88 citations · 88 across the 4 of their papers we have counts for
7 papers
Generative Diffusion Model Driven Massive Random Access in Massive MIMO Systems
Keke Ying, Zhen Gao, Sheng Chen +2
Massive random access is an important technology for achieving ultra-massive connectivity in next-generation wireless communication systems. It aims to address key challenges durin…
Federated Stochastic Gradient Descent Begets Self-Induced Momentum
Howard H. Yang, Zuozhu Liu, Yaru Fu +2
Federated learning (FL) is an emerging machine learning method that can be applied in mobile edge systems, in which a server and a host of clients collaboratively train a statistic…
Federated Learning with Differential Privacy: Algorithms and Performance Analysis
Kang Wei, Jun Li, Ming Ding +6
In this paper, to effectively prevent information leakage, we propose a novel framework based on the concept of differential privacy (DP), in which artificial noises are added to t…
Power Allocation in Cache-Aided NOMA Systems: Optimization and Deep Reinforcement Learning Approaches
Khai Nguyen Doan, Mojtaba Vaezi, Wonjae Shin +3
This work exploits the advantages of two prominent techniques in future communication networks, namely caching and non-orthogonal multiple access (NOMA). Particularly, a system wit…
On Safeguarding Privacy and Security in the Framework of Federated Learning
Chuan Ma, Jun Li, Ming Ding +4
Motivated by the advancing computational capacity of wireless end-user equipment (UE), as well as the increasing concerns about sharing private data, a new machine learning (ML) pa…
Simultaneous Wireless Information and Power Transfer Under Different CSI Acquisition Schemes
Chen-Feng Liu, Marco Maso, Subhash Lakshminarayana +2
In this work, we consider a multiple-input single-output system in which an access point (AP) performs a simultaneous wireless information and power transfer (SWIPT) to serve a use…