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Dario Fertonani

Researcher at Arizona State University

Publications -  47
Citations -  1349

Dario Fertonani is an academic researcher from Arizona State University. The author has contributed to research in topics: Communication channel & Decoding methods. The author has an hindex of 19, co-authored 47 publications receiving 1281 citations. Previous affiliations of Dario Fertonani include Sant'Anna School of Advanced Studies & University of Parma.

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Time-frequency packing for linear modulations: spectral efficiency and practical detection schemes

TL;DR: It is shown that a more involved equalization algorithm allows to achieve an excellent bit-error-rate performance, even when error-correcting codes designed for the Gaussian-noise limited channel are employed, and thus does not require a complete redesign of the coding scheme.
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Mitigation of Intercarrier Interference for OFDM Over Time-Varying Underwater Acoustic Channels

TL;DR: In this paper, two ICI-mitigation schemes are proposed for cyclic-prefixed OFDM over time-varying UWA channels. But the ICI coefficients are not explicitly estimated, and no explicit ICI estimation is performed, and detection is based on an adaptive decision-feedback equalizer applied in the frequency domain across adjacent subcarriers.
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SISO Detection Over Linear Channels With Linear Complexity in the Number of Interferers

TL;DR: This work considers detection over linear channels impaired by additive white Gaussian noise and proposes novel detection algorithms derived by applying the sum-product algorithm to a suitably designed factor graph that can approach or even outperform the performance provided by much more complex algorithms.
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On reliable communications over channels impaired by bursty impulse noise

TL;DR: A two-state Markov model is adopted that allows to describe the typical bursty nature of the impulse noise, in contrast to the memoryless models generally considered in the literature, for digital communications over channels impaired by impulse noise.
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Novel Bounds on the Capacity of the Binary Deletion Channel

TL;DR: Novel bounds on the capacity of the independent and identically distributed binary deletion channel are presented and two simple lower bounds are derived, for low values of the deletion probability, which are almost as good as the best existing lower bounds.