Machine learning for large-scale optimization in 6g wireless networks
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 …
“connected things” to “connected intelligence”, featured by ultra high density, large-scale …
An Introduction to Bilevel Optimization: Foundations and applications in signal processing and machine learning
Recently, bilevel optimization (BLO) has taken center stage in some very exciting
developments in the area of signal processing (SP) and machine learning (ML). Roughly …
developments in the area of signal processing (SP) and machine learning (ML). Roughly …
Edge continual learning for dynamic digital twins over wireless networks
Digital twins (DTs) constitute a critical link between the real-world and the metaverse. To
guarantee a robust connection between these two worlds, DTs should maintain accurate …
guarantee a robust connection between these two worlds, DTs should maintain accurate …
Toward resilient network slicing for satellite–terrestrial edge computing IoT
Satellite–terrestrial edge computing networks (STECNs) emerged as a global solution to
support multiple Internet of Things (IoT) applications in 6G networks. The enabling …
support multiple Internet of Things (IoT) applications in 6G networks. The enabling …
A parallel computing based model for online binary computation offloading in mobile edge computing
A Acheampong, Y Zhang, X Xu - Computer Communications, 2023 - Elsevier
Mobile-edge computing (MEC) with wireless power transfer has recently emerged as a
viable concept for improving the data processing capacity of limited powered networks like …
viable concept for improving the data processing capacity of limited powered networks like …
A survey of advances in optimization methods for wireless communication system design
Mathematical optimization is now widely regarded as an indispensable modeling and
solution tool for the design of wireless communications systems. While optimization has …
solution tool for the design of wireless communications systems. While optimization has …
SWIPT-enabled Cell-Free Massive MIMO-NOMA Networks: A Machine Learning-based Approach
This paper investigates simultaneous wireless information and power transfer (SWIPT)-
enabled cell-free massive multiple-input multiple-output (CF-mMIMO) networks with power …
enabled cell-free massive multiple-input multiple-output (CF-mMIMO) networks with power …
Multi-band wireless communication networks: Fundamentals, challenges, and resource allocation
This paper explores the evolution of wireless communication networks from utilizing the sub-
6 GHz spectrum and the millimeter wave frequency band to incorporating extremely high …
6 GHz spectrum and the millimeter wave frequency band to incorporating extremely high …
GNN-based meta-learning approach for adaptive power control in dynamic D2D communications
This article proposes a deep learning-based power control method for maximizing the sum
rate subject to rate requirements in the interference-limited device-to-device (D2D) …
rate subject to rate requirements in the interference-limited device-to-device (D2D) …
AI empowered resource management for future wireless networks
Resource management plays a pivotal role in wireless networks, which, unfortunately, leads
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …
to challenging NP-hard problems. Artificial Intelligence (AI), especially deep learning …