Future 5G-oriented system for urban rail transit: Opportunities and challenges
As a development direction of urban rail transit system, the train autonomous
circumambulate system (TACS) can operate in a safer, more efficient, and more economical …
circumambulate system (TACS) can operate in a safer, more efficient, and more economical …
Intelligent edge computing in internet of vehicles: A joint computation offloading and caching solution
Recently, Internet of Vehicles (IoV) has become one of the most active research fields in
both academic and industry, which exploits resources of vehicles and Road Side Units …
both academic and industry, which exploits resources of vehicles and Road Side Units …
Jamming and eavesdropping defense scheme based on deep reinforcement learning in autonomous vehicle networks
As a legacy from conventional wireless services, illegal eavesdropping is regarded as one
of the critical security challenges in Connected and Autonomous Vehicles (CAVs) network …
of the critical security challenges in Connected and Autonomous Vehicles (CAVs) network …
Recent developments of butler matrix from components design evolution to system integration for 5g beamforming applications: A survey
Beamforming networks for multiple beam antennas are believed to be in the vanguard of
technological developments in mmWave for 5G wireless applications. The basic idea of …
technological developments in mmWave for 5G wireless applications. The basic idea of …
Edge caching and computation management for real-time internet of vehicles: An online and distributed approach
J Zhao, X Sun, Q Li, X Ma - IEEE Transactions on Intelligent …, 2020 - ieeexplore.ieee.org
Vehicular Edge Computing (VEC) is expected to be an effective solution to meet the ultra-
low delay requirements of many emerging Internet of Vehicles (IoV) services by shifting the …
low delay requirements of many emerging Internet of Vehicles (IoV) services by shifting the …
Semi-distributed resource management in UAV-aided MEC systems: A multi-agent federated reinforcement learning approach
Recently, unmanned aerial vehicle (UAV)-enabled multi-access edge computing (MEC) has
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …
been introduced as a promising edge paradigm for the future space-aerial-terrestrial …
Deep reinforcement learning based mobile edge computing for intelligent Internet of Things
R Zhao, X Wang, J Xia, L Fan - Physical Communication, 2020 - Elsevier
In this paper, we investigate mobile edge computing (MEC) networks for intelligent internet
of things (IoT), where multiple users have some computational tasks assisted by multiple …
of things (IoT), where multiple users have some computational tasks assisted by multiple …
Intelligent ubiquitous computing for future UAV-enabled MEC network systems
In this paper, we investigate intelligent ubiquitous computing for future unmanned aerial
vehicle (UAV)-enabled mobile edge computing network (MEC) systems, where multiple …
vehicle (UAV)-enabled mobile edge computing network (MEC) systems, where multiple …
Ultra-reliable MU-MIMO detector based on deep learning for 5G/B5G-enabled IoT
In this paper, we propose an ultra-reliable multiuser multiple-input multiple-output (MU-
MIMO) detector based on deep learning for the fifth-generation and beyond the fifth …
MIMO) detector based on deep learning for the fifth-generation and beyond the fifth …
Unified analysis of coordinated multipoint transmissions in mmWave cellular networks
This article performs a unified analysis of three coordinated multipoint (CoMP) transmission
strategies in the downlink of mmWave cellular networks, including the fixed-number base …
strategies in the downlink of mmWave cellular networks, including the fixed-number base …