Efficient FPGA Implementation of the Delayed LMS Algorithm

This paper presents the design and implementation of an adaptive filter utilizing the Delayed Least Mean Square (D-LMS) algorithm, optimized for hardware efficiency using Verilog HDL. The D-LMS algorithm improves upon the conventional Least Mean Square (LMS) algorithm by introducing a delay in the weight update process, which decouples error calculation and weight update steps. This modification significantly reduces the critical path, resulting in faster convergence and reduced computational complexity. Key components of the design, such as block carry look-ahead adders and Wallace tree multipliers, were optimized to enhance performance and minimize resource usage. The design was implemented on an FPGA platform, and simulation results show improvements in convergence speed, power consumption, and resource utilization compared to traditional LMS-based adaptive filters. This study demonstrates the practical advantages of the D-LMS algorithm in real-time signal processing applications, including noise cancellation, communication systems, and biomedical signal enhancement.