3 papers
cs.NI2026
On the Physical Plausibility and Distribution Alignment for Sim-to-Real RF Positioning
Ararat Saribekyan, Armen Manukyan, Hrant Khachatrian +1
Reliable radio frequency (RF) positioning from cellular measurements is limited by the high cost and limited coverage of real drive-test data, especially when models must work on s…
cs.CV2025
Fusion of Pervasive RF Data with Spatial Images via Vision Transformers for Enhanced Mapping in Smart Cities
Rafayel Mkrtchyan, Armen Manukyan, Hrant Khachatrian +1
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…
cs.NI2025
On the Limitations of Ray-Tracing for Learning-Based RF Tasks in Urban Environments
Armen Manukyan, Hrant Khachatrian, Edvard Ghukasyan +1
We study the realism of Sionna v1.0.2 ray-tracing for outdoor cellular links in central Rome. We use a real measurement set of 1,664 user-equipments (UEs) and six nominal base-stat…