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| dc.contributor.author | Nassar A.M. | |
| dc.contributor.author | El. Nahal W. | |
| dc.contributor.other | Electronics and Communication Dept. | |
| dc.contributor.other | Faculty of Engineering | |
| dc.contributor.other | Cairo University | |
| dc.contributor.other | Giza | |
| dc.contributor.other | Egypt; Communication Dept. | |
| dc.contributor.other | MSA University | |
| dc.contributor.other | Egypt | |
| dc.date.accessioned | 2020-01-25T19:58:33Z | |
| dc.date.available | 2020-01-25T19:58:33Z | |
| dc.date.issued | 2010 | |
| dc.identifier.isbn | 9.78E+12 | |
| dc.identifier.other | https://doi.org/10.1109/ICENCO.2010.5720442 | |
| dc.identifier.uri | https://ieeexplore.ieee.org/document/5720442 | |
| dc.description | Scopus | |
| dc.description.abstract | 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. 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. � 2011 IEEE. | en_US |
| dc.language.iso | English | en_US |
| dc.publisher | IEEE Computer Society | en_US |
| dc.relation.ispartofseries | ICENCO'2010 - 2010 International Computer Engineering Conference: Expanding Information Society Frontiers | |
| dc.subject | Blind equalization | en_US |
| dc.subject | Channel equalization | en_US |
| dc.subject | Constant Modulus Algorithm (CMA) | en_US |
| dc.subject | Exponentially Weighted Step-size Recursive Least Squares (EXP-RLS) algorithm | en_US |
| dc.subject | Recursive least squared (RLS) algorithm | en_US |
| dc.subject | Errors | en_US |
| dc.subject | Mean square error | en_US |
| dc.subject | Signal to noise ratio | en_US |
| dc.subject | Adaptive blind equalization | en_US |
| dc.subject | Channel equalization | en_US |
| dc.subject | Constant modulus algorithms | en_US |
| dc.subject | Equalization techniques | en_US |
| dc.subject | Rate of convergence | en_US |
| dc.subject | Receiver performance | en_US |
| dc.subject | Recursive least square (RLS) | en_US |
| dc.subject | Research interests | en_US |
| dc.subject | Blind equalization | en_US |
| dc.title | Adaptive blind equalization technique to enhance the Constant Modulus Algorithm performance | en_US |
| dc.type | Conference Paper | en_US |
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| dcterms.source | Scopus | |
| dc.identifier.doi | https://doi.org/10.1109/ICENCO.2010.5720442 | |
| dc.Affiliation | October University for modern sciences and Arts (MSA) |
