activity
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

collaborators

15 papers

cs.NI2022

An Open Framework to Model Diffraction by Dynamic Blockers in Millimeter Wave Simulations

Paolo Testolina, Mattia Lecci, Alessandro Traspadini +1

The millimeter wave (mmWave) band will be exploited to address the growing demand for high data rates and low latency. The higher frequencies, however, are prone to limitations on…

cs.NI2022★ 1 cited

Temporal Characterization of VR Traffic for Network Slicing Requirement Definition

Federico Chiariotti, Matteo Drago, Paolo Testolina +3

Over the past few years, the concept of VR has attracted increasing interest thanks to its extensive industrial and commercial applications. Currently, the 3D models of the virtual…

cs.NI2022

Temporal Characterization of XR Traffic with Application to Predictive Network Slicing

Mattia Lecci, Federico Chiariotti, Matteo Drago +2

Over the past few years, eXtended Reality (XR) has attracted increasing interest thanks to its extensive industrial and commercial applications, and its popularity is expected to r…

cs.NI2021

An Open Framework for Analyzing and Modeling XR Network Traffic

Mattia Lecci, Matteo Drago, Andrea Zanella +1

Thanks to recent advancements in the technology, eXtended Reality (XR) applications are gaining a lot of momentum, and they will surely become increasingly popular in the next deca…

cs.NI2021

A Simulation Framework for Contention-Free Scheduling on WiGig

Matteo Drago, Tommy Azzino, Mattia Lecci +2

The latest IEEE 802.11 amendments provide support to directional communications in the Millimeter Wave spectrum and, thanks to the wide bandwidth available at such frequencies, mak…

cs.NI2021★ 25 cited

An ns-3 Implementation of a Bursty Traffic Framework for Virtual Reality Sources

Mattia Lecci, Andrea Zanella, Michele Zorzi

Next-generation wireless communication technologies will allow users to obtain unprecedented performance, paving the way to new and immersive applications. A prominent application…

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…

cs.NI2019★ 7 cited

Scalable and Accurate Modeling of the Millimeter Wave Channel

Paolo Testolina, Mattia Lecci, Michele Polese +2

Communication at millimeter wave (mmWave) frequencies is one of the main novelties introduced in the 5th generation (5G) of cellular networks. The opportunities and challenges asso…

cs.IT2019★ 7 cited

Enabling Simulation-Based Optimization Through Machine Learning: A Case Study on Antenna Design

Paolo Testolina, Mattia Lecci, Mattia Rebato +5

Complex phenomena are generally modeled with sophisticated simulators that, depending on their accuracy, can be very demanding in terms of computational resources and simulation ti…