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Daniel Benevides da Costa

Researcher at National Yunlin University of Science and Technology

Publications -  331
Citations -  6469

Daniel Benevides da Costa is an academic researcher from National Yunlin University of Science and Technology. The author has contributed to research in topics: Fading & Relay. The author has an hindex of 36, co-authored 289 publications receiving 4875 citations. Previous affiliations of Daniel Benevides da Costa include State University of Campinas & Université du Québec.

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Cognitive Amplify-and-Forward Relay Networks Over Nakagami- $m$ Fading

TL;DR: The outage probability of dual-hop cognitive amplify-and-forward relay networks subject to independent non-identically distributed Nakagami-m fading is examined and it is revealed that the diversity order is strictly defined by the minimum fading severity between the two hops of the secondary network.
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Cooperative dual-hop relaying systems with beamforming over nakagami-m fading channels

TL;DR: This paper investigates the end-to-end performance of dual-hop relaying systems with beamforming over Nakagami-m fading channels with semi-blind (fixed-gain) relays with single antennas, and source and destination nodes equipped with multiple antennas.
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A BNBF User Selection Scheme for NOMA-Based Cooperative Relaying Systems With SWIPT

TL;DR: This letter investigates the outage performance of cooperative relaying transmissions in two-user non-orthogonal multiple access systems, wherein simultaneous wireless information and power transfer is employed at the near users to power their relaying operations.
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Asymptotic Analysis of Cooperative Diversity Systems With Relay Selection in a Spectrum-Sharing Scenario

TL;DR: Three low-complexity relay-selection strategies, namely, selective amplify and forward, selective decode and forward (S-DF), and amplified and forward with partial relay selection (PRS-AF) in a spectrum-sharing scenario are studied and the diversity and coding gains are derived and compared.
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Cognitive Amplify-and-Forward Relaying with Best Relay Selection in Non-Identical Rayleigh Fading

TL;DR: This paper investigates several important performance metrics of cognitive amplify-and-forward (AF) relay networks with a best relay selection strategy and subject to non-identical Rayleigh fading with the result that the diversity gain is defined by the number of relays pertaining to the SU network, being therefore not affected by the interference power constraint of the PU network.