collaborators

8 papers

cs.LG2026

TESLA: Taylor Expansion of Sinusoidal Learnable Activations

Daehwa Ko, Jaehyeon Kim, Seunghyun Ham +1

The parity problem--deciding whether the number of ones in a binary vector is odd or even--remains challenging for standard neural networks due to linear inseparability and the nee…

cs.NI2026

Can Machine Learning Break Wi-Fi Privacy? A Study on MAC Address Randomization

Marta Puig, Costas Michaelides, Lucia Pintor +2

Medium Access Control (MAC) address randomization has been widely adopted during the IEEE 802.11 network discovery phase as a countermeasure against passive tracking. This paper ex…

cs.NI2026

BRAVR: An AP-Assisted Online DRL Mechanism for Interactive VR Bitrate Adaptation over Wi-Fi

Miguel Casasnovas, Francesc Wilhelmi, Boris Bellalta

Interactive virtual reality (VR) streaming over Wi-Fi requires stringent latency and reliability guarantees, which become increasingly difficult to achieve under dynamic channel co…

cs.NI2026

A Tutorial on IEEE 802.11bn Multi-AP Coordination for Wi-Fi 8: From Standardization to Performance Evaluation

Francesc Wilhelmi, Boris Bellalta, Giovanni Geraci +5

The IEEE 802.11bn amendment defines significant modifications to the standard by establishing Ultra High Reliability (UHR) targets in Wireless Local Area Networks (WLANs). This is…

eess.SY2026

Studying the Role of Synthetic Data for Machine Learning-based Wireless Networks Traffic Forecasting

José Pulido, Francesc Wilhelmi, Sergio Fortes +3

Synthetic data generation is an appealing tool for augmenting and enriching datasets, playing a crucial role in advancing artificial intelligence (AI) and machine learning (ML). No…

cs.NI2024

"It's Your Turn": A Novel Channel Contention Mechanism for Improving Wi-Fi's Reliability

Francesc Wilhelmi, Lorenzo Galati-Giordano, Gianluca Fontanesi

The next generation of Wi-Fi, i.e., the IEEE 802.11bn (aka Wi-Fi 8), is not only expected to increase its performance and provide extended capabilities but also aims to offer a rel…