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20192022
most citedSimplified Ray Tracing for the Millimeter Wave Channel: A Performance Evaluation

35 citations · 121 across the 14 of their papers we have counts for

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Showing 2020Show all

7 papers · 1 filter

eess.SP2020

A Full-Stack Open-Source Framework for Antenna and Beamforming Evaluation in mmWave 5G NR

Mattia Lecci, Tommaso Zugno, Silvia Zampato +1

Millimeter wave (mmWave) communication represents one of the main innovations of the next generation of wireless technologies, allowing users to reach unprecedented data rates. To…

cs.NI2020

Exploiting Scheduled Access Features of mmWave WLANs for Periodic Traffic Sources

Mattia Lecci, Matteo Drago, Andrea Zanella +1

Many current and future multimedia and industrial applications, like video streaming, eXtended Reality or remote robot control, are characterized by periodic data transmissions wit…

cs.NI2020★ 6 cited

The challenges of Scheduling and Resource Allocation in IEEE 802.11ad/ay

Salman Mohebi, Mattia Lecci, Andrea Zanella +1

The IEEE 802.11ad WiFi amendment enables short-range multi-gigabit communications in the unlicensed 60~GHz spectrum, unlocking new interesting applications such as wireless Augment…

eess.SP2020★ 3 cited

Accuracy vs. Complexity for mmWave Ray-Tracing: A Full Stack Perspective

Mattia Lecci, Paolo Testolina, Michele Polese +2

The millimeter wave (mmWave) band will provide multi-gigabits-per-second connectivity in the radio access of future wireless systems. The high propagation loss in this portion of t…

eess.SP2020★ 21 cited

Quasi-Deterministic Channel Model for mmWaves: Mathematical Formalization and Validation

Mattia Lecci, Michele Polese, Chiehping Lai +4

5G and beyond networks will use, for the first time ever, the millimeter wave (mmWave) spectrum for mobile communications. Accurate performance evaluation is fundamental to the des…

eess.SP2020★ 35 cited

Simplified Ray Tracing for the Millimeter Wave Channel: A Performance Evaluation

Mattia Lecci, Paolo Testolina, Marco Giordani +6

Millimeter-wave (mmWave) communication is one of the cornerstone innovations of fifth-generation (5G) wireless networks, thanks to the massive bandwidth available in these frequenc…

cs.NI2020★ 16 cited

Machine Learning-aided Design of Thinned Antenna Arrays for Optimized Network Level Performance

Mattia Lecci, Paolo Testolina, Mattia Rebato +2

With the advent of millimeter wave (mmWave) communications, the combination of a detailed 5G network simulator with an accurate antenna radiation model is required to analyze the r…