The frontiers of deep reinforcement learning for resource management in future wireless HetNets: Techniques, challenges, and research directions
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Machine learning for physical layer in 5G and beyond wireless networks: A survey
Fifth-generation (5G) technology will play a vital role in future wireless networks. The
breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where …
breakthrough 5G technology will unleash a massive Internet of Everything (IoE), where …
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 …
Trustworthy deep learning in 6G-enabled mass autonomy: From concept to quality-of-trust key performance indicators
Mass autonomy promises to revolutionize a wide range of engineering, service, and mobility
industries. Coordinating complex communication among hyperdense autonomous agents …
industries. Coordinating complex communication among hyperdense autonomous agents …
At the Dawn of Generative AI Era: A tutorial-cum-survey on new frontiers in 6G wireless intelligence
A Celik, AM Eltawil - IEEE Open Journal of the …, 2024 - ieeexplore.ieee.org
As we transition from the 5G epoch, a new horizon beckons with the advent of 6G, seeking a
profound fusion with novel communication paradigms and emerging technological trends …
profound fusion with novel communication paradigms and emerging technological trends …
Deep reinforcement learning for radio resource allocation and management in next generation heterogeneous wireless networks: A survey
Next generation wireless networks are expected to be extremely complex due to their
massive heterogeneity in terms of the types of network architectures they incorporate, the …
massive heterogeneity in terms of the types of network architectures they incorporate, the …
Joint multi-objective optimization for radio access network slicing using multi-agent deep reinforcement learning
Radio access network (RAN) slices can provide various customized services for next-
generation wireless networks. Thus, multiple performance metrics of different types of RAN …
generation wireless networks. Thus, multiple performance metrics of different types of RAN …
Explainable and robust artificial intelligence for trustworthy resource management in 6G networks
Artificial intelligence (AI) is expected to be an integral part of radio resource management
(RRM) in sixth-generation (6G) networks. However, the opaque nature of complex deep …
(RRM) in sixth-generation (6G) networks. However, the opaque nature of complex deep …
[HTML][HTML] Deep Reinforcement Learning for QoS provisioning at the MAC layer: A Survey
Abstract Quality of Service (QoS) provisioning is based on various network management
techniques including resource management and medium access control (MAC). Various …
techniques including resource management and medium access control (MAC). Various …
AI/ML for beyond 5G systems: Concepts, technology enablers & solutions
Abstract 5G brought an evolution on the network architecture employing the service-based
paradigm, enabling flexibility in realizing customized services across different technology …
paradigm, enabling flexibility in realizing customized services across different technology …