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Danilo Spano

Researcher at University of Luxembourg

Publications -  32
Citations -  1149

Danilo Spano is an academic researcher from University of Luxembourg. The author has contributed to research in topics: Precoding & Zero-forcing precoding. The author has an hindex of 11, co-authored 32 publications receiving 590 citations. Previous affiliations of Danilo Spano include University of Salento.

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Satellite Communications in the New Space Era: A Survey and Future Challenges

TL;DR: In this article, the authors present a survey of the state of the art in satellite communications, while highlighting the most promising open research topics, such as new constellation types, on-board processing capabilities, non-terrestrial networks and space-based data collection/processing.
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A Tutorial on Interference Exploitation via Symbol-Level Precoding: Overview, State-of-the-Art and Future Directions

TL;DR: The definition of constructive interference (CI) is presented and the corresponding mathematical characterization is formulated for popular modulation types, based on which optimization-based precoding techniques are discussed.
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Symbol-Level and Multicast Precoding for Multiuser Multiantenna Downlink: A State-of-the-Art, Classification, and Challenges

TL;DR: A unified view and classification of precoding techniques with respect to two main axes is presented: 1) the switching rate of the precoding weights, leading to the classes of block-level and symbol-level precoding and 2) the number of users that each stream is addressed to, hence unicast, multicast, and broadcast precoding.
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Symbol-Level Precoding for the Nonlinear Multiuser MISO Downlink Channel

TL;DR: Numerical results are presented in a comparative fashion to show the effectiveness of the proposed techniques, which outperform the state-of-the-art symbol-level precoding schemes in terms of spatial peak-to-average power ratio, spatial dynamic range, and symbol error rate over nonlinear channels.
Proceedings ArticleDOI

Per-Antenna Power Minimization in Symbol-Level Precoding

TL;DR: The problem of per-antenna power minimization in symbol-level precoding is formulated and solved, under Quality-of-Service constraints, and the proposed design is optimized in order to control the instantaneous power transmitted by the antennas, and more specifically to limit the power peaks, while guaranteeing some specific target signal-to-noise ratios at the receivers.