Design and implementation of low complexity LMS adaptive filter

Document Type : Research Paper


1 ME VLSI, ECE, PSG College of Technology, India

2 Department of ECE, PSG College of Technology Coimbatore, India

3 Department of ECE,PSG College of Technology, India


An adaptive filter is a real-time computational device that iteratively simulates the relationship between a filter's input and output signals. It is based on an adaptive algorithm that iteratively self-adjusts the linear filter coefficients to decrease the power of e. (n). The LMS method is one of the most widely used adaptive algorithms for adjusting the coefficients of adaptive filters, among others. The error-computation block and the weight-update block, which determine the filter's efficiency, are the two key computing blocks of the direct-form LMS adaptive filter. In this paper, adaptive filter is implemented in two different architectures namely, zero adaptation delay adaptive filter and two adaptations delay adaptive filter which results in low power consumption and less area complexity. Zero adaptation delay adaptive filter provides nearly 52\% savings in the area and the delay decreases by 26\% in two adaptations delay adaptive filter over the conventional adaptive filter. Hence based on the required speed and area for the application, any one of the proposed structures can be used.


[1] W.A. Harrison, J.S. Lim and E. Singer, A new application of adaptive noise cancellation, IEEE Trans. Acoust.
Speech, Signal Process. 34(1) (1986) 21–27.
[2] S. Haykin and B. Widrow, Least-Mean-Square Adaptive Filters, Hoboken, NJ, USA: Wiley-Interscience, 2003.
[3] R.H. Hearn, J.R. Zeidler, E. Dong and R.C. Goodlin, Adaptive noise cancelling: principles and applications,
Proc. IEEE. 63(12) (1975) 1692–1716.
[4] H. Kaur and R. Talwar, Performance comparison of adaptive filter algorithms for noise cancellation, IEEE Signal
Process Lett. 16(1) (2009).
[5] P. Kumar Meher and S. Yoon Park, Critical-path analysis and low-complexity implementation of the LMS adaptive
algorithm, IEEE Trans Circuits Syst I Regul Pap. 61(3) (2014) 778–788.
[6] G. Long, F. Ling and J.G. Proakis, The LMS algorithm with delayed coefficient adaptation, IEEE Trans. Acoust.,
Speech. Signal Process. 37(9) (1989) 1397–1405.
[7] P.K. Meher and M. Maheshwari, A high-speed FIR adaptive filter architecture using a modified delayed LMS
algorithm, Proc. IEEE Int. Symp. Circuits Syst. (2011) 121–124.
[8] M.D. Meyer and D.P. Agrawal, Amodular pipelined implementation of a delayed LMS transversal adaptive filter,
Proc. IEEE Int. Symp. Circuits Syst. (1990) 1943–1946.
Volume 12, Special Issue
December 2021
Pages 1827-1833
  • Receive Date: 05 August 2021
  • Revise Date: 15 October 2021
  • Accept Date: 07 November 2021