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FPGA Implementation of LMS Algorithm Used in Adaptive Equalizer


Affiliations
1 Gandhi Institute for Technological Advancement (GITA) /ECE, Bhubaneswar, Odisha, India.
 

Least mean squares (LMS) algorithms are used in adaptive filters to find the filter coefficients that relate to producing the least mean squares of the error signal which is the difference between the desired and the actual signal. It is a stochastic gradient descent method in that the filter is only adapted based on the error at the current time. The gradient descent method finds a minimum, by taking steps in the direction negative of the gradient, by adjusting the filter coefficients to minimize the error. The aim of this paper is to implement LMS algorithm in FPGA in wireless communication system. The implementation results shows the error minimize technique. It is tested in hardware using FPGA kit.
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  • FPGA Implementation of LMS Algorithm Used in Adaptive Equalizer

Abstract Views: 136  |  PDF Views: 93

Authors

Kaliprasanna Swain
Gandhi Institute for Technological Advancement (GITA) /ECE, Bhubaneswar, Odisha, India.
Manoj Kumar Sahoo
Gandhi Institute for Technological Advancement (GITA) /ECE, Bhubaneswar, Odisha, India.

Abstract


Least mean squares (LMS) algorithms are used in adaptive filters to find the filter coefficients that relate to producing the least mean squares of the error signal which is the difference between the desired and the actual signal. It is a stochastic gradient descent method in that the filter is only adapted based on the error at the current time. The gradient descent method finds a minimum, by taking steps in the direction negative of the gradient, by adjusting the filter coefficients to minimize the error. The aim of this paper is to implement LMS algorithm in FPGA in wireless communication system. The implementation results shows the error minimize technique. It is tested in hardware using FPGA kit.

References