Ultrareliable and low-latency wireless communication: Tail, risk, and scale
Ensuring ultrareliable and low-latency communication (URLLC) for 5G wireless networks
and beyond is of capital importance and is currently receiving tremendous attention in …
and beyond is of capital importance and is currently receiving tremendous attention in …
Distributed federated learning for ultra-reliable low-latency vehicular communications
In this paper, the problem of joint power and resource allocation (JPRA) for ultra-reliable low-
latency communication (URLLC) in vehicular networks is studied. Therein, the network-wide …
latency communication (URLLC) in vehicular networks is studied. Therein, the network-wide …
Intelligent resource slicing for eMBB and URLLC coexistence in 5G and beyond: A deep reinforcement learning based approach
In this paper, we study the resource slicing problem in a dynamic multiplexing scenario of
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
two distinct 5G services, namely Ultra-Reliable Low Latency Communications (URLLC) and …
Dynamic task offloading and resource allocation for ultra-reliable low-latency edge computing
To overcome devices' limitations in performing computation-intense applications, mobile
edge computing (MEC) enables users to offload tasks to proximal MEC servers for faster …
edge computing (MEC) enables users to offload tasks to proximal MEC servers for faster …
High-reliability and low-latency wireless communication for internet of things: Challenges, fundamentals, and enabling technologies
As one of the key enabling technologies of emerging smart societies and industries (ie,
industry 4.0), the Internet of Things (IoT) has evolved significantly in both technologies and …
industry 4.0), the Internet of Things (IoT) has evolved significantly in both technologies and …
Deep-reinforcement-learning-based mode selection and resource allocation for cellular V2X communications
Cellular vehicle-to-everything (V2X) communication is crucial to support future diverse
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
vehicular applications. However, for safety-critical applications, unstable vehicle-to-vehicle …
Federated learning for ultra-reliable low-latency V2V communications
In this paper, a novel joint transmit power and resource allocation approach for enabling
ultra-reliable low-latency communication (URLLC) in vehicular networks is proposed. The …
ultra-reliable low-latency communication (URLLC) in vehicular networks is proposed. The …
Age of information aware radio resource management in vehicular networks: A proactive deep reinforcement learning perspective
In this paper, we investigate the problem of age of information (AoI)-aware radio resource
management for expected long-term performance optimization in a Manhattan grid vehicle …
management for expected long-term performance optimization in a Manhattan grid vehicle …
Meta-reinforcement learning based resource allocation for dynamic V2X communications
This paper studies the allocation of shared resources between vehicle-to-infrastructure (V2I)
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …
and vehicle-to-vehicle (V2V) links in vehicle-to-everything (V2X) communications. In existing …
Wireless networked multirobot systems in smart factories
Smart manufacturing based on artificial intelligence and information communication
technology will become the main contributor to the digital economy of the upcoming …
technology will become the main contributor to the digital economy of the upcoming …