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dc.contributor.authorMartinek, Radek
dc.contributor.authorKonečný, Jaromír
dc.contributor.authorKoudelka, Petr
dc.contributor.authorŽídek, Jan
dc.contributor.authorNazeran, Homer
dc.date.accessioned2017-09-01T05:23:31Z
dc.date.available2017-09-01T05:23:31Z
dc.date.issued2017
dc.identifier.citationWireless Personal Communications. 2017, vol. 95, issue 4, p. 4001-4011.cs
dc.identifier.issn0929-6212
dc.identifier.issn1572-834X
dc.identifier.urihttp://hdl.handle.net/10084/120178
dc.description.abstractIn this paper we briefly describe the design, implementation, and evaluation of a novel adaptive optimization approach for the feed-forward software defined equalization (FFSDE) method using the least mean squared (LMS) algorithm. In our design, we adaptively change the filter length (N) and step size (mu) to achieve the optimal bit error rate value. We used a vector signal generator RF PXI-5670 and a vector signal analyzer (VSA) RF PXI-5660 to test the validity of our approach. We implemented our method for the M-ary quadrature amplitude modulation (M-QAM) scheme in the VSA (which served as a receiver). The experimental results showed that we achieved high convergence speed and accuracy for rapidly changing transmitter channel characteristics. The automatic optimal setting feature of the LMS Algorithm parameters N and mu, enabled us to solve the hardware configuration problem for the FFSDE method. Determination of the LMS Algorithm training sequence size for the particular M-QAM allowed us to eliminate redundant data of the training sequence and increase the throughput.cs
dc.language.isoencs
dc.publisherSpringercs
dc.relation.ispartofseriesWireless Personal Communicationscs
dc.relation.urihttps://doi.org/10.1007/s11277-017-4036-3cs
dc.rights© Springer Science+Business Media New York 2017cs
dc.subjectfeed-forward software defined equalization (FFSDE)cs
dc.subjectleast mean square (LMS)cs
dc.subjectM-QAMcs
dc.subjectmodulation error ratio (MER)cs
dc.subjectbit error ratio (BER)cs
dc.titleAdaptive optimization of control parameters for feed-forward software defined equalizationcs
dc.typearticlecs
dc.identifier.doi10.1007/s11277-017-4036-3
dc.type.statusPeer-reviewedcs
dc.description.sourceWeb of Sciencecs
dc.description.volume95cs
dc.description.issue4cs
dc.description.lastpage4011cs
dc.description.firstpage4001cs
dc.identifier.wos000407399800026


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