AI-based radio resource allocation in support of the massive heterogeneity of 6G networks
There is a consensus in industry and academia that 6G wireless networks will incorporate
massive heterogeneous radio access technologies (RATs) in order to cater to the high …
massive heterogeneous radio access technologies (RATs) in order to cater to the high …
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 …
Deep learning for radio resource allocation with diverse quality-of-service requirements in 5G
To accommodate diverse Quality-of-Service (QoS) requirements in 5th generation cellular
networks, base stations need real-time optimization of radio resources in time-varying …
networks, base stations need real-time optimization of radio resources in time-varying …
Deep reinforcement learning for resource allocation in 5G communications
The rapid growth of data traffic has pushed the mobile telecommunication industry towards
the adoption of fifth generation (5G) communications. Cloud radio access network (CRAN) …
the adoption of fifth generation (5G) communications. Cloud radio access network (CRAN) …
A survey on resource allocation for 5G heterogeneous networks: Current research, future trends, and challenges
In the fifth-generation (5G) mobile communication system, various service requirements of
different communication environments are expected to be satisfied. As a new evolution …
different communication environments are expected to be satisfied. As a new evolution …
Deep learning (DL) based joint resource allocation and RRH association in 5G-multi-tier networks
Fifth-Generation (5G) networks have adopted a multi-tier structural model which includes
femtocells, picocells, and macrocells to ensure the user quality-of-service (QoS). To meet …
femtocells, picocells, and macrocells to ensure the user quality-of-service (QoS). To meet …
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 …
A survey on applications of deep reinforcement learning in resource management for 5G heterogeneous networks
YL Lee, D Qin - 2019 Asia-Pacific Signal and Information …, 2019 - ieeexplore.ieee.org
Heterogeneous networks (HetNets) have been regarded as the key technology for fifth
generation (5G) communications to support the explosive growth of mobile traffics. By …
generation (5G) communications to support the explosive growth of mobile traffics. By …
DeepRAT: A DRL-based framework for multi-RAT assignment and power allocation in HetNets
Wireless heterogeneous networks (HetNets), where several systems with multi-radio access
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
technologies (multi-RATs) coexist for massive multi-connectivity networks, are in service …
A Multi-Agent Deep Reinforcement Learning Approach for RAN Resource Allocation in O-RAN
Artificial intelligence (AI) and Machine Learning (ML) are considered as key enablers for
realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in …
realizing the full potential of fifth-generation (5G) and beyond mobile networks, particularly in …