activity
20132025
most cited6G White Paper on Machine Learning in Wireless Communication Networks

94 citations · 101 across the 15 of their papers we have counts for

collaborators

33 papers

eess.SP2025

Max-Min Fairness for Stacked Intelligent Metasurface-Assisted Multi-User MISO Systems

Nipuni Ginige, Prathapasinghe Dharmawansa, Arthur Sousa de Sena +3

Stacked intelligent metasurface (SIM) is an emerging technology that uses multiple reconfigurable surface layers to enable flexible wave-based beamforming. In this paper, we focus…

cs.NI2025

Towards Specialized Wireless Networks Using an ML-Driven Radio Interface

Kamil Szczech, Maksymilian Wojnar, Katarzyna Kosek-Szott +8

Future wireless networks will need to support diverse applications (such as extended reality), scenarios (such as fully automated industries), and technological advances (such as t…

eess.SP2025

Comprehensive Review of Deep Unfolding Techniques for Next-Generation Wireless Communication Systems

Sukanya Deka, Kuntal Deka, Nhan Thanh Nguyen +3

The application of machine learning in wireless communications has been extensively explored, with deep unfolding emerging as a powerful model-based technique. Deep unfolding enhan…

eess.SP2022

Supervised Learning based Sparse Channel Estimation for RIS aided Communications

Dilin Dampahalage, K. B. Shashika Manosha, Nandana Rajatheva +1

An reconfigurable intelligent surface (RIS) can be used to establish line-of-sight (LoS) communication when the direct path is compromised, which is a common occurrence in a millim…

eess.SP2021

LiDAR Aided Human Blockage Prediction for 6G

Dileepa Marasinghe, Nandana Rajatheva, Matti Latva-aho

Leveraging higher frequencies up to THz band paves the way towards a faster network in the next generation of wireless communications. However, such shorter wavelengths are suscept…

eess.SP2021

Untrained DNN for Channel Estimation of RIS-Assisted Multi-User OFDM System with Hardware Impairments

Nipuni Ginige, K. B. Shashika Manosha, Nandana Rajatheva +1

Reconfigurable intelligent surface (RIS) is an emerging technology for improving performance in fifth-generation (5G) and beyond networks. Practically channel estimation of RIS-ass…