activity
20242026
most citedAI-Driven Channel State Information (CSI) Extrapolation for 6G: Current Situations, Challenges and Future Research

13 citations · 35 across the 24 of their papers we have counts for

collaborators

25 papers

cs.AI2026

CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models

Yuan Gao, Wenjun Yu, Jun Jiang +3

Channel foundation models (CFMs) are commonly evaluated in model-specific pipelines that differ in data, radio configurations, partitions, adaptation procedures, task definitions,…

eess.SP2026

Generalizable and Computational Efficient Channel Extrapolation for 6G: A Configurable AI-Driven Framework Built from a Modular Perspective

Yuan Gao, Xinyi Wu, Jiang Jun +5

Acquiring channel state information (CSI) with manageable overhead has been essential to provide high-performance communication services, which is extremely challenging in the emer…

eess.SP2026

6G Native AI and Channel Foundation Models

Shugong Xu, Jun Jiang, Yuan Gao

The integration of artificial intelligence (AI) and wireless communications is widely regarded as a core objective of sixth-generation (6G) systems. However, both the meaning of na…

eess.SP2026

CSI-CLIP++: A Scalable Channel Foundation Model for Wireless Communication via CIR-CSI Consistency

Jun Jiang, Wenjun Yu, Yunfan Li +2

Self-supervised learning can exploit large-scale unlabeled channel data to improve the transferability of wireless AI models. Existing channel foundation models are often built on…

eess.SP2026

Generalizable and Robust Beam Prediction for 6G Networks: An Deep-Learning Framework with Positioning Feature Fusion

Yanliang Jin, Yunfan Li, Jiang Jun +5

Beamforming (BF) is essential for enhancing system capacity in fifth generation (5G) and beyond wireless networks, yet exhaustive beam training in ultra-massive multiple-input mult…

eess.SP2026

Dynamic Channel Charting: An LSTM-AE-based Approach

Yuan Gao, Wenjing Xie, Yiming Liu +3

With the development of the sixth-generation (6G) communication system, Channel State Information (CSI) plays a crucial role in improving network performance. Traditional Channel C…

eess.SP2026

Near-Field Positioning for XL-MIMO Uniform Circular Arrays: An Attention-Enhanced Deep Learning Approach

Yuan Gao, Xinyu Guo, Han Li +2

In the evolving landscape of sixth-generation (6G) mobile communication, multiple-input multiple-output (MIMO) systems are incorporating an unprecedented number of antenna elements…

eess.SP2026

Channel Extrapolation for MIMO Systems with the Assistance of Multi-path Information Induced from Channel State Information

Yuan Gao, Xinyi Wu, Jiang Jun +5

Acquiring channel state information (CSI) through traditional methods, such as channel estimation, is increasingly challenging for the emerging sixth generation (6G) mobile network…

cs.CV2026

Efficient UAV trajectory prediction: A multi-modal deep diffusion framework

Yuan Gao, Xinyu Guo, Wenjing Xie +4

To meet the requirements for managing unauthorized UAVs in the low-altitude economy, a multi-modal UAV trajectory prediction method based on the fusion of LiDAR and millimeter-wave…

cs.CV2026

ReinPath: A Multimodal Reinforcement Learning Approach for Pathology

Kangcheng Zhou, Jun Jiang, Qing Zhang +3

Interpretability is significant in computational pathology, leading to the development of multimodal information integration from histopathological image and corresponding text dat…

eess.SP2026

CSI-MAE: A Masked Autoencoder-based Channel Foundation Model

Jun Jiang, Xiaolong Ruan, Shugong Xu

Self-Supervised Learning (SSL) has emerged as a key technique in machine learning, tackling challenges such as limited labeled data, high annotation costs, and variable wireless ch…

eess.SP2026★ 13 cited

AI-Driven Channel State Information (CSI) Extrapolation for 6G: Current Situations, Challenges and Future Research

Yuan Gao, Zichen Lu, Xinyi Wu +7

CSI extrapolation is an effective method for acquiring channel state information (CSI), essential for optimizing performance of sixth-generation (6G) communication systems. Traditi…

cs.NI2025

Sidelink Positioning: Standardization Advancements, Challenges and Opportunities

Yuan Gao, Guangjin Pan, Zhiyong Zhong +4

With the integration of cellular networks in vertical industries that demand precise location information, such as vehicle-to-everything (V2X), public safety, and Industrial Intern…

eess.SP2025★ 12 cited

SSNet: Flexible and robust channel extrapolation for fluid antenna systems enabled by an self-supervised learning framework

Yuan Gao, Yiming Liu, Runze Yu +5

Fluid antenna systems (FAS) signify a pivotal advancement in 6G communication by enhancing spectral efficiency and robustness. However, obtaining accurate channel state information…

eess.SP2025

Enhanced Fingerprint-based Positioning With Practical Imperfections: Deep learning-based approaches

Shugong Xu, Jun Jiang, Wenjun Yu +7

High-precision positioning is vital for cellular networks to support innovative applications such as extended reality, unmanned aerial vehicles (UAVs), and industrial Internet of T…

eess.SP2025★ 7 cited

Enabling 6G Through Multi-Domain Channel Extrapolation: Opportunities and Challenges of Generative Artificial Intelligence

Yuan Gao, Zichen Lu, Yifan Wu +5

Channel extrapolation has attracted wide attention due to its potential to acquire channel state information (CSI) with high accuracy and minimal overhead. This is becoming increas…

cs.CV2025

Stage-wise Adaptive Label Distribution for Facial Age Estimation

Bo Wu, Zhiqi Ai, Jun Jiang +2

Label ambiguity poses a significant challenge in age estimation tasks. Most existing methods address this issue by modeling correlations between adjacent age groups through label d…

cs.CV2025

Stereo-based 3D Anomaly Object Detection for Autonomous Driving: A New Dataset and Baseline

Shiyi Mu, Zichong Gu, Hanqi Lyu +2

3D detection technology is widely used in the field of autonomous driving, with its application scenarios gradually expanding from enclosed highways to open conventional roads. For…

eess.SP2025

Towards channel foundation models (CFMs): Motivations, methodologies and opportunities

Jun Jiang, Yuan Gao, Xinyi Wu +1

Artificial intelligence (AI) models for wireless systems are commonly optimized for fixed tasks, channel distributions, and system configurations, which limits their reuse when dow…

cs.CV2025

Great X: A Unified Multi-Modal Simulator Bridging the Sim2Real Gap for 6G

Yuan Gao, Kongwu Huang, Jun Jiang +2

Large-scale, precisely synchronized multi-modal datasets are critical for data-driven sixth-generation (6G) wireless research, yet real-world collection remains costly and difficul…

eess.SP2025

C2S-AE: CSI to Sensing enabled by an Auto-Encoder-based Framework

Jun Jiang, Shugong Xu, Wenjun Yu +1

Next-generation mobile networks are set to utilize integrated sensing and communication (ISAC) as a critical technology, providing significant support for sectors like the industri…

eess.SP2025

A MIMO Wireless Channel Foundation Model via CIR-CSI Consistency

Jun Jiang, Wenjun Yu, Yunfan Li +2

In the field of artificial intelligence, self-supervised learning has demonstrated superior generalization capabilities by leveraging large-scale unlabeled datasets for pretraining…

eess.SP2025

MTCA: Multi-Task Channel Analysis for Wireless Communication

Jun Jiang, Wenjun Yu, Yuan Gao +1

In modern wireless communication systems, the effective processing of Channel State Information (CSI) is crucial for enhancing communication quality and reliability. However, curre…

cs.NI2024

SANDWICH: Towards an Offline, Differentiable, Fully-Trainable Wireless Neural Ray-Tracing Surrogate

Yifei Jin, Ali Maatouk, Sarunas Girdzijauskas +3

Wireless ray-tracing (RT) is emerging as a key tool for three-dimensional (3D) wireless channel modeling, driven by advances in graphical rendering. Current approaches struggle to…