7 papers
Deep Reinforcement Learning Based Block Coordinate Descent for Downlink Weighted Sum-rate Maximization on AI-Native Wireless Networks
Siya Chen, Chee Wei Tan, H. Vincent Poor
This paper introduces a deep reinforcement learning-based block coordinate descent (DRL-based BCD) algorithm to address the nonconvex weighted sum-rate maximization (WSRM) problem…
Learning More with Less: A Generalizable, Self-Supervised Framework for Privacy-Preserving Capacity Estimation with EV Charging Data
Anushiya Arunan, Yan Qin, Xiaoli Li +3
Accurate battery capacity estimation is key to alleviating consumer concerns about battery performance and reliability of electric vehicles (EVs). However, practical data limitatio…
A New Class of Analog Precoding for Multi-Antenna Multi-User Communications over High-Frequency Bands
W. Zhu, H. D. Tuan, E. Dutkiewicz +2
A network relying on a large antenna-array-aided base station is designed for delivering multiple information streams to multi-antenna users over high-frequency bands such as the m…
Holographic Multi-User Multi-Stream Beamforming Maintaining Rate-Fairness
W. Zhu, H. D. Tuan, E. Dutkiewicz +2
We present the first investigation into the transmission of multi-stream information from a base station equipped with reconfigurable holographic surfaces (RHS) to multiple users w…
Optimal Sizing and Control of a Grid-Connected Battery in a Stacked Revenue Model Including an Energy Community
Tudor Octavian Pocola, Valentin Robu, Jip Rietveld +5
Recent years have seen rapid increases in intermittent renewable generation, requiring novel battery energy storage systems (BESS) solutions. One recent trend is the emergence of l…
Towards AI-Driven RANs for 6G and Beyond: Architectural Advancements and Future Horizons
Mathushaharan Rathakrishnan, Samiru Gayan, Rohit Singh +4
It is envisioned that 6G networks will be supported by key architectural principles, including intelligence, decentralization, interoperability, and digitalization. With the advanc…