Education
- Ph.D. in Information Engineering - University of Padova, Italy (2022)
- M.Sc. in Telecommunication Engineering - University of Padova, Italy (2018)
- B.Sc. in Information Engineering - University of Padova, Italy (2016)
Research Interests
- Non-Terrestrial Networks
- Spectrum Sharing and Coexistence
- 5G and beyond cellular networks
Paolo Testolina is a Research Scientist at the Wireless Networks and Embedded Systems (WiNES) Laboratory and at the Ultrabroadband Nanonetworking (UN) Laboratory at the Institute for the Wireless Internet of Things, with Prof. Tommaso Melodia and Prof. Josep Jornet. His research focuses on studying and designing wireless communications systems, with a keen interest on channel modeling, spectrum science and everything space-related.
Publications
Evaluating cellular systems, from 5G New Radio (NR) and 5G-Advanced to 6G, is challenging because the performance emerges from the tight coupling of propagation, beam management, scheduling, and higher-layer interactions. System-level simulation is therefore indispensable, yet the vast majority of studies rely on the statistical 3GPP channel models. These are well suited to capture average behavior across many statistical realizations, but cannot reproduce site-specific phenomena such as corner diffraction, street-canyon blockage, or deterministic line-of-sight conditions and angle-of-departure/arrival relationships that drive directional links. This paper extends 5G-LENA, an NR module for the system-level Network Simulator 3 (ns-3), with a trace-based channel model that processes the Multipath Components (MPCs) obtained from external ray-tracers (e.g., Sionna Ray Tracer (RT)) or measurement campaigns. Our module constructs frequency-domain channel matrices and feeds them to the existing Physical (PHY)/Medium Access Control (MAC) stack without any further modifications. The result is a geometry-based channel model that remains fully compatible with the standard 3GPP implementation in 5G-LENA, while delivering site-specific geometric fidelity. This new module provides a key building block toward Digital Twin (DT) capabilities by offering realistic site-specific channel modeling, unlocking studies that require site awareness, including beam management, blockage mitigation, and environment-aware sensing. We demonstrate its capabilities for precise beam-steering validation and end-to-end metric analysis. In both cases, the trace-driven engine exposes performance inflections that the statistical model does not exhibit, confirming its value for high-fidelity system-level cellular networks research and as a step toward DT applications.
LinkWe analyze the open-loop mechanical tracking performance of a sub-Terahertz (sub-THz) and Terahertz (THz) uplink communication system. These high-frequency bands enable multi-gigabit links through large bandwidths and narrow beams, but require precise pointing to overcome spreading loss. A tracking system can be used to orient horn antennas toward mobile targets. We develop a mathematical model that captures the mechanical dynamics of a real tracking system, which includes motion latency and acceleration and velocity limits, to quantify pointing errors during satellite passes and integrate these effects into the link budget. We evaluate the trade-offs between beam directionality and pointing tolerance across different Low Earth Orbit (LEO) satellite trajectories and control strategies. The results link the hardware limitations to the communications performance, providing design guidelines for high-frequency Non-Terrestrial Network (NTN) uplink under practical mechanical constraints.
LinkDigital twins are now a staple of wireless networks design and evolution. Creating an accurate digital copy of a real system offers numerous opportunities to study and analyze its performance and issues. It also allows designing and testing new solutions in a risk-free environment, and applying them back to the real system after validation. A candidate technology that will heavily rely on digital twins for design and deployment is 6G, which promises robust and ubiquitous networks for eXtended Reality (XR) and immersive communications solutions. In this paper, we present BostonTwin, a dataset that merges a high-fidelity 3D model of the city of Boston, MA, with the existing geospatial data on cellular base stations deployments, in a ray-tracing-ready format. Thus, BostonTwin enables not only the instantaneous rendering and programmatic access to the building models, but it also allows for an accurate representation of the electromagnetic propagation environment in the real-world city of Boston. The level of detail and accuracy of this characterization is crucial to designing 6G networks that can support the strict requirements of sensitive and high-bandwidth applications, such as XR and immersive communication.
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