124 citations
- Beijing University of Posts and TelecommunicationsCN7 papers
- Southeast UniversityCN6 papers
- Tsinghua UniversityCN4 papers
- University of SouthamptonGB3 papers
- Purple Mountain LaboratoriesCN2 papers
- Shanghai Jiao Tong UniversityCN2 papers
- State Key Laboratory of Networking and Switching Technology2 papers
- ZTE (China)CN2 papers
- Beijing Information Science & Technology UniversityCN1 paper
- Beijing Institute of TechnologyCN1 paper
- Beijing Jiaotong UniversityCN1 paper
- Centre Hospitalier Universitaire de Clermont-FerrandFR1 paper
8 papers · 1 filter
NOMA for Next-generation Massive IoT: Performance Potential and Technology Directions
Yifei Yuan, Sen Wang, Yongpeng Wu +4
Broader applications of the Internet of Things (IoT) are expected in the forthcoming 6G system, although massive IoT is already a key scenario in 5G, predominantly relying on physi…
Deep Reinforcement Learning for Energy-Efficient Beamforming Design in Cell-Free Networks
Weilai Li, Wanli Ni, Hui Tian +1
Cell-free network is considered as a promising architecture for satisfying more demands of future wireless networks, where distributed access points coordinate with an edge cloud p…
First- and Second-Moment Constrained Gaussian Channels
Shuai Ma, Michèle Wigger
This paper studies the channel capacity of intensity-modulation direct-detection (IM/DD) visible light communication (VLC) systems under both optical and electrical power constrain…
Deep Deterministic Policy Gradient for Relay Selection and Power Allocation in Cooperative Communication Network
Yuanzhe Geng, Erwu Liu, Rui Wang +4
Perfect channel state information (CSI) is usually required when considering relay selection and power allocation in cooperative communication. However, it is difficult to get an a…
Compressive Sensing Techniques for Next-Generation Wireless Communications
Zhen Gao, Linglong Dai, Shuangfeng Han +3
A range of efficient wireless processes and enabling techniques are put under a magnifier glass in the quest for exploring different manifestations of correlated processes, where s…
Machine Learning Inspired Energy-Efficient Hybrid Precoding for MmWave Massive MIMO Systems
Xinyu Gao, Linglong Dai, Ying Sun +2
Hybrid precoding is a promising technique for mmWave massive MIMO systems, as it can considerably reduce the number of required radio-frequency (RF) chains without obvious performa…