High Performance of LMS Adaptive Filter Using LUT

Abstract
The presents an efficient implementation of adaptive filter by minimizing the area and the power consumed with the use of least mean square algorithm. The memory based structures are replaced with the MAC units in order to achieve the optimized area and power. The LUTs are memory based units used for the design of the filter.
Keywords:MAC, LUT, memory, adaptive filter.
INTRODUCTION
The term ‘filter’ is often applied to any device or system that processes incoming signals or other data in such a way as to eliminate noise, or predict the next input signal from moment to moment[1] . During the last decades the adaptive filters have attracted many researches due to the property of their selfdesigning. Hence, an adaptive filter is a computational device that attempts to model the relationship between two signals in an iterative manner. Adaptive filters are often realized either with a set of logic operations implemented on a field programmable gate array (FPGA) or with a set of programming instructions running on a microprocessor or on a digital signal processor. The adaptive filter is defined by 4 main aspects: 1. The signal processed by a filter. 2. The structure defines how the output of the filter is computed from its input signal. 3. The parameters within this structure that can be iteratively changed to alter the filter’s input-output relationship. 4. The algorithm that describes how the parameters are adjusted from one time instant to next. The adaptive filtering consists of 2 basic operations: the filtering process and adaptation process. In filtering process, an output signal is generated from an input data signal using a digital filter. In the adaptation process, consists of an adaptation algorithm which adjusts the coefficients of the filter to minimize the desired function.
CONCLUSION
An efficient adaptive filter has being designed and simulated using Xilinx so comparing with the literature survey [2], the area and the power has been minimized.