Radio Propagation Modeling

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3 papers in the last four weeks, down 25% on the four weeks before. 0.0% of all new papers.

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LiLib: Lifelong Air-to-Ground Path-Loss Prediction on UAVs via a Drift-Triggered Model Library
Oct 5, 2026Minh TranConcept Drift Wireless Communications
Hanoi University of Science and Technology (HUST), Hanoi, Vietnam
TRACE: Learning to Self-Calibrate Wireless Digital Twins from ISAC Measurements
Sep 26, 2026Saad Masrur, Saeed R. Khosravirad, Ismail GuvencRadio Propagation Modeling Digital Twins
Department of Electrical and Computer Engineering, North Carolina State University, Raleigh, NC · Radio Systems Research, Nokia Bell Labs, Murray Hill, NJ, USA
Rethinking Radiomap Blind Prediction with Limited Environment and Configuration Representations
Sep 10, 2026Xiaojie Li, Yu Han, Han Fang +3Residual Learning Cross-Domain Generalization
School of Information Science and Engineering, Southeast University, Nanjing 210096, China · National Mobile Communications Research Laboratory, Southeast University, Nanjing 210096, China · School of Cyber Science and Engineering, Southeast University, Nanjing 210096, China +2
KODAMA: Multimodal Digital Twin Reconstruction for Urban RF Propagation Modelling
Sep 7, 2026Maximiliano Wardle, A. Ryo Koblitz3D Reconstruction Radio Propagation Modeling
Nokia Bell Labs · University of York
Tri-Band Channel Measurement-Enabled Multi-Layer Digital Twin for Terahertz Wireless Data Centers
Sep 1, 2026Mingjie Zhu, Ziming Yu, Guangjian Wang +1Wireless Communications Radio Propagation Modeling
Terahertz Wireless Communications (TWC) Interdisciplinary Research Center, Shanghai Jiao Tong University, Shanghai 200240, China · Huawei Technologies Company Ltd., Chengdu 611731, China · Terahertz Wireless Communications (TWC) Interdisciplinary Research Center, and Cooperative Medianet Innovation Center (CMIC), School of Information Science and Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
BeamRMX: Radiation-Pattern-Driven Learning for Generalizable Beam Radio Map Prediction and Beam Management
Sep 1, 2026Yue Zhang, Xiucheng Wang, Wenshuo Chen +16G Networks Radio Propagation Modeling
State Key Laboratory of ISN and the School of Telecommunications Engineering, Xidian University, Xi’an 710071, China · The Hong Kong University of Science and Technology (Guangzhou), Guangzhou 511453, China
A Systematic Sample Size Analysis of ML-Based Path Loss Prediction for LPWAN
Aug 11, 2026Robert Bitterling, Christian Nettersheim, Jörn Hees +1Wireless Communications Radio Propagation Modeling
Fraunhofer FKIE · Hochschule Bonn-Rhein-Sieg Cyber Analysis & Defense Department of Computer Science Wachtberg, Germany
ControlRadio: Prompt-Driven Controllable Diffusion for Cross-Modal Radio Map Generation
Aug 10, 2026Kangjun Liu, Xiying Pan, Shuhang Zhang +3Wireless Communications Generative Modeling
Pengcheng Laboratory, China · South China University of Technology and the Pengcheng Laboratory, China · Peking University, China +2
GSBF: Gaussian Splatting for Environment-Aware Beamforming
Aug 6, 2026Yijie Bian, Wei Guo, Zixin Wang +33D Gaussian Splatting Wireless Communications
Dept. of ECE, The Hong Kong University of Science and Technology, Hong Kong, China
MultiPathFormer: Towards a Foundation Model for Multipath Wireless Propagation
Aug 5, 2026Blessed Guda, Kayley Sze, Carlee Joe-WongWireless Foundation Models Wireless Localization
Carnegie Mellon University Pittsburgh, USA
Generative Models for Modeling and Synthesizing MIMO Channels in Adverse Weather Conditions
Jul 31, 2026Vignesh Nandakumar, Faraz Barati, Brian L. EvansSynthetic Data Generation Wireless Communications
Point2Radio: A Foundation Model for Cross-Scene Radio Fields from Material-Aware Point Clouds
Jul 31, 2026Chaozheng Wen, Chenghong Bian, Hongze Chen +1Wireless Foundation Models Wireless Communications
Hong Kong University of Science and Technology
mmRadarTwin: A Measurement-Calibrated Signal-Level Digital Twin Platform for Indoor mmWave Radar
Jul 30, 2026Jianyi Zhou, Chenghao Zhang, Yanli Li +1Millimeter-Wave Radar mmWave Radar Sensing
The University of Sydney · Sydney, NSW, Australia
SymNet: A Multi-Task Network for Joint Radio Map Reconstruction and Transmitter Localization
Jul 30, 2026Lyuzhou Ye, Thanh Dat Le, Yan HuangMulti-Task Learning Wireless Communications
University of North Texas 1155 Union Circle Denton, Texas
CORF-GS: Real-Time Wireless Radiance Field Reconstruction via Coupled Optical-RF Gaussian Splatting
Jul 28, 2026Jinya Zhang, Jiajia Guo, Chao-Kai Wen +13D Gaussian Splatting Streaming 3D Reconstruction
Low-Altitude Channel Multipath Prediction via Panoramic Perception and Vision-Language Model
Jul 24, 2026Zihang Zeng, Shu Sun, Meixia Tao +3Wireless Communications Radio Propagation Modeling
School of Information Science and Electronic Engineering, Shanghai Jiao Tong University, Shanghai 200240, China
EA-RMENet -- Path Loss Prediction in Urban Environments using Deep Learning
Jul 17, 2026Jonathan O'Shea, Conor BrennanRadio Propagation Modeling Dense Prediction
DCU School of Electronic Engineering
HybridSim: A Physics-Learning Hybrid Digital Twin for mmWave Human Sensing
Jul 17, 2026Weitao Xiong, Tianyu Liu, Peng Li +4Synthetic Data Generation Millimeter-Wave Radar
1Xiamen University Malaysia · 2The Hong Kong University of Science and Technology · University of North Carolina at Charlotte
CFM-Bench: A Unified Multi-Domain, Multi-Task Benchmark for Channel Foundation Models
Jul 16, 2026Yuan Gao, Wenjun Yu, Jun Jiang +3Wireless Foundation Models Benchmark Design
School of Communication and Information Engineering, Shanghai University, Shanghai, China · Xi’an Jiaotong-Liverpool University, Suzhou, China
Physics-Aware Conditional SetGAN for Spatially Consistent Multi-User TR 38.901 Channel Generation
Jul 13, 2026Mauro Gonzalo Tarazona-Levano, David Lopez-Perez, Nicola Piovesan +1Wireless Communications Radio Propagation Modeling
Institute of Telecommunications and Multimedia Applications (iTEAM), Universitat Politècnica de València (UPV), Spain · Beihang Valencia Polytechnic Institute (BVPI), China · Huawei Technologies, France
RadioDiff-v2: Generative Angular Radio Maps for Multi-Beam Selection and Localization
Jul 9, 2026Xiucheng Wang, Junxi Huang, Nan ChengDiffusion Transformer 6G Networks
State Key Laboratory of ISN and School of Telecommunications Engineering, Xidian University, Xi’an 710071, China
Scene-Conditioned PINN-GNN for Multipath RF Maps: Cross-Scene Generation and In-Scene Completion
Jul 2, 2026Lizhou Liu, Xiaohui Chen, Zihan Tang +2Wireless Communications Radio Propagation Modeling
Department of Electronic Engineering and Information Science, University of Science and Technology of China, Hefei, Anhui 230026, China · Wireless Technology Lab, Huawei, Shenzhen 518129, China
QuaMoE-DRF: Proactive Beam and Rate Adaptation via Multimodal Dynamic Radio Map Forecasting in ISAC Networks
Jul 1, 2026Zhihan Zeng, Kaihe Wang, Zhongpei Zhang +1Integrated Sensing and Communication Wireless Communications
National Key Laboratory of Wireless Communications, University of Electronic Science and Technology of China, Chengdu 611731, China · University of Electronic Science and Technology of China, Chengdu 611731, China · College of Information Science and Electronic Engineering, Zhejiang University, Hangzhou 310027, China +2
Multi-Modal Conditioned High-Resolution Transformer for Urban Electromagnetic Field Map Prediction Download PDF
Jun 26, 2026Do-Eon Kim, Dongryul Park, Seungyoung Ahn +3Transformer Wireless Communications
Soongsil University, Seoul 06978, Republic of Korea · Cho Chun Shik Graduate School of Mobility, Korea Advanced Institute of Science and Technology, Daejeon 34051, Republic of Korea · Department of Intelligent Semiconductors, Soongsil University, Seoul 06978, Republic of Korea
Point-Cloud-Assistant Localized Statistical Channel Prediction by Tangent Gaussian Splatting
Jun 17, 2026Ye Xue, Yiheng Wang, Xinhua Shao +3Point Cloud Learning Wireless Communications
RMPrior: Bridging Propagation Priors and Diffusion Refinement for Efficient Radio Map Construction
Jun 2, 2026Zixuan Guo, Xiucheng Wang, Nan ChengFew-Step Diffusion Sampling Wireless Communications
School of Physics, Xidian University, Xi’an, 710071, China · State Key Laboratory of ISN and School of Telecommunications Engineering, Xidian University, Xi’an, 710071, China
RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling
May 28, 2026Zheng Fang, Junjie Liu, Kangjun Liu +33D Reconstruction Wireless Communications
Pengcheng Laboratory, China · Department of Computer Science and Engineering, Southern University of Science and Technology, Shenzhen, China · Harbin Institute of Technology, Shenzhen, China
GeoGS-CE: Learning Delay--Beam Channel Priors with 3D Gaussians for High-Mobility Scenarios
May 15, 2026Yumeng Zhang, Jiajia Guo, Chaozheng Wen +2Wireless Communications Radio Propagation Modeling
iComAI Lab, HKUST
PropSplat: Map-Free RF Field Reconstruction via 3D Gaussian Propagation Splatting
May 8, 2026William Bjorndahl, Maninder Pal Singh, Farhad Nouri +13D Gaussian Splatting Wireless Communications
Department of Electrical and Computer Engineering, Southern Methodist University, Dallas, TX, USA · Department of Engineering Technology, University of Houston, Houston, TX, USA
Differentiable Ray Tracing with Gaussians for Unified Radio Propagation Simulation and View Synthesis
May 8, 2026Niklas Vaara, Lam Huynh, Pekka Sangi +23D Gaussian Splatting Differentiable Rendering
Center for Machine Vision and Signal Analysis, University of Oulu, Finland · CubiCasa Oy, Finland

Oct 5, 2026, cs.LGJ/K move · Enter open · S save

LiLib: Lifelong Air-to-Ground Path-Loss Prediction on UAVs via a Drift-Triggered Model Library

Minh Tran

Hanoi University of Science and Technology (HUST), Hanoi, Vietnam

Concept Drift Wireless Communications Radio Propagation Modeling Online Continual Learning

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UAVs that act as relays or base stations need accurate air-to-ground path-loss predictions for rate adaptation and placement, but propagation conditions change as a UAV moves between suburban, urban and high-rise areas, and the same areas are often revisited. Online regressors that adapt by forgetting must relearn each environment from scratch, whereas a single model trained on all data averages incompatible regimes. We propose LiLib, a lightweight continual-learning scheme in which a UAV maintains a small library of recursive-least-squares experts. A windowed residual test detects drift; a short probe phase then either reuses the best stored expert or creates a new one. In simulations based on four standard urbanization profiles, LiLib reduces prediction RMSE from 5.89 dB (best sliding-window baseline) to 4.03 dB (p < 0.001), lowers the error shortly after a return to a known environment from 12.3 dB to 5.7 dB, and recovers 99% of the throughput of a regime-aware oracle in rate adaptation. The library stores four experts in under 0.5 KB, and identifies regimes with 92% purity without labels. When a second UAV is initialized with the library of a peer, its error after environment changes halves. LiLib does not reach the oracle, and similar regimes may be merged when shadowing is strong. The results indicate that, for recurring drift, remembering is more effective than re-adapting.

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