10 papers · 1 filter
GLocFM: A Geometry-Aware Foundation Model for 3D Indoor Wireless Localization
Chenghong Bian, Chaozheng Wen, Hongze Chen +1
Learning-based wireless localizers often fail to utilize geometric information about the propagation environment, limiting their ability to exploit non-line-of-sight (NLoS) propaga…
P-WRFGS: Pruning 3D Gaussians for Efficient Wireless Radiance Field Construction
Chenghong Bian, Meng Hua, Deniz Gunduz
Wireless channel modeling is a key building block for next-generation wireless systems. Predicting the channel state information (CSI) across different transmitter locations can su…
In-Context Learning for Deep Joint Source-Channel Coding Over MIMO Channels
Meng Hua, Wenjing Zhang, Chenghong Bian +1
Large language models have demonstrated the ability to perform \textit{in-context learning} (ICL), whereby the model performs predictions by directly mapping the query and a few ex…
LISAC: Learned Coded Waveform Design for ISAC with OFDM
Chenghong Bian, Yumeng Zhang, Meng Hua +2
We propose deep learning based coded waveform design for integrated sensing and communication (ISAC) with orthogonal frequency-division multiplexing (OFDM). Our goal is to design a…
Over-the-Air Learning-based Geometry Point Cloud Transmission
Chenghong Bian, Yulin Shao, Deniz Gunduz
This paper presents novel solutions for the efficient and reliable transmission of point clouds over wireless channels for real-time applications. We first propose SEmatic Point cl…
Towards AI-Native Fronthaul: Neural Compression for NextG Cloud RAN
Chenghong Bian, Yulin Shao, Deniz Gunduz
The rapid growth of data traffic and the emerging AI-native wireless architectures in NextG cellular systems place new demands on the fronthaul links of Cloud Radio Access Networks…