66 citations · 109 across the 11 of their papers we have counts for
12 papers · 1 filter
Learning Autonomy in Management of Wireless Random Networks
Hoon Lee, Sang Hyun Lee, Tony Q. S. Quek
This paper presents a machine learning strategy that tackles a distributed optimization task in a wireless network with an arbitrary number of randomly interconnected nodes. Indivi…
Learning Optimal Fronthauling and Decentralized Edge Computation in Fog Radio Access Networks
Hoon Lee, Junbeom Kim, Seok-Hwan Park
Fog radio access networks (F-RANs), which consist of a cloud and multiple edge nodes (ENs) connected via fronthaul links, have been regarded as promising network architectures. The…
Learning Robust Beamforming for MISO Downlink Systems
Junbeom Kim, Hoon Lee, Seok-Hwan Park
This paper investigates a learning solution for robust beamforming optimization in downlink multi-user systems. A base station (BS) identifies efficient multi-antenna transmission…
Multi-Agent Deep Reinforcement Learning for Distributed Resource Management in Wirelessly Powered Communication Networks
Sangwon Hwang, Hanjin Kim, Hoon Lee +1
This paper studies multi-agent deep reinforcement learning (MADRL) based resource allocation methods for multi-cell wireless powered communication networks (WPCNs) where multiple h…
Deep Learning Methods for Universal MISO Beamforming
Junbeom Kim, Hoon Lee, Seung-Eun Hong +1
This letter studies deep learning (DL) approaches to optimize beamforming vectors in downlink multi-user multi-antenna systems that can be universally applied to arbitrarily given…
Deep Learning-based Limited Feedback Designs for MIMO Systems
Jeonghyeon Jang, Hoon Lee, Sangwon Hwang +2
We study a deep learning (DL) based limited feedback methods for multi-antenna systems. Deep neural networks (DNNs) are introduced to replace an end-to-end limited feedback procedu…