7 papers
Temporal Channel Estimation for Generalized CSI Feedback
Minwoo Kim, Hyeonsu Lyu, Sehyun Ryu +2
Efficient Channel State Information (CSI) feedback is indispensable for frequency division duplex (FDD) massive multiple-input multiple-output (MIMO) systems. Existing compressed s…
Beam-Response Contrastive Learning for Transmitter-Side MIMO CSI Representation
Sehyun Ryu, Yumin Kim, Minjae Lee +2
Self-supervised representation learning from unlabeled channel state information (CSI) can reduce labeling and adaptation overhead in learning-based multiple-input multiple-output…
Advancing Multi-Robot Networks via MLLM-Driven Sensing, Communication, and Computation: A Comprehensive Survey
Hyun Jong Yang, Howon Lee, Kyuhong Shim +10
Imagine advanced humanoid robots, powered by multimodal large language models (MLLMs), coordinating missions across industries like warehouse logistics, manufacturing, and safety r…
Blockage-Aware Multi-RIS WSR Maximization via Per-RIS Indexed Synchronization Sequences and Closed-Form Riemannian Updates
Sehyun Ryu, Hyun Jong Yang
Millimeter-wave (mmWave) multi-user MIMO systems are highly vulnerable to blockage, and reconfigurable intelligent surfaces (RIS) have been proposed as a remedy. However, RIS links…
Standards-Compliant DM-RS Allocation via Temporal Channel Prediction for Massive MIMO Systems
Sehyun Ryu, Hyun Jong Yang
Reducing feedback overhead in beyond 5G networks is a critical challenge, as the growing number of antennas in modern massive MIMO systems substantially increases the channel state…
Deeper Understanding of Black-box Predictions via Generalized Influence Functions
Hyeonsu Lyu, Jonggyu Jang, Sehyun Ryu +1
Influence functions (IFs) elucidate how training data changes model behavior. However, the increasing size and non-convexity in large-scale models make IFs inaccurate. We suspect t…