Using the Fireworks Algorithm for ML Detection of Nonlinear OFDM
Date
2017-09
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Coadvisor
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Publisher
IEEE
Language
English
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Abstract
Orthogonal 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
Keywords
OFDM, ML performance
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conferenceObject
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Open Access