5 papers
RadioFormer3D: Weakly Supervised 3D Radio Map Estimation in Low-Altitude Airspace via Generative Modeling
Zheng Fang, Junjie Liu, Kangjun Liu +3
With the emergence of wireless applications in three-dimensional environments, such as the low-altitude airspace and 3D heterogeneous networks, radio map estimation is increasingly…
Bridging the Sampling Distribution Shift in Radio Map Estimation: A Trajectory-Aware Paradigm
Feng Qiu, Zheng Fang, Shuhang Zhang +4
Learning-based radio map estimation (RME) plays a critical role in UAV-assisted wireless sensing, enabling tasks such as coverage prediction and network optimization. Most current…
RadioDUN: A Physics-Inspired Deep Unfolding Network for Radio Map Estimation
Taiqin Chen, Zikun Zhou, Zheng Fang +5
The radio map represents the spatial distribution of spectrum resources within a region, supporting efficient resource allocation and interference mitigation. However, it is diffic…
RadioFormer: A Multiple-Granularity Radio Map Estimation Transformer with 1\textpertenthousand Spatial Sampling
Zheng Fang, Kangjun Liu, Ke Chen +4
The task of radio map estimation aims to generate a dense representation of electromagnetic spectrum quantities, such as the received signal strength at each grid point within a ge…
Generative AI on SpectrumNet: An Open Benchmark of Multiband 3D Radio Maps
Shuhang Zhang, Shuai Jiang, Wanjie Lin +4
Radio map is an efficient demonstration for visually displaying the wireless signal coverage within a certain region. It has been considered to be increasingly helpful for the futu…