1 citations · 2 across the 17 of their papers we have counts for
17 papers
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…
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…
Prediction-Powered Risk Monitoring of Deployed Models for Detecting Harmful Distribution Shifts
Guangyi Zhang, Yunlong Cai, Guanding Yu +1
We study the problem of monitoring model performance in dynamic environments where labeled data are limited. To this end, we propose prediction-powered risk monitoring (PPRM), a se…
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…
Conformal Sparsification for Bandwidth-Efficient Edge-Cloud Speculative Decoding
Payel Bhattacharjee, Fengwei Tian, Meiyu Zhong +3
Edge-cloud speculative decoding (SD) accelerates inference by having a cloud-based large language model (LLM) that verifies draft tokens generated by a resource-constrained small l…
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…
Dynamic Bandwidth Allocation for Hybrid Event-RGB Transmission
Pujing Yang, Guangyi Zhang, Yunlong Cai +2
Event cameras asynchronously capture pixel-level intensity changes with extremely low latency. They are increasingly used in conjunction with RGB cameras for a wide range of vision…
Joint Transmission and Deblurring: A Semantic Communication Approach Using Events
Pujing Yang, Guangyi Zhang, Yunlong Cai +2
Deep learning-based joint source-channel coding (JSCC) is emerging as a promising technology for effective image transmission. However, most existing approaches focus on transmitti…
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…
Towards Compatible Semantic Communication: A Perspective on Digital Coding and Modulation
Guangyi Zhang, Kequan Zhou, Yunlong Cai +2
Semantic communication (SC) is emerging as a pivotal innovation within the 6G framework, aimed at enabling more intelligent transmission. This development has led to numerous studi…
Coarse-to-Fine: A Dual-Phase Channel-Adaptive Method for Wireless Image Transmission
Hanlei Li, Guangyi Zhang, Kequan Zhou +2
Developing channel-adaptive deep joint source-channel coding (JSCC) systems is a critical challenge in wireless image transmission. While recent advancements have been made, most e…
Rate-Adaptive Generative Semantic Communication Using Conditional Diffusion Models
Pujing Yang, Guangyi Zhang, Yunlong Cai
Recent advances in deep learning-based joint source-channel coding (DJSCC) have shown promise for end-to-end semantic image transmission. However, most existing schemes primarily f…
Learned Image Transmission with Hierarchical Variational Autoencoder
Guangyi Zhang, Hanlei Li, Yunlong Cai +3
In this paper, we introduce an innovative hierarchical joint source-channel coding (HJSCC) framework for image transmission, utilizing a hierarchical variational autoencoder (VAE).…
Digital Wireless Image Transmission via Distribution Matching
Pujing Yang, Guangyi Zhang, Yunlong Cai
Deep learning-based joint source-channel coding (JSCC) is emerging as a potential technology to meet the demand for effective data transmission, particularly for image transmission…
From Analog to Digital: Multi-Order Digital Joint Coding-Modulation for Semantic Communication
Guangyi Zhang, Pujing Yang, Yunlong Cai +2
Recent studies in joint source-channel coding (JSCC) have fostered a fresh paradigm in end-to-end semantic communication. Despite notable performance achievements, present initiati…
Feature Allocation for Semantic Communication with Space-Time Importance Awareness
Kequan Zhou, Guangyi Zhang, Yunlong Cai +3
In the realm of semantic communication, the significance of encoded features can vary, while wireless channels are known to exhibit fluctuations across multiple subchannels in diff…
Deep Refinement-Based Joint Source Channel Coding over Time-Varying Channels
Junyu Pan, Hanlei Li, Guangyi Zhang +2
In recent developments, deep learning (DL)-based joint source-channel coding (JSCC) for wireless image transmission has made significant strides in performance enhancement. Nonethe…