Author

Wenqiang Yi

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Conference Aug 2026

Beamforming-Aided Wireless Multimodal Federated Learning: Dynamic Pruning and Joint Optimization

Wireless multimodal federated learning (MFL) is promising for privacy-preserving edge intelligence, but its practical deployment is challenged by modality heterogeneity, client resource heterogeneity, and the high communication and computation cost of multimodal models. This paper proposes a beamforming-aided wireless...

Chun-Feng Xie, Zhi-Xiong Chen, Wenqiang Yi et al. · 2026 IEEE/CIC International... · 0 citations

Open access 2026

Fast Online Channel Estimation in Massive MIMO: A Zero-Shot Self-Supervised Approach

With the growing number of antennas in massive multiple-input multiple-output (MIMO) systems, robust and fast channel estimation becomes increasingly critical yet remains highly challenging. In this work, we propose a lightweight zero-shot self-supervised (ZS-SS) learning framework. It leverages non-local self-similari...

Zijun Gao, Wenqiang Yi, Fatma Benkhelifa et al. · IEEE Transactions on Wireles... · 0 citations

2026

Distribution Deviation-Aware Split Federated Learning in Resource-Limited Wireless Networks

The escalating complexity of deep neural networks introduces substantial challenges to deploying federated learning (FL) in resource-limited edge environments. To address these limitations, split federated learning (SFL) has emerged as a promising paradigm, alleviating client-side computational and communication burden...

Chunfeng Xie, Zhixiong Chen, Wenqiang Yi et al. · IEEE Transactions on Communi... · 1 citation