Machine learning for large-scale optimization in 6g wireless networks

Y Shi, L Lian, Y Shi, Z Wang, Y Zhou… - … Surveys & Tutorials, 2023 - ieeexplore.ieee.org
The sixth generation (6G) wireless systems are envisioned to enable the paradigm shift from
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …

[HTML][HTML] Cell-free massive multiple-input multiple-output challenges and opportunities: A survey

M Ajmal, A Siddiqa, B Jeong, J Seo, D Kim - ICT Express, 2023 - Elsevier
Cell-free (CF) massive multiple-input multiple-output (mMIMO) system is a state-of-the-art
emerging technology targeted towards beyond fifth-generation (B5G) and sixth-generation …

Interference nulling using reconfigurable intelligent surface

T Jiang, W Yu - IEEE Journal on Selected Areas in …, 2022 - ieeexplore.ieee.org
This paper investigates the interference nulling capability of reconfigurable intelligent
surface (RIS) in a multiuser environment where multiple single-antenna transceivers …

Quantum machine learning for next-G wireless communications: Fundamentals and the path ahead

B Narottama, Z Mohamed… - IEEE Open Journal of the …, 2023 - ieeexplore.ieee.org
A comprehensive coverage of the state-of-the-art in quantum machine learning (QML)
methodologies, with a unique perspective on their applications for wireless communications …

A survey of advances in optimization methods for wireless communication system design

YF Liu, TH Chang, M Hong, Z Wu, AMC So… - arXiv preprint arXiv …, 2024 - arxiv.org
Mathematical optimization is now widely regarded as an indispensable modeling and
solution tool for the design of wireless communications systems. While optimization has …

Leveraging variational autoencoders for parameterized MMSE channel estimation

M Baur, B Fesl, W Utschick - arXiv preprint arXiv:2307.05352, 2023 - arxiv.org
In this manuscript, we propose to utilize the generative neural network-based variational
autoencoder for channel estimation. The variational autoencoder models the underlying true …

Active beam tracking with reconfigurable intelligent surface

H Han, T Jiang, W Yu - ICASSP 2023-2023 IEEE International …, 2023 - ieeexplore.ieee.org
This paper studies a beam tracking problem in a reconfigurable intelligent surface (RIS)-
assisted communication system, in which a single antenna access point (AP) tracks a single …

Energy-Efficient Power Allocation in Cell-Free Massive MIMO via Graph Neural Networks

R Raghunath, B Peng, EA Jorswieck - arXiv preprint arXiv:2401.14281, 2024 - arxiv.org
CF-mMIMO systems are a promising solution to enhance the performance in 6G wireless
networks. Its distributed nature of the architecture makes it highly reliable, provides sufficient …

[PDF][PDF] Advanced Wireless Sensor Networks: Applications, Challenges and Research Trends

D Kandris, E Anastasiadis - Electronics, 2024 - mdpi.com
A typical wireless sensor network (WSN) contains wirelessly interconnected devices, called
sensor nodes, which have sensing, processing, and communication abilities and are …

Contextual Bandit-Based Amplifier IBO Optimization in Massive MIMO Network

M Hoffmann, P Kryszkiewicz - IEEE Access, 2023 - ieeexplore.ieee.org
Massive Multiple-Input Multiple-Output (MMIMO) is one of the 5G key enablers. Though,
most of the works consider MMIMO under assumptions of ideal hardware. It has been shown …