720 citations · 2.3k across the 59 of their papers we have counts for
8 papers · 1 filter
Holographic MIMO Surfaces for 6G Wireless Networks: Opportunities, Challenges, and Trends
Chongwen Huang, Sha Hu, George C. Alexandropoulos +5
Future wireless networks are expected to evolve towards an intelligent and software reconfigurable paradigm enabling ubiquitous communications between humans and mobile devices. Th…
Uplink power control in cell-free massive MIMO via deep learning
Carmen D'Andrea, Alessio Zappone, Stefano Buzzi +1
This paper focuses on the use of a deep learning approach to perform sum-rate-max and max-min power allocation in the uplink of a cell-free massive MIMO network. In particular, we…
Distributed Power Control for Large Energy Harvesting Networks: A Multi-Agent Deep Reinforcement Learning Approach
Mohit K. Sharma, Alessio Zappone, Mohamad Assaad +2
In this paper, we develop a multi-agent reinforcement learning (MARL) framework to obtain online power control policies for a large energy harvesting (EH) multiple access channel,…
Energy-Efficient Power Control in Cell-Free and User-Centric Massive MIMO at Millimeter Wave
Mario Alonzo, Stefano Buzzi, Alessio Zappone +1
In a cell-free massive MIMO architecture a very large number of distributed access points simultaneously and jointly serves a much smaller number of mobile stations; a variant of t…
Smart Radio Environments Empowered by AI Reconfigurable Meta-Surfaces: An Idea Whose Time Has Come
Marco Di Renzo, Merouane Debbah, Dinh-Thuy Phan-Huy +11
Future wireless networks are expected to constitute a distributed intelligent wireless communications, sensing, and computing platform, which will have the challenging requirement…
Deep Learning Based Online Power Control for Large Energy Harvesting Networks
Mohit K Sharma, Alessio Zappone, Merouane Debbah +1
In this paper, we propose a deep learning based approach to design online power control policies for large EH networks, which are often intractable stochastic control problems. In…