arXiv Machine Learning

Self-Localizing MIMO Beam Mapping for Intelligent Open RAN with Continuously Evolving Channel Memory

arXiv:2511. 17007v2 Announce Type: replace-cross Abstract: Open and intelligent radio access networks (RANs) envisioned for 6G require accurate and reusable wireless channel knowledge for intelligent inference and control.

arXiv Machine Learning

Jul 24

RadioTrace: Transmitter-Aware Diffusion for Radio Map Estimation without Deployment-Time Fine-Tuning

arXiv:2607. 20909v1 Announce Type: cross Abstract: Radio map (RM) estimation aims to reconstruct the spatial distribution of wireless signal characteristics, such as received signal strength (RSS), from sparse measurements, a task that is critical for spectrum management, interference mitigation, and localization in modern wireless networks.

By Liu Yang, Qiang Li, Zhuo Cao, Weijie Xiong, Guomin Sun, Jingran Lin

diffusion fine-tuning benchmarks

arXiv Machine Learning

Jun 11

NARRAS: Edge-Triggered Distributed Inference for CSI-Based Localization in Vehicular IoT Networks

arXiv:2606. 11914v1 Announce Type: cross Abstract: CSI-based localization with spatially distributed antenna arrays exposes a basic resource trade-off.

By Rodrigo Oliver, Ricardo Vazquez Alvarez, Alejandro Lancho, Stefano Rini

arXiv Machine Learning

Aug 12

Null-Space Flow Matching for MIMO Channel Estimation in Latency-Constrained Systems

arXiv:2604. 22005v2 Announce Type: replace-cross Abstract: Accurate yet low-latency channel state information (CSI) acquisition is essential for multiple-input multiple-output (MIMO) communication systems.

By Junjie Zhao, Guangming Liang, Xiaonan Liu, Dongzhu Liu

diffusion efficiency

arXiv AI

Jul 14

JEPA for AI-Native 6G: Predictive Representations and Open Challenges

arXiv:2607. 09798v1 Announce Type: cross Abstract: Sixth-generation (6G) networks are moving toward AI-native operation, where learning modules are embedded across the radio access network (RAN), edge, and core.

By Sheikh Salman Hassan, Irshad A. Meer, Almoatssimbillah Saifaldawla, Yan Kyaw Tun, Mustafa Ozger, Madyan Alsenwi, Nguyen Van Huynh, Woong-Hee Lee, Cedomir Stefanovic, Mathini Sellathurai, Henk Wymeersch, Tharmalingam Ratnarajah

rag diffusion benchmarks

arXiv AI

Jul 20

Map as a Prompt: Learning Multi-Modal Spatial-Signal Foundation Models for Cross-scenario Wireless Localization

arXiv:2607. 15713v1 Announce Type: cross Abstract: Accurate and robust wireless localization is a critical enabler for emerging 5G/6G applications, including autonomous driving, extended reality, and smart manufacturing.

By Yong Chu, Xun Zhou, Zenglin Xu, Hui Wang, Yue Yu

agents robotics multimodal benchmarks

arXiv Machine Learning

1d ago

Lightweight Deep Learning-Based Channel Estimation for RIS-Aided Extremely Large-Scale MIMO Systems on Resource-Limited Edge Devices

arXiv:2507. 09627v3 Announce Type: replace-cross Abstract: Next-generation wireless technologies such as 6G aim to meet demanding requirements such as ultra-high data rates, low latency, and enhanced connectivity.

By Muhammad Kamran Saeed, Ashfaq Khokhar, Shakil Ahmed

arXiv Machine Learning

Jun 11

OmniLoc: A Geometry-Aware Foundation Model for Anchor-Free UE Localization Across Diverse Indoor Environments

arXiv:2606. 11490v1 Announce Type: new Abstract: Indoor localization from wireless measurements remains challenging in large-scale deployments due to substantial variation in building geometry, the set of detectable access points (APs), and the heterogeneity of received signals.

By Lei Chu, Yuning Zhang, Omer Gokalp Serbetci, Anushka Katiyar, Bassel Abou Ali Modad, Andreas F. Molisch

llms rag nlp benchmarks

arXiv Machine Learning

Jun 16

Context-Aware Markov VAE for CSI Compression in Wireless Systems

arXiv:2606. 16607v1 Announce Type: cross Abstract: This paper considers neural channel state information (CSI) compression for time-varying massive multiple-input multiple-output (MIMO) channels in frequency division duplex (FDD) systems with limited feedback resources.

By Efstathios Chatziloizos, Konstantinos Vandikas, Aneta Vulgarakis Feljan, Zheng Chen, Nikolaos Pappas

diffusion

arXiv Machine Learning

Jul 24

Environment-Aware Channel Inference via Cross-Modal Flow: From Multimodal Sensing to Wireless Channels

arXiv:2512. 04966v2 Announce Type: replace-cross Abstract: Accurate channel state information (CSI) underpins reliable and efficient wireless communication.

By Guangming Liang, Mingjie Yang, Dongzhu Liu, Paul Henderson, Lajos Hanzo

diffusion multimodal benchmarks safety

arXiv AI

Jul 28

Fast Cross-Scenario Adaptation of CSI Models via Channel Conditional Parameter Generation

arXiv:2607. 22637v1 Announce Type: new Abstract: Deep learning has shown strong potential for massive multiple-input multiple-output (Massive MIMO) physical-layer tasks, including channel state information (CSI) feedback and channel estimation.

By Xudong Zou, Siyu Wu, Zunlei Feng, Jie Song, Yuanyu Wan, Mingli Song, Jiacong Hu

diffusion fine-tuning

arXiv AI

Jul 3

Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion

arXiv:2607. 01777v1 Announce Type: cross Abstract: Radio frequency (RF) maps provide a compact representation of multipath propagation characteristics and are fundamental to channel modeling, coverage analysis, and environment-aware wireless optimization.

By Lizhou Liu, Xiaohui Chen, Zihan Tang, Mengyao Ma, Wenyi Zhang

diffusion

arXiv Machine Learning

1d ago

RadioVIL: Anomaly-Aware Diffusion Models for Radio Map Inpainting and Zero-Shot Vehicle Localization

arXiv:2608. 16167v1 Announce Type: cross Abstract: High-precision radio map construction is essential for emerging 6G Integrated Sensing and Communication (ISAC) applications, including digital twins and intelligent transportation.

By Ruixin Zhao, Xiucheng Wang, Qiming Zhang, Nan Cheng, Ruijin Sun, Conghao Zhou

diffusion

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