Linear Combination of Exponential Moving Averages for Wireless Channel Prediction. - Gabriele Formis; Stefano Scanzio; Gianluca Cena; Adriano Valenzano (INDIN, 2023)

Predicting Wireless Channel Quality by Means of Moving Averages and Regression Models. - Gabriele Formis; Stefano Scanzio; Gianluca Cena; Adriano Valenzano (WFCS, 2023)

On the Use of Artificial Neural Networks to Predict the Quality of Wi-Fi Links. - Alberto Salvatore Colletto; Stefano Scanzio; Gabriele Formis; Gianluca Cena (IEEE Access, 2023)

On the Accuracy and Precision of Moving Averages to Estimate Wi-Fi Link Quality. - Gianluca Cena; Gabriele Formis; Matteo Rosani; Stefano Scanzio (ETFA, 2024)

Wireless Sensor Networks Based on TSCH/TDMA with Power Consumption and Latency Constraints. - Stefano Scanzio; Gabriele Formis; Tullio Facchinetti; Giacomo Paolini; Gianluca Cena (ETFA, 2024)

Mixing Neural Networks and Exponential Moving Averages for Predicting Wireless Links Behavior. - Gabriele Formis; Stefano Scanzio; Lukasz Wisniewski; Gianluca Cena (ICPS, 2024)

Multi-Link Operation and Wireless Digital Twin to Support Enhanced Roaming in Next-Gen Wi-Fi. - Stefano Scanzio; Matteo Rosani; Gabriele Formis; Dave Cavalcanti 001; Valerio Frascolla; Guido Marchetto; Gianluca Cena (WFCS, 2024)

Ultralow Power and Green TSCH-Based WSNs With Proactive Reduction of Idle Listening. - Stefano Scanzio; Federico Quarta; Giacomo Paolini; Gabriele Formis; Gianluca Cena (IEEE Internet Things J., 2024)

Widening the Coverage of Reference Broadcast Infrastructure Synchronization in Wi-Fi Networks. - Gianluca Cena; Pietro Chiavassa; Gabriele Formis; Stefano Scanzio (WFCS, 2025)

On the Prediction of Wi-Fi Performance through Deep Learning. - Gabriele Formis; Amanda Ericson; Stefan Forsström; Kyi Thar; Gianluca Cena; Stefano Scanzio (WFCS, 2025)

Compression of Executable QR Codes or sQRy for Industry: an Example for Wi-Fi Access Points. - Stefano Scanzio; Gabriele Formis; Pietro Chiavassa; Lukasz Wisniewski; Gianluca Cena (WFCS, 2025)

Improving Wi-Fi Network Performance Prediction with Deep Learning Models. - Gabriele Formis; Amanda Ericson; Stefan Forsström; Kyi Thar; Gianluca Cena; Stefano Scanzio (CoRR, 2025)