The Vienna 4G/5G Drive-Test Dataset is a city‑scale open dataset of georeferenced LTE and 5G NR measurements collected across Vienna, Austria. It combines passive wideband scanner observations with active handset logs, offering complementary network‑side and user‑side views of deployed radio access networks. The dataset includes inferred base‑station deployment descriptors, high‑resolution building and terrain models, and is organized into scanner, handset, estimated cell information, and city‑model components to support reproducible benchmarking in environment‑aware learning, propagation modeling, coverage analysis, and ray‑tracing calibration workflows.
By Wilfried Wiedner, Lukas Eller, Mariam Mussbah, Dominik R\"ossler, Valerian Maresch, Philipp Svoboda, Markus Rupp
arXiv:2608. 07444v1 Announce Type: cross Abstract: Accurate user equipment (UE) localization is critical for beam management in reconfigurable intelligent surface (RIS)-assisted millimeter-wave (mmWave) based sixth-generation (6G) networks, especially if the direct base-station-UE links are unavailable.
By Md Tarek Hassan, Dmitry Zelenchuk, Muhammad Ali Babar Abbasi
arXiv:2609.32923v2 Announce Type: replace
Abstract: Wireless digital twins (DTs) rely on 3D environment models to predict radio propagation and support wireless-network decisions, yet these models ar...
By Saad Masrur, Saeed R. Khosravirad, Ismail Guvenc
arXiv:2608. 14599v1 Announce Type: cross Abstract: The placement of base station (BS) is a fundamental determinant of coverage and capacity of urban wireless networks.
By Zhenyu Tao, Yuxuan Li, Wei Xu, Yongming Huang, Xiaohu You
The paper introduces Physics-Unrolled Hybrid Neural Operator (PU‑HNO), a three‑stage cascade that transforms low‑fidelity ray‑tracing outputs and scene priors into high‑fidelity indoor radio maps by sequentially modeling reflection, diffraction, and scattering. It demonstrates that, under conditionally unbiased label noise, the model can learn stable propagation structures and surpass its own training labels. Experiments on varied floorplans show PU‑HNO outperforming image‑to‑image baselines, wireless learning models, and monolithic neural operators in both image quality and wireless deployment metrics.
By Rafid Umayer Murshed, Saif Ur Rahman, Mingyue Tang, Elahe Soltanaghai
arXiv:2605.08211v2 Announce Type: replace-cross
Abstract: Channel-gain maps provide the channel gain between any two locations in a geographical region. They find numerous applications, from resource...
By Prasenjit Dhara, Daniel Romero
arXiv:2608. 09285v1 Announce Type: cross Abstract: Learning-based wireless localizers often fail to utilize geometric information about the propagation environment, limiting their ability to exploit non-line-of-sight (NLoS) propagation and generalize across scenes.
By Chenghong Bian, Chaozheng Wen, Hongze Chen, Jun Zhang
arXiv:2604. 22056v3 Announce Type: replace Abstract: Optimal wireless transmitter placement is a central task in radio-network planning, and exhaustive search becomes prohibitively expensive at scale.
By \c{C}a\u{g}kan Yapar
arXiv:2508. 03736v2 Announce Type: replace-cross Abstract: In this paper, we present a deep learning-based approach that integrates the DINOv2 architecture to improve building mapping by combining (possibly erroneous) maps from open-source platforms with pervasive radio frequency (RF) data collected from multiple wireless user equipments and base stations.
By Rafayel Mkrtchyan, Armen Manukyan, Hrant Khachatrian, Theofanis P. Raptis
arXiv:2609.07298v2 Announce Type: replace
Abstract: 3D reconstruction typically strives for geometric fidelity or visual plausibility. Radio frequency digital twins (RFDT) are instead judged by wheth...
By Maximiliano Wardle, A. Ryo Koblitz
arXiv:2511. 05522v4 Announce Type: replace-cross Abstract: Accurate, low-latency channel modeling is essential for real-time wireless network simulation and digital-twin applications.
By Ali Saeizadeh, Miead Tehrani-Moayyed, Davide Villa, J. Gordon Beattie Jr., Pedram Johari, Stefano Basagni, Tommaso Melodia
arXiv:2605.01777v2 Announce Type: replace-cross
Abstract: An evolution of Wireless Communications towards 5G and beyond provides improved user experience in terms of quality of services. Understandin...
By A. Sathi Babu, V. Udaya Sankar, Vishnu Ram OV