New blind equalization technique for Constant Modulus Algorithm (CMA)

dc.AffiliationOctober University for modern sciences and Arts (MSA)
dc.contributor.authorNassar A.M.
dc.contributor.authorEl Nahal W.
dc.contributor.otherElectronics and Communication Dept.
dc.contributor.otherFaculty of Engineering
dc.contributor.otherCairo University
dc.contributor.otherGiza
dc.contributor.otherEgypt; MSA University
dc.contributor.otherCommunication Dept.
dc.contributor.other6th October
dc.contributor.otherEgypt
dc.date.accessioned2020-01-25T19:58:32Z
dc.date.available2020-01-25T19:58:32Z
dc.date.issued2010
dc.descriptionScopus
dc.description.abstractEqualization plays an important role for the communication system receiver to correctly recover the symbol send by the transmitter, where the received signals may contain additive noise and intersymbol interference (ISI). Blind equalization is a technique of many equalization techniques at which the transmitted symbols over a communication channel can be recovered without the aid of training sequences, recently blind equalizers have a wide range of research interest since they do not require training sequence and extra bandwidth, but the main weaknesses of these approaches are their high computational complexity and slow adaptation, so different algorithms are presented to avoid this nature. The most popular blind algorithm which has a wide acceptance is the Constant Modulus Algorithm (CMA). The performance of CMA suffers from slow convergence rate or adaptation which corresponds to various transmission delays especially in wireless communication systems, which require higher speed and lower bandwidth. This paper introduces a new blind equalization technique, the Exponentially Weighted Step-size Recursive Least Squares Constant Modulus Algorithm (EXP-RLS-CMA), based upon the combination between the Exponentially Weighted Step-size Recursive Least Squares (EXP-RLS) algorithm and the Constant Modulus Algorithm (CMA), by providing several assumptions to obtain faster convergence rate to an optimal delay where the Mean Squared Error (MSE) is minimum, and so this selected algorithm can be implemented in digital system to improve the receiver performance. Simulations are presented to show the excellence of this technique, and the main parameters of concern to evaluate the performance are, the rate of convergence, the mean square error (MSE), and the average error versus different signal-to-noise ratios. �2010 IEEE.en_US
dc.identifier.doihttps://doi.org/10.1109/CQR.2010.5619909
dc.identifier.isbn9.78E+12
dc.identifier.otherhttps://doi.org/10.1109/CQR.2010.5619909
dc.identifier.urihttps://ieeexplore.ieee.org/document/5619909
dc.language.isoEnglishen_US
dc.relation.ispartofseries2010 IEEE International Workshop Technical Committee on Communications Quality and Reliability, CQR 2010
dc.subjectBlind equalizationen_US
dc.subjectChannel equalizationen_US
dc.subjectConstant Modulus Algorithm (CMA)en_US
dc.subjectExponentially weighted step-size Recursive Least Squares (EXP-RLS) algorithmen_US
dc.subjectRecursive Least Squared (RLS) algorithmen_US
dc.subjectAverage errorsen_US
dc.subjectBlind algorithmsen_US
dc.subjectBlind equalizeren_US
dc.subjectChannel equalizationen_US
dc.subjectCommunication channelen_US
dc.subjectConstant modulus algorithmsen_US
dc.subjectConvergence ratesen_US
dc.subjectDigital systemen_US
dc.subjectEqualization techniquesen_US
dc.subjectExponentially weighted step-size recursive least squares algorithmsen_US
dc.subjectFaster convergenceen_US
dc.subjectMain parametersen_US
dc.subjectMean squared erroren_US
dc.subjectOptimal delayen_US
dc.subjectRate of convergenceen_US
dc.subjectReceived signalsen_US
dc.subjectReceiver performanceen_US
dc.subjectRecursive least squared algorithmsen_US
dc.subjectRecursive least squaresen_US
dc.subjectTraining sequencesen_US
dc.subjectTransmission delaysen_US
dc.subjectWireless communication systemen_US
dc.subjectAlgorithmsen_US
dc.subjectApproximation theoryen_US
dc.subjectBlind equalizationen_US
dc.subjectCommunication systemsen_US
dc.subjectComputational complexityen_US
dc.subjectGlobal system for mobile communicationsen_US
dc.subjectIntersymbol interferenceen_US
dc.subjectMean square erroren_US
dc.subjectRadio systemsen_US
dc.subjectSignal to noise ratioen_US
dc.subjectWireless telecommunication systemsen_US
dc.subjectConvergence of numerical methodsen_US
dc.titleNew blind equalization technique for Constant Modulus Algorithm (CMA)en_US
dc.typeConference Paperen_US
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