Using the Fireworks Algorithm for ML Detection of Nonlinear OFDM

dc.contributor.authorGuerreiro, João
dc.contributor.authorDinis, Rui
dc.contributor.authorCarvalho, Paulo Montezuma
dc.date.accessioned2018-01-13T14:36:33Z
dc.date.available2018-01-13T14:36:33Z
dc.date.issued2017-09
dc.description.abstractOrthogonal frequency division multiplexing (OFDM) schemes have high envelope fluctuations and peak-to-average power ratio (PAPR), making them very prone to nonlinear distortion effects, which can affect significantly the performance when conventional receivers are employed. However, it was recently shown that strong nonlinear distortion effects on OFDM signals do not necessarily lead to performance degradation. In fact, Nonlinear OFDM schemes can outperform linear ones when optimum maximum likelihood (ML) receivers are employed. In this paper, we considered OFDM schemes with strong nonlinear distortion effects and we proposed a low-complexity detection scheme able to approach the optimum ML performance. Our technique is based on the fireworks algorithm (FWA) and allows excellent trade-offs between performance and complexity
dc.identifier.urihttp://hdl.handle.net/11144/3389
dc.language.isoengpor
dc.peerreviewedyespor
dc.publisherIEEEpor
dc.rightsopen accesspor
dc.subjectOFDM
dc.subjectML performance
dc.titleUsing the Fireworks Algorithm for ML Detection of Nonlinear OFDMpor
dc.typeconferenceObjectpor
degois.publication.titleVTC'17 (Fall)por
dspace.entity.typePublicationen

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