Federated learning empowered computation offloading and resource management in 6G-V2X
Humankind's urbanization and luxuriousneed increase the number of vehicles day by day.
Alongside the advancement of technologies, autonomous vehicles have now come into a …
Alongside the advancement of technologies, autonomous vehicles have now come into a …
Data correlation-aware resource management in wireless virtual reality (VR): An echo state transfer learning approach
Providing seamless connectivity for wireless virtual reality (VR) users has emerged as a key
challenge for future cloud-enabled cellular networks. In this paper, the problem of wireless …
challenge for future cloud-enabled cellular networks. In this paper, the problem of wireless …
A new block-based reinforcement learning approach for distributed resource allocation in clustered IoT networks
Resource allocation and spectrum management are two major challenges in the massive
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
scale deployment of Internet of Things (IoT) and Machine-to-Machine (M2M) communication …
A machine learning framework for resource allocation assisted by cloud computing
Conventionally, resource allocation is formulated as an optimization problem and solved
online with instantaneous scenario information. Since most resource allocation problems …
online with instantaneous scenario information. Since most resource allocation problems …
[PDF][PDF] Deep learning for proactive resource allocation in LTE-U networks
LTE in unlicensed spectrum (LTE-U) is a promising approach to overcome the wireless
spectrum scarcity. However, to reap the benefits of LTE-U, a fair coexistence mechanism …
spectrum scarcity. However, to reap the benefits of LTE-U, a fair coexistence mechanism …
eNB selection for machine type communications using reinforcement learning based Markov decision process
YJ Liu, SM Cheng, YL Hsueh - IEEE Transactions on Vehicular …, 2017 - ieeexplore.ieee.org
Machine type communication (MTC), as one of the most promising technologies in the future
wireless communication, has brought mobile communication network into a new level. The …
wireless communication, has brought mobile communication network into a new level. The …
Delay-optimal virtualized radio resource scheduling in software-defined vehicular networks via stochastic learning
Due to the high density of vehicles and various types of vehicular services, it is challenging
to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks …
to guarantee the quality of vehicular services in current Long-Term Evolution (LTE) networks …
Mobility-aware dynamic offloading strategy for C-V2X under multi-access edge computing
B Li, F Chen, Z Peng, P Hou, H Ding - Physical Communication, 2021 - Elsevier
Multi-access edge computing (MEC) technology is envisioned as a promising paradigm to
achieve the user needs of low-latency applications. Complex computation tasks are …
achieve the user needs of low-latency applications. Complex computation tasks are …
Machine learning based flexible transmission time interval scheduling for eMBB and uRLLC coexistence scenario
The enhanced Mobile Broadband (eMBB) and ultra-Reliable Low Latency Communications
(uRLLC) are the two main scenarios of 5 th generation (5G) mobile communication system …
(uRLLC) are the two main scenarios of 5 th generation (5G) mobile communication system …
Deep-reinforcement-learning-based offloading scheduling for vehicular edge computing
Vehicular edge computing (VEC) is a new computing paradigm that has great potential to
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …
enhance the capability of vehicle terminals (VTs) to support resource-hungry in-vehicle …