A fractionally spaced blind equalization algorithm with global convergence

Authors:
Alper T. Erdogan
Affiliations:
EE Department, Koc University, Sariyer, 34450 Istanbul, Turkey
Venue:
Signal Processing
Year:
2008

Citing 4
Cited 1

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Minimization methods for non-differentiable functions
A fractionally spaced blind equalizer based on linear programming

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On convergence analysis of fractionally spaced adaptive blindequalizers

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Fast and low complexity blind equalization via subgradient projections

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Implementation of enhanced fractionally spaced algorithm for blind equalization technology in WSNs

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Abstract

Two different fractionally spaced extensions of the SubGradient based Blind equalization Algorithm (SGBA) are provided. The first one is the direct extension of the linearly constrained SGBA for the symbol spaced setting. The second extension is the weighted and the 2-norm constrained fractionally spaced SGBA (FS-SGBA) algorithm. It is proven that the latter algorithm is globally convergent to a perfect equalization point under the well-known equalizability conditions for the fractionally spaced setting. The simulation results provided illustrates the relative merit of the proposed algorithm in comparison to the state of the art algorithms.