11 citations · 13 across the 13 of their papers we have counts for
6 papers · 1 filter
Mixed-Timescale Differential Coding for Downlink Model Broadcast in Wireless Federated Learning
Chung-Hsuan Hu, Zheng Chen, Erik G. Larsson
In standard federated learning systems, the parameter server broadcasts the global model to the participating devices in every iteration. Motivated by the temporal correlation betw…
Robust and Efficient Average Consensus with Non-Coherent Over-the-Air Aggregation
Yuhang Deng, Zheng Chen, Erik G. Larsson
Non-coherent over-the-air (OTA) computation has garnered increasing attention for its advantages in facilitating information aggregation among distributed agents in resource-constr…
A Unified Activity Detection Framework for Massive Access: Beyond the Block-Fading Paradigm
Jianan Bai, Erik G. Larsson
The wireless channel changes continuously with time and frequency and the block-fading assumption, which is popular in many theoretical analyses, never holds true in practical scen…
Delay-Constrained Grant-Free Random Access in MIMO Systems: Distributed Pilot Allocation and Power Control
Jianan Bai, Zheng Chen, Erik. G. Larsson
We study a delay-constrained grant-free random access system with a multi-antenna base station. The users randomly generate data packets with expiration deadlines, which are then t…
Faster Convergence with Less Communication: Broadcast-Based Subgraph Sampling for Decentralized Learning over Wireless Networks
Daniel Pérez Herrera, Zheng Chen, Erik G. Larsson
Consensus-based decentralized stochastic gradient descent (D-SGD) is a widely adopted algorithm for decentralized training of machine learning models across networked agents. A cru…
Detecting Active Attacks in Over-the-Air Computation using Dummy Samples
David Nordlund, Zheng Chen, Erik G. Larsson
Over-the-Air (OtA) computation is a newly emerged concept for computing functions of data from distributed nodes by taking advantage of the wave superposition property of wireless…