5 papers
Towards CSI-Native Foundation Models: A Channel-Adaptive Roadmap for 6G
Chenyu Zhang, Xinchen Lyu, Chenshan Ren +2
Wireless foundation models offer a path toward reusable channel state information (CSI) intelligence for sixth-generation (6G) systems. However, existing generic-backbone adaptatio…
Adaptive 3D-RoPE: Physics-Aligned Rotary Positional Encoding for Wireless Foundation Models
Chenyu Zhang, Xinchen Lyu, Chenshan Ren +4
Wireless foundation models (WFMs) have emerged as a promising paradigm for unified channel state information (CSI) acquisition across diverse tasks in sixth-generation (6G) network…
HeterCSI: Channel-Adaptive Heterogeneous CSI Pretraining Framework for Generalized Wireless Foundation Models
Chenyu Zhang, Xinchen Lyu, Chenshan Ren +3
Wireless foundation models promise transformative capabilities for channel state information (CSI) processing across diverse 6G network applications, yet face fundamental challenge…
Reflection-Driven Self-Optimization 6G Agentic AI RAN via Simulation-in-the-Loop Workflows
Yunhao Hu, Xinchen Lyu, Chenshan Ren +3
The escalating complexity of sixth-generation (6G) networks demands unprecedented levels of autonomy beyond the capabilities of traditional optimization-based and current AI-based…
FourierCompress: Layer-Aware Spectral Activation Compression for Efficient and Accurate Collaborative LLM Inference
Jian Ma, Xinchen Lyu, Jun Jiang +4
Collaborative large language model (LLM) inference enables real-time, privacy-preserving AI services on resource-constrained edge devices by partitioning computational workloads be…