Machine learning for resource management in cellular and IoT networks: Potentials, current solutions, and open challenges
Internet-of-Things (IoT) refers to a massively heterogeneous network formed through smart
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
devices connected to the Internet. In the wake of disruptive IoT with a huge amount and …
Artificial intelligence-based techniques for emerging heterogeneous network: State of the arts, opportunities, and challenges
Recently, mobile networking systems have been designed with more complexity of
infrastructure and higher diversity of associated devices and resources, as well as more …
infrastructure and higher diversity of associated devices and resources, as well as more …
Joint optimization of handover control and power allocation based on multi-agent deep reinforcement learning
D Guo, L Tang, X Zhang… - IEEE Transactions on …, 2020 - ieeexplore.ieee.org
In this paper, we study the handover (HO), and power allocation problem in a two-tier
heterogeneous network (HetNet), which consists of a macro base station, and some …
heterogeneous network (HetNet), which consists of a macro base station, and some …
User scheduling and resource allocation in HetNets with hybrid energy supply: An actor-critic reinforcement learning approach
Densely deployment of various small-cell base stations in cellular networks to increase
capacity will lead to heterogeneous networks (HetNets), and meanwhile, embedding the …
capacity will lead to heterogeneous networks (HetNets), and meanwhile, embedding the …
Metaverse for wireless systems: Architecture, advances, standardization, and open challenges
The growing landscape of emerging wireless applications is a key driver towards the
development of novel wireless system designs. Such a design can be based on a metaverse …
development of novel wireless system designs. Such a design can be based on a metaverse …
Efficient handover protocol for 5G and beyond networks
VO Nyangaresi, AJ Rodrigues - Computers & Security, 2022 - Elsevier
The fifth generation (5G) and beyond 5G (B5G) networks offer ultra-low latencies, higher
reliability, scalability, data rates and capacities to support applications such as vehicular …
reliability, scalability, data rates and capacities to support applications such as vehicular …
A survey on handover and mobility management in 5G HetNets: current state, challenges, and future directions
Fifth-generation (5G) networks offer high-speed data transmission with low latency,
increased base station volume, improved quality of service (QoS), and massive multiple …
increased base station volume, improved quality of service (QoS), and massive multiple …
Intelligent handover decision scheme using double deep reinforcement learning
Handovers (HOs) have been envisioned to be more challenging in 5G networks due to the
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
inclusion of millimetre wave (mm-wave) frequencies, resulting in more intense base station …
A non-stochastic learning approach to energy efficient mobility management
Energy efficient mobility management is an important problem in modern wireless networks
with heterogeneous cell sizes and increased nodes densities. We show that optimization …
with heterogeneous cell sizes and increased nodes densities. We show that optimization …
Reinforcement learning meets wireless networks: A layering perspective
Driven by the soaring traffic demand and the growing diversity of mobile services, wireless
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …
networks are evolving to be increasingly dense and heterogeneous. Accordingly, in such …