1 citations · 1 across the 6 of their papers we have counts for
6 papers
Amortized Neural SVD for XL-MIMO: Structure-Guided Factor Prediction for Beamforming and Multi-Stream Utility
Yue Zhang, Yiyan Zhang, Ruijin Sun +2
Singular value decomposition (SVD) is a core operation in multiple-input multiple-output (MIMO) beamforming, but the cubic complexity of standard SVD routines can lead to a major l…
RadioDiff-Flux: Efficient Radio Map Construction via Generative Denoise Diffusion Model Trajectory Midpoint Reuse
Xiucheng Wang, Peilin Zheng, Honggang Jia +4
Accurate radio map (RM) construction is essential to enabling environment-aware and adaptive wireless communication. However, in future 6G scenarios characterized by high-speed net…
RadioMapMotion: A Dataset and Baseline for Proactive Spatio-Temporal Radio Environment Prediction
Honggang Jia, Nan Cheng, Xiucheng Wang
Radio maps (RMs), which provide location-based pathloss estimations, are fundamental to enabling proactive, environment-aware communication in 6G networks. However, existing deep l…
UrbanMIMOMap: A Ray-Traced MIMO CSI Dataset with Precoding-Aware Maps and Benchmarks
Honggang Jia, Xiucheng Wang, Nan Cheng +2
Sixth generation (6G) systems require environment-aware communication, driven by native artificial intelligence (AI) and integrated sensing and communication (ISAC). Radio maps (RM…
RadioMamba: Breaking the Accuracy-Efficiency Trade-off in Radio Map Construction via a Hybrid Mamba-UNet
Honggang Jia, Nan Cheng, Xiucheng Wang +4
Radio map (RM) has recently attracted much attention since it can provide real-time and accurate spatial channel information for 6G services and applications. However, current deep…
Latent Diffusion Model Based Denoising Receiver for 6G Semantic Communication: From Stochastic Differential Theory to Application
Xiucheng Wang, Honggang Jia, Nan Cheng
In this paper, a novel semantic communication framework empowered by generative artificial intelligence (GAI) is proposed, to enhance the robustness against both channel noise and…