMOS FFT processor for 16-point radix-4 complex FFT computation, realized utilizing 0.18µm standard CMOS technology. Fixed point data format is preferred in comparison of floating point data format for a shorter dynamic range and reduced hardware utilization; thus, catering to the needs of portability. Furthermore, computations results at particular stage are rounded to avoid overflow issue and to be stored in register. The computation speed of the design is observed to be 50MHz after the synthesis process. Compared to traditional radix-4 algorithm the architecture proposed for 16-point FFT results in 1.73% of power saving and 5.5% of area reduction.

Application Specific Integrated Circuits Design and Implementation of Rademacher and Walsh Functions

“…Chip designing also requires highly sophisticated and specialized EDA tools, which play very important role in de-signing a chip. This is because at each step, the designer needs to optimize the design to the best achievable limit and this can only be done with the help of highly specialized tools (Palaniappan and Zulkifli, 2007). Synopsys is one of the leading company in the manufacturing of EDA tools and this design is implemented by using complete CBIC design suite of soft-wares from Synopsys.…”

“…From decades, Fourier theory has been a very important tool in analyzing signals, particularly for the analysis of analog signals where sine-cosine functions are used. However, with the advent of digital computers and their use in different fields, theory of Discrete Fourier Analysis has to be further developed (Palaniappan and Zulkifli, 2007). For Discrete Signal Analysis, there are many other theories to analyze them and sometimes they gives better result than discrete fourier analysis.…”

“…Field Programmable Gate Arrays (FPGAs) are good choice for hardware realization but with limitations in design optimization. Furthermore, FPGA implementation is good for prototyping where, the aim is to predict the behavior of design in real world applications, there are many DSP systems reported in literature few of them are (Palaniappan and Zulkifli, 2007;Benhamid and Othman, 2009;Rais et al, 2010;Rais, 2010;Teymourzadeh et al, 2010). Application Specific Integrated Circuits (ASIC) is the most feasible technology to realize DSP algorithms and any other complex algorithm, without much limitations in optimizing the design.…”