15 citations · 82 across the 25 of their papers we have counts for
7 papers · 1 filter
An Autoencoder-Based Constellation Design for AirComp in Wireless Federated Learning
Yujia Mu, Xizixiang Wei, Cong Shen
Wireless federated learning (FL) relies on efficient uplink communications to aggregate model updates across distributed edge devices. Over-the-air computation (a.k.a. AirComp) has…
Advancing RAN Slicing with Offline Reinforcement Learning
Kun Yang, Shu-ping Yeh, Menglei Zhang +3
Dynamic radio resource management (RRM) in wireless networks presents significant challenges, particularly in the context of Radio Access Network (RAN) slicing. This technology, cr…
Offline Reinforcement Learning for Wireless Network Optimization with Mixture Datasets
Kun Yang, Cong Shen, Jing Yang +2
The recent development of reinforcement learning (RL) has boosted the adoption of online RL for wireless radio resource management (RRM). However, online RL algorithms require dire…
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Xizixiang Wei, Cong Shen, Jing Yang +1
We propose a novel communication design, termed random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system. The ke…
Random Orthogonalization for Federated Learning in Massive MIMO Systems
Xizixiang Wei, Cong Shen, Jing Yang +1
We propose a novel uplink communication method, coined random orthogonalization, for federated learning (FL) in a massive multiple-input and multiple-output (MIMO) wireless system.…
Multi-player Multi-armed Bandits with Collision-Dependent Reward Distributions
Chengshuai Shi, Cong Shen
We study a new stochastic multi-player multi-armed bandits (MP-MAB) problem, where the reward distribution changes if a collision occurs on the arm. Existing literature always assu…