8 papers
Theoretical Analysis of Diffusion Models for Radio Map Estimation with Ultra-low Sampling Rates
Zhiyuan Liu, Qingyu Liu, Shuhang Zhang +2
Radio maps, which characterize the spatial distribution of radio frequency metrics such as received signal strength, are essential for a wide range of wireless applications. The pr…
A Fine-Grained 3D Radio Map Construction Paradigm with Ultra-Low Sampling Rates by Large Generative Models
Zhiyuan Liu, Qingyu Liu, Shuhang Zhang +2
A radio map captures the spatial distribution of wireless channel parameters, such as the strength of the signal received, across a geographic area. The problem of fine-grained thr…
RIS-Aided Wireless Amodal Sensing for Single-View 3D Reconstruction
Yuhan Wang, Haobo Zhang, Qingyu Liu +2
Amodal sensing is critical for various real-world sensing applications because it can recover the complete shapes of partially occluded objects in complex environments. Among vario…
RadioPiT: Radio Map Generation with Pixel Transformer Driven by Ultra-Sparse Real-World Data
Zeyao Sun, Bohao Fan, Qingyu Liu +2
As wireless communication networks rapidly evolve, spectrum resources are increasingly scarce, making effective spectrum management critically important. Radio map is a spatial rep…
WiFi-Diffusion: Achieving Fine-Grained WiFi Radio Map Estimation With Ultra-Low Sampling Rate by Diffusion Models
Zhiyuan Liu, Shuhang Zhang, Qingyu Liu +2
Fine-grained radio map presents communication parameters of interest, e.g., received signal strength, at every point across a large geographical region. It can be leveraged to impr…
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…