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Recursive Probability Estimation of Decision Feedback Equalizers based on Constant Modulus Errors
Author(s) -
Namyong Kim
Publication year - 2015
Publication title -
journal of the korea academia-industrial cooperation society
Language(s) - English
Resource type - Journals
eISSN - 2288-4688
pISSN - 1975-4701
DOI - 10.5762/kais.2015.16.3.2172
Subject(s) - constant (computer programming) , mathematics , computational complexity theory , algorithm , probability of error , zero (linguistics) , distortion (music) , modulus , compensation (psychology) , control theory (sociology) , computer science , artificial intelligence , psychology , amplifier , computer network , geometry , control (management) , bandwidth (computing) , psychoanalysis , programming language , linguistics , philosophy
The DF-MZEP-CME (decision feedback – maximum zero-error probability for constant modulus errors) algorithm that makes the probability for constant modulus error (CME) close to zero and employs decision feedback(DF) structures shows more improved performance in channel distortion compensation. However the DF-MZEP-CMEalgorithm has a computational complexity proportional to a sample size for probability estimation and this propertyplays a role of an obstacle in practical implementation. In this paper, the gradient of DF-MZEP-CME is proposedto be estimated recursively and shown to solve the computational problem by making the algorithm independent ofthe sample size. For a sample size N, the conventional method has 10N multiplications but the proposed has only20 regardless of N. Also the recursive gradient estimation for weight update is kept in continuity from the initial stateto the steady state without any error propagation. Key Words : Constant modulus error, Probability, Decision-feedback, Recursive gradient, Computational complexity.

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