An Adaptive Alternating Direction Method of Multipliers for Vehicle-to-Everything Computation Offloading in Cloud-Edge Collaborative Environment
W Shu, X Feng, C Guo - IEEE Internet of Things Journal, 2024 - ieeexplore.ieee.org
Vehicle-to-Everything edge computing accomplishes the goal of low latency by offloading
tasks to edge computing servers, but how to reduce the computing latency of vehicle …
tasks to edge computing servers, but how to reduce the computing latency of vehicle …
Integrated sensing and communication waveform design in the Internet of Vehicles
Z Li, Z Ma, Y Liang - Vehicular Communications, 2023 - Elsevier
We design an integrated sensing and communication (ISAC) transmission waveform with
total transmission power, waveform similarity, and peak-to-average power ratio (PAPR) …
total transmission power, waveform similarity, and peak-to-average power ratio (PAPR) …
Ultra-Reliable Deep-Reinforcement-Learning-Based Intelligent Downlink Scheduling for 5G New Radio-Vehicle to Infrastructure Scenarios
J Wang, Y Zheng, J Wang, Z Shen, L Tong, Y Jing… - Sensors, 2023 - mdpi.com
Higher standards for reliability and efficiency apply to the connection between vehicle
terminals and infrastructure by the fifth-generation mobile communication technology (5G). A …
terminals and infrastructure by the fifth-generation mobile communication technology (5G). A …
Ultra-reliable intelligent link scheduling based on DRL for manned/unmanned aerial vehicle cooperative scenarios
Y Liao, G Gao, Y Jing - Physical Communication, 2024 - Elsevier
When manned/unmanned aerial vehicle (MAV–UAV) perform cooperative missions in
complex and variable situations, the communication link between manned aerial vehicle …
complex and variable situations, the communication link between manned aerial vehicle …
Resource allocation for cognitive network slicing in PD-SCMA system based on two-way deep reinforcement learning
Z Zhenyu, Z Yong, Y Siyu, C Zhenjie - China Communications, 2024 - ieeexplore.ieee.org
In this paper, we propose the Two-way Deep Reinforcement Learning (DRL)-Based
resource allocation algorithm, which solves the problem of resource allocation in the …
resource allocation algorithm, which solves the problem of resource allocation in the …