Deep learning for B5G open radio access network: Evolution, survey, case studies, and challenges
Open Radio Access Network (O-RAN) alliance was recently launched to devise a new RAN
architecture featuring open, software-driven, virtual, and intelligent radio access architecture …
architecture featuring open, software-driven, virtual, and intelligent radio access architecture …
The emergence of wireless MAC protocols with multi-agent reinforcement learning
In this paper, we propose a new framework, exploiting the multi-agent deep deterministic
policy gradient (MADDPG) algorithm, to enable a base station (BS) and user equipment …
policy gradient (MADDPG) algorithm, to enable a base station (BS) and user equipment …
Opportunistic non-contiguous OFDMA scheduling framework for future B5G/6G cellular networks
HB Salameh, H Al-Obiedollah, R Mahasees… - … Modelling Practice and …, 2022 - Elsevier
In this paper, we consider the problem of resource allocation within Beyond 5G (B5G) and
the envisioned 6G wireless networks with Cognitive Radio (CR) capability. CR technology …
the envisioned 6G wireless networks with Cognitive Radio (CR) capability. CR technology …
Deep Reinforcement Learning for Downlink Scheduling in 5G and Beyond Networks: A Review
M Seguin, A Omer, M Koosha… - 2023 IEEE 34th …, 2023 - ieeexplore.ieee.org
The coexistence of a wide variety of different applications with diverse Quality of Service
(QoS) and Quality of Experience (QoE) requirements calls for more sophisticated radio …
(QoS) and Quality of Experience (QoE) requirements calls for more sophisticated radio …
Mobility planning of LoRa gateways for edge storage of IoT data
LoRaWAN is now a leading technology in IoT developments due to its low power
consumption and simple deployment features. Despite being termed a long-distance …
consumption and simple deployment features. Despite being termed a long-distance …
Cooperative scheduler to enhance massive connectivity in 5G and beyond by minimizing interference in OMA and NOMA
The fifth-generation (5G) and beyond 5G (B5G) wireless networks introduced massive
machine-type communications (mMTC) to cope with the growing demand of massive …
machine-type communications (mMTC) to cope with the growing demand of massive …
[PDF][PDF] Fairness-oriented user scheduling for bursty downlink transmission using multi-agent reinforcement learning
In this work, we develop practical user scheduling algorithms for downlink bursty traffic with
emphasis on user fairness. In contrast to the conventional scheduling algorithms that either …
emphasis on user fairness. In contrast to the conventional scheduling algorithms that either …
[HTML][HTML] Data-intensive workflow scheduling strategy based on deep reinforcement learning in multi-clouds
S Zhang, Z Zhao, C Liu, S Qin - Journal of Cloud Computing, 2023 - Springer
With the increase development of Internet of Things devices, the data-intensive workflow has
emerged as a new kinds of representation for IoT applications. Because most IoT systems …
emerged as a new kinds of representation for IoT applications. Because most IoT systems …
Multi-User Multi-Application Packet Scheduling for Application-Specific QoE Enhancement Based on Knowledge-Embedded DDPG in 6G RAN
Y Fu, X Wang - arXiv preprint arXiv:2405.01007, 2024 - arxiv.org
The rapidly growing diversity of concurrent applications from both different users and same
devices calls for application-specific Quality of Experience (QoE) enhancement of future …
devices calls for application-specific Quality of Experience (QoE) enhancement of future …