most citedJoint User Association and Resource Allocation for Adaptive Semantic Communication in 5G and Beyond Networks

1 citations · 1 across the 3 of their papers we have counts for

collaborators

5 papers

cs.NI2026

Energy-Efficient Online Scheduling for Wireless Powered Mobile Edge Computing Networks

Xingqiu He, Chaoqun You, Yuzhi Yang +4

Wireless Powered Mobile Edge Computing (WP-MEC) integrates mobile edge computing (MEC) with wireless power transfer (WPT) to simultaneously extend the operational lifetime and enha…

cs.NI20261 cited

Joint User Association and Resource Allocation for Adaptive Semantic Communication in 5G and Beyond Networks

Xingqiu He, Chaoqun You, Zihan Chen +4

Semantic communication (SemCom) has emerged as a promising paradigm that leverages Deep Neural Networks (DNNs) to extract task-relevant information, thereby substantially reducing…

cs.CV2025

Video Object Recognition in Mobile Edge Networks: Local Tracking or Edge Detection?

Kun Guo, Yun Shen, Xijun Wang +3

Fast and accurate video object recognition, which relies on frame-by-frame video analytics, remains a challenge for resource-constrained devices such as traffic cameras. Recent adv…

eess.SY2025

Lightweight Federated Learning in Mobile Edge Computing with Statistical and Device Heterogeneity Awareness

Jinghong Tan, Zhichen Zhang, Kun Guo +2

Federated learning enables collaborative machine learning while preserving data privacy, but high communication and computation costs, exacerbated by statistical and device heterog…

cs.NI2025

FIRE: A Failure-Adaptive Reinforcement Learning Framework for Edge Computing Migrations

Marie Siew, Shikhar Sharma, Zekai Li +5

In edge computing, users' service profiles are migrated due to user mobility. Reinforcement learning (RL) frameworks have been proposed to do so, often trained on simulated data. H…