AIAug 10, 2012

Elimination of ISI Using Improved LMS Based Decision Feedback Equalizer

arXiv:1208.2199v1
AI Analysis

This addresses the problem of slow signal recovery in communication systems, but it is incremental as it builds on existing LMS and DFE methods.

The paper tackled the slow convergence of the Least Mean Square algorithm in Decision Feedback Equalizers for removing Inter Symbol Interference by modifying the algorithm to update weights based on disturbance severity, resulting in increased convergence speed.

This paper deals with the implementation of Least Mean Square (LMS) algorithm in Decision Feedback Equalizer (DFE) for removal of Inter Symbol Interference (ISI) at the receiver. The channel disrupts the transmitted signal by spreading it in time. Although, the LMS algorithm is robust and reliable, it is slow in convergence. In order to increase the speed of convergence, modifications have been made in the algorithm where the weights get updated depending on the severity of disturbance.

Foundations

The foundational work for this paper's niche, ranked by how specifically the neighbourhood builds on it — not by global fame.

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