A survey on model-based, heuristic, and machine learning optimization approaches in RIS-aided wireless networks

H Zhou, M Erol-Kantarci, Y Liu… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
Reconfigurable intelligent surfaces (RISs) have received considerable attention as a key
enabler for envisioned 6G networks, for the purpose of improving the network capacity …

Interference management in 5G and beyond networks: A comprehensive survey

N Trabelsi, LC Fourati, CS Chen - Computer Networks, 2024 - Elsevier
During the last decade, wireless data services have had an incredible impact on people's
lives in ways we could never have imagined. The number of mobile devices has increased …

Evolution of NOMA toward next generation multiple access (NGMA) for 6G

Y Liu, S Zhang, X Mu, Z Ding, R Schober… - IEEE Journal on …, 2022 - ieeexplore.ieee.org
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 …

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 …

Learning from peers: Deep transfer reinforcement learning for joint radio and cache resource allocation in 5G RAN slicing

H Zhou, M Erol-Kantarci, HV Poor - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

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 …

Latency-aware task scheduling in software-defined edge and cloud computing with erasure-coded storage systems

J Tang, MM Jalalzai, C Feng, Z Xiong… - IEEE Transactions on …, 2022 - ieeexplore.ieee.org
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 …

Energy-aware dynamic DU selection and NF relocation in O-RAN using actor–critic learning

S Mollahasani, T Pamuklu, R Wilson, M Erol-Kantarci - Sensors, 2022 - mdpi.com
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 …

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 …

Energy-efficient and delay-guaranteed joint resource allocation and du selection in o-ran

T Pamuklu, S Mollahasani… - 2021 IEEE 4th 5G World …, 2021 - ieeexplore.ieee.org
The radio access network (RAN) part of the next-generation wireless networks will require
efficient solutions for satisfying low latency and high-throughput services. The open RAN (O …