1 citations · 1 across the 7 of their papers we have counts for
7 papers
Decentralized Learning over Wireless Networks with Broadcast-Based Subgraph Sampling
Daniel Pérez Herrera, Zheng Chen, Erik G. Larsson
This work centers on the communication aspects of decentralized learning over wireless networks, using consensus-based decentralized stochastic gradient descent (D-SGD). Considerin…
Over-the-Air Federated Learning with Compressed Sensing: Is Sparsification Necessary?
Adrian Edin, Zheng Chen
Over-the-Air (OtA) Federated Learning (FL) refers to an FL system where multiple agents apply OtA computation for transmitting model updates to a common edge server. Two important…
Dynamic Scheduling for Federated Edge Learning with Streaming Data
Chung-Hsuan Hu, Zheng Chen, Erik G. Larsson
In this work, we consider a Federated Edge Learning (FEEL) system where training data are randomly generated over time at a set of distributed edge devices with long-term energy co…
Distributed Consensus in Wireless Networks with Probabilistic Broadcast Scheduling
Daniel Pérez Herrera, Zheng Chen, Erik G. Larsson
We consider distributed average consensus in a wireless network with partial communication to reduce the number of transmissions in every iteration/round. Considering the broadcast…
Robust Beamforming Design for IRS-Aided URLLC in D2D Networks
Jing Cheng, Chao Shen, Zheng Chen +1
Intelligent reflecting surface (IRS) and device-to-device (D2D) communication are two promising technologies for improving transmission reliability between transceivers in communic…
Probabilistic Caching in Wireless D2D Networks: Cache Hit Optimal vs. Throughput Optimal
Zheng Chen, Nikolaos Pappas, Marios Kountouris
Departing from the conventional cache hit optimization in cache-enabled wireless networks, we consider an alternative optimization approach for the probabilistic caching placement…