1 citations · 1 across the 7 of their papers we have counts for
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Voxel-CKM: Voxelized Radio Frequency Radiance Fields for Fast and Few-Shot CKM Construction
Hanlei Li, Guangyi Zhang, Kequan Zhou +2
Channel knowledge maps (CKMs) are designed to predict channel state information (CSI) from user locations, thereby enabling low-overhead CSI acquisition. However, existing CKM cons…
Reliable LLM-Based Edge-Cloud-Expert Cascades for Telecom Knowledge Systems
Qiushuo Hou, Sangwoo Park, Matteo Zecchin +4
Large language models (LLMs) are emerging as key enablers of automation in domains such as telecommunications, assisting with tasks including troubleshooting, standards interpretat…
Location-Agnostic Channel Knowledge Map Construction for Dynamic Scenes
Kequan Zhou, Guangyi Zhang, Hanlei Li +2
To alleviate the pilot and CSI-feedback burden in 6G, channel knowledge map (CKM) has emerged as a promising approach that predicts CSI solely from user locations. Nevertheless, ac…
Quantize-Sample-and-Verify: LLM Acceleration via Adaptive Edge-Cloud Speculative Decoding
Guangyi Zhang, Yunlong Cai, Guanding Yu +2
In edge-cloud speculative decoding (SD), edge devices equipped with small language models (SLMs) generate draft tokens that are verified by large language models (LLMs) in the clou…
F-CKM: Learning Channel Knowledge Map with Radio Frequency Radiance Field Rendering
Kequan Zhou, Guangyi Zhang, Hanlei Li +3
In 6G mobile communications, acquiring accurate and timely channel state information (CSI) becomes increasingly challenging due to the growing antenna array size and bandwidth. To…
ROME: Robust Model Ensembling for Semantic Communication Against Semantic Jamming Attacks
Kequan Zhou, Guangyi Zhang, Yunlong Cai +2
Recently, semantic communication (SC) has garnered increasing attention for its efficiency, yet it remains vulnerable to semantic jamming attacks. These attacks entail introducing…