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 with non-IID data in wireless networks
Federated learning provides a promising paradigm to enable network edge intelligence in
the future sixth generation (6G) systems. However, due to the high dynamics of wireless …
the future sixth generation (6G) systems. However, due to the high dynamics of wireless …
Vehicular task offloading via heat-aware MEC cooperation using game-theoretic method
Mobile-edge computing (MEC) has been witnessed as a promising solution for the vehicular
task offloading. Due to the limited computing resource of individual MEC servers, it faces …
task offloading. Due to the limited computing resource of individual MEC servers, it faces …
Federated-learning-enabled intelligent fog radio access networks: Fundamental theory, key techniques, and future trends
The rise of big data and AI boosts the development of future wireless networks. However,
due to the high cost of data offloading and model training, it is challenging to implement …
due to the high cost of data offloading and model training, it is challenging to implement …
Deep reinforcement learning based computation offloading and resource allocation for low-latency fog radio access networks
GMS Rahman, T Dang, M Ahmed - Intelligent and Converged …, 2020 - ieeexplore.ieee.org
Fog Radio Access Networks (F-RANs) have been considered a groundbreaking technique
to support the services of Internet of Things by leveraging edge caching and edge …
to support the services of Internet of Things by leveraging edge caching and edge …
Computation offloading and wireless resource management for healthcare monitoring in fog-computing-based internet of medical things
Y Qiu, H Zhang, K Long - IEEE Internet of Things Journal, 2021 - ieeexplore.ieee.org
During the COVID-19 pandemic, Internet of Medical Things (IoMT) has been playing an
important role in controlling the development of the epidemic, including enabling doctors in …
important role in controlling the development of the epidemic, including enabling doctors in …
Latency‐minimum offloading decision and resource allocation for fog‐enabled Internet of Things networks
Q Wang, S Chen - Transactions on Emerging …, 2020 - Wiley Online Library
The rapid growth of the number of sensing devices enables computation offloading to be a
promising solution to alleviate the burden of core network communication and provide low …
promising solution to alleviate the burden of core network communication and provide low …
Cooperative task offloading for mobile edge computing based on multi-agent deep reinforcement learning
J Yang, Q Yuan, S Chen, H He… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Driven by the prevalence of the computation-intensive and delay-intensive mobile
applications, Mobile Edge Computing (MEC) is emerging as a promising solution …
applications, Mobile Edge Computing (MEC) is emerging as a promising solution …
On the design of federated learning in the mobile edge computing systems
The combination of artificial intelligence and mobile edge computing (MEC) is considered as
a promising evolution path of the future wireless networks. As a model-level coordination …
a promising evolution path of the future wireless networks. As a model-level coordination …
EMI and IEMI impacts on the radio communication network of electrified railway systems: A critical review
Y Fan, L Zhang, K Li - IEEE Transactions on Vehicular …, 2023 - ieeexplore.ieee.org
The electrified railway system has been rapidly rolled out in many countries and regions in
the past decades, along with the transportation decarbonization agenda. The latest …
the past decades, along with the transportation decarbonization agenda. The latest …