A survey on over-the-air computation
Communication and computation are often viewed as separate tasks. This approach is very
effective from the perspective of engineering as isolated optimizations can be performed …
effective from the perspective of engineering as isolated optimizations can be performed …
Multiple Access Techniques for Intelligent and Multi-Functional 6G: Tutorial, Survey, and Outlook
Multiple access (MA) is a crucial part of any wireless system and refers to techniques that
make use of the resource dimensions to serve multiple users/devices/machines/services …
make use of the resource dimensions to serve multiple users/devices/machines/services …
Federated learning via unmanned aerial vehicle
Federated learning (FL) has emerged as a promising alternative to centralized machine
learning for exploiting large amounts of data generated by networks while ensuring data …
learning for exploiting large amounts of data generated by networks while ensuring data …
Joint Spectrum, Precoding, and Phase Shifts Design for RIS-Aided Multiuser MIMO THz Systems
A Mehrabian, VWS Wong - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
Terahertz (THz) wireless systems aim to support content-rich applications with ultra-high
data rate. Due to high molecular absorption, THz signals experience severe path loss over …
data rate. Due to high molecular absorption, THz signals experience severe path loss over …
Online Optimization for Over-the-Air Federated Learning with Energy Harvesting
Federated learning (FL) is recognized as a promising privacy-preserving distributed
machine learning paradigm, given its potential to enable collaborative model training among …
machine learning paradigm, given its potential to enable collaborative model training among …
Survey: federated learning data security and privacy-preserving in edge-Internet of Things
H Li, L Ge, L Tian - Artificial Intelligence Review, 2024 - Springer
The amount of data generated owing to the rapid development of the Smart Internet of
Things is increasing exponentially. Traditional machine learning can no longer meet the …
Things is increasing exponentially. Traditional machine learning can no longer meet the …
Algorithm Unrolling for Massive Connectivity in IoT Networks
In this book chapter, grant‐free uplink transmission in an Internet of Things (IoT) network that
comprises a base station (BS) with multiple antennas and massive single‐antenna IoT …
comprises a base station (BS) with multiple antennas and massive single‐antenna IoT …
Bayesian Game-Driven Incentive Mechanism for Blockchain-Enabled Secure Federated Learning in 6 G Wireless Networks
L Cai, Y Dai, Q Hu, J Zhou, Y Zhang… - IEEE Transactions on …, 2024 - ieeexplore.ieee.org
The sixth-generation (6 G) wireless networks are envisioned to build a data-driven digital
world with widespread Artificial Intelligence (AI). Federated learning (FL) is a distributed AI …
world with widespread Artificial Intelligence (AI). Federated learning (FL) is a distributed AI …
Jointly Optimizing Terahertz based Sensing and Communications in Vehicular Networks: A Dynamic Graph Neural Network Approach
In this paper, the problem of vehicle service mode selection (sensing, communication, or
both) and vehicle connections within terahertz (THz) enabled joint sensing and …
both) and vehicle connections within terahertz (THz) enabled joint sensing and …
Scalable Hybrid Beamforming for Multi-User MISO Systems: A Graph Neural Network Approach
S Wan, Z Wang, Y Zhou - IEEE Transactions on Wireless …, 2024 - ieeexplore.ieee.org
Hybrid beamforming is a promising technology for enhancing the energy-and spectral-
efficiency of wireless networks with large-scale antenna arrays, yet the current designs fall …
efficiency of wireless networks with large-scale antenna arrays, yet the current designs fall …