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C Model Sim (Fixed-Point) -A New Approach to Pipeline FFT Processor

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Presentation on theme: "C Model Sim (Fixed-Point) -A New Approach to Pipeline FFT Processor"— Presentation transcript:

1 C Model Sim (Fixed-Point) -A New Approach to Pipeline FFT Processor
Presenter: Chia-Hsin Chen, Yen-Chi Lee Mentor: Chenjo Instructor: Andy Wu

2 Outline FFT Review FFT on Hardware What’s Fixed-Point Model Analysis
RTL Implementation Conclusion & Future Works Reference 2019/4/7 Owen, Lee

3 FFT Review An efficient algorithm computes DFT Twiddle Factor:
2019/4/7 Owen, Lee

4 Radix-22 DIF Algorithm Proposed by S. He and M. Torkelson
Applying a 3-dimensional linear index map 2019/4/7 Owen, Lee

5 Radix-22 DIF Algorithm (cont.)
2019/4/7 Owen, Lee

6 R22SDF Pipeline FFT Example: N=256 2019/4/7 Owen, Lee

7 Floating Point vs Fixed-point
Use many bits to represent a number More precise but more computationally demanding Fixed-point Use finite bits to represent a number For hardware implementation 2019/4/7 Owen, Lee

8 Fixed-Point Model Quantization Saturation Truncation
input & twiddle factor Saturation BF2I & BF2II Truncation multiplication 2019/4/7 Owen, Lee

9 Fixed-Point Model (Cont.)
Quantization For initial values (input & twiddle factor) Table look up techniques Saturation For addition If there is a carry-out from MSB, set the number to maximum Truncation For multiplication Store the required bits form MSB, and omit the rest 2019/4/7 Owen, Lee

10 C/C++ Simulation 2019/4/7 Owen, Lee

11 Signal-of-Quantization-Noise Ratio
SQNR : ratio of signal power to noise power Error range lies in ±1/2 LSB For each additional bit, the SQNR goes up by about 6dB 2019/4/7 Owen, Lee

12 Requirements 64-point R22SDF Dynamic range for input data:[-4,4]
Number of bits for input data:10~14 Number of bits for output data:16~20 SQNR≧50dB Evaluation Equation: Score = Area * (clock period)2 2019/4/7 Owen, Lee

13 Analysis Overview Worst case for integer part :
input x[n]=4 for n=0~63 → maximum output X[0]=4*64=256 → needs 8 bits for integer part But it is not often the case Based on the simulation result, 7 bits is enough 2019/4/7 Owen, Lee

14 Analysis Overview(Cont.)
Fractional part and twiddle factor are closely related Fix one of them and alter the other, the effect is not obvious Therefore, fractional part and twiddle factor have to be increased simultaneously 2019/4/7 Owen, Lee

15 Plotting (Fix Integer Part)
Fix integer part(5 – 8 bits) 2019/4/7 Owen, Lee

16 Average Case vs Single Case
2019/4/7 Owen, Lee

17 Plotting (Fix Fractional Part)
Fix fractional part(7 – 10bits) 2019/4/7 Owen, Lee

18 Plotting (Fix Twiddle Factor)
Fix twiddle factor(8 – 11bits) 2019/4/7 Owen, Lee

19 Average SQNR Table (7-bit integer part)
frac\twi 6 7 8 9 10 11 12 13 5 2019/4/7 Owen, Lee

20 Possible Sets 2019/4/7 Owen, Lee

21 RTL Realization Just for functional work
Word-lengths are the same through the whole process Integer : 8 bits (including sign bit) Fractional : 8 bits Twiddle : 12 bits (including sign bit) Omit area and timing consideration 2019/4/7 Owen, Lee

22 RTL Realization (Cont.)
16 points 64 points Logic elements: 2990 Registers : 2054 fmax : 21.46MHz 2019/4/7 Owen, Lee

23 RTL Realization (Cont.)
Memory storage reducing Symmetry of twiddle factor Area reducing Different word-lengths of adder and multiplier Power saving Treat delay block as RAM 2019/4/7 Owen, Lee

24 Conclusion & Future Works
We find some possible sets that meet the requirement Apply these sets of wordlengths to our RTL model Take area & clock period into consideration Power, if possible 2019/4/7 Owen, Lee

25 References S. He and M. Torkelson. “A new approach to pipeline FFT processor.” IEEE Proceedings of IPPS ’96. S. He and M. Torkelson. “Designing Pipeline FFT Processor for OFDM (de)Modulation.” ISSSE, pp , Sept J. Y. Oh and M. S. Lim. “New Radix-2 to the 4th Power Pipeline FFT Processor.” IEICE Trans. Electron., Vol.E88-C, No.8 Aug. 2005 E. E. Swartzlander, W. K. W. Young, and S. J. Joseph. “A radix 4 delay commutator for fast Fourier transform processor implementation.” IEEE J. Solid-State Circuits, SC-19(5): , Oct C. D. Thompson. “Fourier transform in VLSI.” IEEE Trans. Comput., C-32(11): , Nov.1983. Y. Jung, Y. Tak, J. Kim, J. Park, D. Kim, and H. Park. “Efficient FFT Algorithm for OFDM Modulation.” Proceedings of IEEE Region 10 International Conference on Electrical and Electronic Technology. Vol.2 pp , 2001. A. M. Despain. “Very Fast Fourier Transform Algorithms Hardware for Implementation.” IEEE Trans. on Computers, Vol. c-28, No. 5, May 1979 A. –Y. Wu. “CORDIC.” Slides of Advanced VLSI Y. H. Hu. “CORDIC-based VLSI architectures for digital signal processing.” IEEE Signal Processing Magazine. Pp July 1992 J. G. Proakis. D. G. Manolakis. “Digital signal processing” 3rd edition, Prentice Hall 2019/4/7 Owen, Lee

26 Thanks for Your Attention
Q & A ? 2019/4/7 Owen, Lee


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