A survey on model-based, heuristic, and machine learning optimization approaches in RIS-aided wireless networks
Reconfigurable intelligent surfaces (RISs) have received considerable attention as a key
enabler for envisioned 6G networks, for the purpose of improving the network capacity …
enabler for envisioned 6G networks, for the purpose of improving the network capacity …
Evolution of NOMA toward next generation multiple access (NGMA) for 6G
Due to the explosive growth in the number of wireless devices and diverse wireless
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
services, such as virtual/augmented reality and Internet-of-Everything, next generation …
[HTML][HTML] Machine learning: A catalyst for THz wireless networks
AAA Boulogeorgos, E Yaqub, M Di Renzo… - Frontiers in …, 2021 - frontiersin.org
With the vision to transform the current wireless network into a cyber-physical intelligent
platform capable of supporting bandwidth-hungry and latency-constrained applications, both …
platform capable of supporting bandwidth-hungry and latency-constrained applications, both …
ADAPTIVE6G: Adaptive resource management for network slicing architectures in current 5G and future 6G systems
A Thantharate, C Beard - Journal of Network and Systems Management, 2023 - Springer
Future intelligent wireless networks demand an adaptive learning approach towards a
shared learning model to allow collaboration between data generated by network elements …
shared learning model to allow collaboration between data generated by network elements …
Learning from peers: Deep transfer reinforcement learning for joint radio and cache resource allocation in 5G RAN slicing
Network slicing is a critical technique for 5G communications that covers radio access
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
network (RAN), edge, transport and core slicing. The evolving network architecture requires …
Dynamic CU-DU selection for resource allocation in O-RAN using actor-critic learning
S Mollahasani, M Erol-Kantarci… - 2021 IEEE Global …, 2021 - ieeexplore.ieee.org
Recently, there has been tremendous efforts by network operators and equipment vendors
to adopt intelligence and openness in the next generation radio access network (RAN). The …
to adopt intelligence and openness in the next generation radio access network (RAN). The …
Latency-aware task scheduling in software-defined edge and cloud computing with erasure-coded storage systems
The collaborative edge and cloud computing system has emerged as a promising solution to
fulfill the unprecedented high requirements of 5G application scenarios. Due to vendor …
fulfill the unprecedented high requirements of 5G application scenarios. Due to vendor …
Energy-aware dynamic DU selection and NF relocation in O-RAN using actor–critic learning
Open radio access network (O-RAN) is one of the promising candidates for fulfilling flexible
and cost-effective goals by considering openness and intelligence in its architecture. In the …
and cost-effective goals by considering openness and intelligence in its architecture. In the …
Accelerating reinforcement learning via predictive policy transfer in 6g ran slicing
AM Nagib, H Abou-Zeid… - IEEE Transactions on …, 2023 - ieeexplore.ieee.org
Reinforcement Learning (RL) algorithms have recently been proposed to solve dynamic
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
radio resource management (RRM) problems in beyond 5G networks. However, RL-based …
An architecture and performance evaluation framework for artificial intelligence solutions in beyond 5G radio access networks
The evolution of mobile communications towards beyond 5th-generation (B5G) networks is
envisaged to incorporate high levels of network automation. Network automation requires …
envisaged to incorporate high levels of network automation. Network automation requires …