Design and Implementation of Low Complexity LMS Adaptive Filter

Adaptive filter is a computational device that iteratively models the relationship between the input and output signals of a filter in the real time. It works based on an adaptive algorithm that self-adjusts the coefficients of the linear filter iteratively to minimize the power of e(n). The LMS algorithm is one of the most popularly used adaptive algorithm among others which adjusts the coefficients of adaptive filters. There are two main computing blocks in the direct-form LMS adaptive filter, namely, the error-computation block and the weight-update block which decides the efficiency of the filter. In this paper, adaptive filter is implemented in two different architectures namely, zero adaptation delay adaptive filter and two adaptation delay adaptivefilter which result in low power consumption and less area complexity.Zero adaptation delay adaptive filter provides nearly 52% savings in area and the delay decreases by 26% in two adaptation 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.