6 papers
Finite-Precision Conjugate Gradient Method for Massive MIMO Detection
Yiming Fang, Li Chen, Changsheng You +2
The implementation of the conjugate gradient (CG) method for massive MIMO detection is computationally challenging, especially for a large number of users and correlated channels.…
BeamVLM for Low-altitude Economy: Generative Beam Prediction via Vision-language Models
Chenran Kou, Changsheng You, Mingjiang Wu +3
For low-altitude economy (LAE), fast and accurate beam prediction between high-mobility unmanned aerial vehicles (UAVs) and ground base stations is of paramount importance, which e…
FedLoDrop: Federated LoRA with Dropout for Generalized LLM Fine-tuning
Sijing Xie, Dingzhu Wen, Changsheng You +3
Fine-tuning (FT) large language models (LLMs) is crucial for adapting general-purpose models to specific tasks, enhancing accuracy and relevance with minimal resources. To further…
Aerial Semantic Relay-Enabled SAGIN: Joint UAV Deployment and Resource Allocation
Yanbo Yin, Dingzhu Wen, Changsheng You +3
Space-Air-Ground Integrated Networks (SAGINs) are pivotal for enabling ubiquitous connectivity in 6G systems, yet they face significant challenges due to severe satellite-to-ground…
Communication Efficient Cooperative Edge AI via Event-Triggered Computation Offloading
You Zhou, Changsheng You, Kaibin Huang
Rare events, despite their infrequency, often carry critical information and require immediate attentions in mission-critical applications such as autonomous driving, healthcare, a…
Federated Dropout: Convergence Analysis and Resource Allocation
Sijing Xie, Dingzhu Wen, Xiaonan Liu +3
Federated Dropout is an efficient technique to overcome both communication and computation bottlenecks for deploying federated learning at the network edge. In each training round,…