Machine learning for large-scale optimization in 6g wireless networks
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
Resource allocation for simultaneous wireless information and power transfer systems: A tutorial overview
Over the last decade, simultaneous wireless information and power transfer (SWIPT) has
become a practical and promising solution for connecting and recharging battery-limited …
become a practical and promising solution for connecting and recharging battery-limited …
[HTML][HTML] Connected autonomous vehicles for improving mixed traffic efficiency in unsignalized intersections with deep reinforcement learning
Human driven vehicles (HDVs) with selfish objectives cause low traffic efficiency in an un-
signalized intersection. On the other hand, autonomous vehicles can overcome this …
signalized intersection. On the other hand, autonomous vehicles can overcome this …
Deep-learning-based wireless resource allocation with application to vehicular networks
It has been a long-held belief that judicious resource allocation is critical to mitigating
interference, improving network efficiency, and ultimately optimizing wireless communication …
interference, improving network efficiency, and ultimately optimizing wireless communication …
Graph embedding-based wireless link scheduling with few training samples
Link scheduling in device-to-device (D2D) networks is usually formulated as a non-convex
combinatorial problem, which is generally NP-hard and difficult to get the optimal solution …
combinatorial problem, which is generally NP-hard and difficult to get the optimal solution …
Low-latency edge cooperation caching based on base station cooperation in SDN based MEC
C Li, C Qianqian, Y Luo - Expert Systems with Applications, 2022 - Elsevier
With the increase of mobile terminal equipment and network mass data, users have higher
requirements for delay and service quality. To reduce user access latency and more …
requirements for delay and service quality. To reduce user access latency and more …
A GNN-based supervised learning framework for resource allocation in wireless IoT networks
The Internet of Things (IoT) allows physical devices to be connected over the wireless
networks. Although device-to-device (D2D) communication has emerged as a promising …
networks. Although device-to-device (D2D) communication has emerged as a promising …
Applications of auction and mechanism design in edge computing: A survey
Edge computing as a promising technology provides lower latency, more efficient
transmission, and faster speed of data processing since the edge servers are closer to the …
transmission, and faster speed of data processing since the edge servers are closer to the …
Minimizing the age-of-critical-information: an imitation learning-based scheduling approach under partial observations
Age of Information (AoI) has become an important metric to evaluate the freshness of
information, and studies of minimizing AoI in wireless networks have drawn extensive …
information, and studies of minimizing AoI in wireless networks have drawn extensive …
Energy efficiency based joint computation offloading and resource allocation in multi-access MEC systems
X Yang, X Yu, H Huang, H Zhu - IEEE Access, 2019 - ieeexplore.ieee.org
With the rapid growth of computation demands from mobile applications, mobile-edge
computing (MEC) provides a new method to meet requirement of high data rate and high …
computing (MEC) provides a new method to meet requirement of high data rate and high …