New blind equalization technique for Constant Modulus Algorithm (CMA)
dc.Affiliation | October University for modern sciences and Arts (MSA) | |
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; MSA University | |
dc.contributor.other | Communication Dept. | |
dc.contributor.other | 6th October | |
dc.contributor.other | Egypt | |
dc.date.accessioned | 2020-01-25T19:58:32Z | |
dc.date.available | 2020-01-25T19:58:32Z | |
dc.date.issued | 2010 | |
dc.description | Scopus | |
dc.description.abstract | Equalization 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.doi | https://doi.org/10.1109/CQR.2010.5619909 | |
dc.identifier.isbn | 9.78E+12 | |
dc.identifier.other | https://doi.org/10.1109/CQR.2010.5619909 | |
dc.identifier.uri | https://ieeexplore.ieee.org/document/5619909 | |
dc.language.iso | English | en_US |
dc.relation.ispartofseries | 2010 IEEE International Workshop Technical Committee on Communications Quality and Reliability, CQR 2010 | |
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 | Average errors | en_US |
dc.subject | Blind algorithms | en_US |
dc.subject | Blind equalizer | en_US |
dc.subject | Channel equalization | en_US |
dc.subject | Communication channel | en_US |
dc.subject | Constant modulus algorithms | en_US |
dc.subject | Convergence rates | en_US |
dc.subject | Digital system | en_US |
dc.subject | Equalization techniques | en_US |
dc.subject | Exponentially weighted step-size recursive least squares algorithms | en_US |
dc.subject | Faster convergence | en_US |
dc.subject | Main parameters | en_US |
dc.subject | Mean squared error | en_US |
dc.subject | Optimal delay | en_US |
dc.subject | Rate of convergence | en_US |
dc.subject | Received signals | en_US |
dc.subject | Receiver performance | en_US |
dc.subject | Recursive least squared algorithms | en_US |
dc.subject | Recursive least squares | en_US |
dc.subject | Training sequences | en_US |
dc.subject | Transmission delays | en_US |
dc.subject | Wireless communication system | en_US |
dc.subject | Algorithms | en_US |
dc.subject | Approximation theory | en_US |
dc.subject | Blind equalization | en_US |
dc.subject | Communication systems | en_US |
dc.subject | Computational complexity | en_US |
dc.subject | Global system for mobile communications | en_US |
dc.subject | Intersymbol interference | en_US |
dc.subject | Mean square error | en_US |
dc.subject | Radio systems | en_US |
dc.subject | Signal to noise ratio | en_US |
dc.subject | Wireless telecommunication systems | en_US |
dc.subject | Convergence of numerical methods | en_US |
dc.title | New blind equalization technique for Constant Modulus Algorithm (CMA) | en_US |
dc.type | Conference Paper | en_US |
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dcterms.source | Scopus |
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