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Review of Computer Engineering Research

December 2020, Volume 7, 2, pp 73-85

LMS Algorithm for Adaptive Transversal Equalization of a Linear Dispersive Communication Channel

Farrukh Arslan

Farrukh Arslan 1


  1. School of Electrical and Computer Engineering, Purdue University, West Lafayette, USA. 1

on Google Scholar
on PubMed

Pages: 73-85

DOI: 10.18488/journal.76.2020.72.73.85

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Article History:

Received: 21 July, 2020
Revised: 24 August, 2020
Accepted: 10 September, 2020
Published: 01 October, 2020


Abstract:

The presence of any type of distortion in communication system, regardless of the causes, is undesirable and undeniably has a negative impacts on the system in general and therefore it is necessary to eliminate its effects. This study employs one of the well-known algorithms for adaptive equalization of linear dispersive communication channel which is Least Mean Square (LMS) algorithm. The LMS technique is basically utilized to eliminate the noise in communication channel. The novelty of this paper includes the profoundly analyzing of the influence of rate of convergence, miss-adjustment, computational requirement, and sensitivity to Eigen-value spread in sufficient details in a simple and plain way. Moreover, the system performance improvement employing the feedback equalizer technique is intensively presented which shows that our methodology is very effective to eliminate the noise in the system. The simulation work has been performed with MATLAB software.
Contribution/ Originality
This study uses new estimation methodology which is regarded as profoundly analyzing of the influence of rate of convergence, miss-adjustment, computational requirement, and sensitivity to Eigen-value spread in sufficient details in a simple and plain way.

Keywords:

Adaptive signal processing, Adaptive transversal filter (ATF), Adaptive equalization, Least mean square (LMS) algorithm, Simulation, MATLAB.

Reference:

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Statistics:

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Funding:

This study received no specific financial support.

Competing Interests:

The author declares that there are no conflicts of interests regarding the publication of this paper.

Acknowledgement:


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