Reconfigurable FIR Filter using Multipliers

Abstract

In signal processing, a finite impulse response (FIR) filter is a filter whose impulse response (or response to any finite length input) is of finite duration, because it settles to zero in finite time. This is in contrast to infinite impulse response (IIR) filters, which may have internal feedback and may continue to respond indefinitely (usually decaying).The impulse response (that is, the output in response to a Kronecker delta input) of an Nth-order discrete-time FIR filter lasts exactly N + 1 samples (from first nonzero element through last nonzero element) before it then settles to zero. FIR filters can be discrete-time or continuous-time, and digital or analog. In this paper, FIR filter multipliers are extensively characterized with power simulations, providing a methodology for the perturbation of the coefficients of baseline filters at the algorithm level to trade-off reduced power consumption for filter quality. The proposed optimization technique does not require any hardware overhead and it enables the possibility of scaling the power consumption of the filter at runtime, while ensuring the full baseline performance of any programmed filter whenever it is required. The analyzed FIR filters were fabricated in a 28nm FD-SOI test chip and measured at a near-threshold, 600mV supply voltage.

Country : India

1 M.Punitha2 K.Preethi3 G.Kanagaraj

  1. PG Scholar, Department of VLSI, AVS Engineering College, Salem, Tamilnadu, India
  2. Assistant Professor, Department of ECE, AVS Engineering College, Salem, Tamilnadu, India
  3. Assistant Professor, Department of ECE, AVS Engineering College, Salem, Tamilnadu, India

IRJIET, Volume 2, Issue 2, April 2018 pp. 5-8

References

  1. K. Bhardwaj, P. S. Mane, and J. Henkel, “Power- and area-efficient approximate wallace tree multiplier for error-resilient systems,” in Proc. 15th Int. Symp. Quality Electron. Design (ISQED), Mar. 2015, pp. 263–269.
  2. J. Chen, C. H. Chang, F. Feng, W. Ding, and J. Ding, “Novel design algorithm for low complexity programmable FIR filters based on extended double base number system,” IEEE Trans. Circuits Syst. I, Reg. Papers, vol. 62, no. 1, pp. 224–233, Jan. 2016.
  3. P. Kulkarni, P. Gupta, and M. Ercegovac, “Trading accuracy for power with an underdesigned multiplier architecture,” in Proc. 24th Int. Conf. VLSI Design, Jan. 2015, pp. 346–351.
  4. C.-H. Lin and I.-C. Lin, “High accuracy approximate multiplier with error correction,” in Proc. IEEE 31st Int. Conf. Compute. Design (ICCD), Oct. 2014, pp. 33–38.
  5. C. Liu, J. Han, and F. Lombardi, “A low-power, high-performance approximate multiplier with configurable partial error recovery,” in Proc. Design, Autom. Test Eur. Conf. Exhibit. (DATE), Mar. 2014, pp. 1–4.
  6. C. Neau, K. Muhammad, and K. Roy, “Low complexity FIR filters using factorization of perturbed coefficients,” in Proc. Design, Autom. Test Eur. Conf. Exhibit. (DATE), 2014, pp. 268–272.
  7. S. Y. Park and P. K. Meher, “Efficient FPGA and ASIC realizations of a DA-based reconfigurable FIR digital filter,” IEEE Trans. Circuits Syst. II, Exp. Briefs, vol. 61, no. 7, pp. 511–515, Jul. 2015.
  8. P. N. Whatmough, S. Das, D. M. Bull,     and I. Darwazeh, “Circuit-level timing error tolerance for  low-power DSP filters and transforms,” IEEE Trans. Very Large Scale Integr. (VLSI) Syst., vol.  21, no. 6, pp. 989–999, Jun. 2016.