8 citations · 21 across the 4 of their papers we have counts for
8 papers · 1 filter
Federated Learning over Wireless Device-to-Device Networks: Algorithms and Convergence Analysis
Hong Xing, Osvaldo Simeone, Suzhi Bi
The proliferation of Internet-of-Things (IoT) devices and cloud-computing applications over siloed data centers is motivating renewed interest in the collaborative training of a sh…
Real-Time Resource Allocation for Wireless Powered Multiuser Mobile Edge Computing With Energy and Task Causality
Feng Wang, Hong Xing, Jie Xu
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, in which a multi-antenna hybrid access point (AP) wirelessly charges multiple users, and each…
Decentralized Federated Learning via SGD over Wireless D2D Networks
Hong Xing, Osvaldo Simeone, Suzhi Bi
Federated Learning (FL), an emerging paradigm for fast intelligent acquisition at the network edge, enables joint training of a machine learning model over distributed data sets an…
Energy-Efficient Proactive Caching for Fog Computing with Correlated Task Arrivals
Hong Xing, Jingjing Cui, Yansha Deng +1
With the proliferation of latency-critical applications, fog-radio network (FRAN) has been envisioned as a paradigm shift enabling distributed deployment of cloud-clone facilities…
Joint Task Assignment and Resource Allocation for D2D-Enabled Mobile-Edge Computing
Hong Xing, Liang Liu, Jie Xu +1
With the proliferation of computation-extensive and latency-critical applications in the 5G and beyond networks, mobile-edge computing (MEC) or fog computing, which provides cloud-…
Optimal Resource Allocation for Wireless Powered Mobile Edge Computing with Dynamic Task Arrivals
Feng Wang, Hong Xing, Jie Xu
This paper considers a wireless powered multiuser mobile edge computing (MEC) system, where a multi-antenna access point (AP) employs the radio-frequency (RF) signal based wireless…