CORF-GS: Real-Time Wireless Radiance Field Reconstruction via Coupled Optical-RF Gaussian Splatting

2026-07-28

AI Summary

This work addresses the limitation of existing wireless radiance field (WRF) reconstruction methods, which rely on offline optimization and thus struggle to support real-time channel modeling. The authors propose CORF-GS, a novel framework that achieves, for the first time, real-time coupled optimization of optical and radio-frequency (RF) Gaussian splatting. By employing a unified Gaussian representation with shared geometry and modality-specific appearance, the method leverages optical images as structural priors and performs optical-guided Gaussian densification and joint optimization upon arrival of each new keyframe. This enables the shared geometry to simultaneously conform to both optical structure and RF power distribution. The approach supports keyframe-driven incremental reconstruction, significantly improving RF spectral synthesis quality in simulations and achieving a 6.4× speedup over current WRF methods.

Abstract

Recent advances in 3D Gaussian Splatting (3DGS)-based wireless radiance field (WRF) reconstruction provide an efficient solution for wireless channel modeling. However, existing WRF reconstruction methods rely on pre-collected observations and offline optimization, and thus struggle to provide real-time channel knowledge. To bridge this gap, we propose CORF-GS, a real-time WRF reconstruction framework that processes sequential optical and radio frequency (RF) keyframes. Specifically, CORF-GS constructs a unified Gaussian representation for optical and RF with shared geometry and modality-specific appearance, allowing high-resolution optical images to provide structural priors for WRF reconstruction. When a new keyframe arrives, CORF-GS first employs optical-guided Gaussian sampling to densify the WRF in under-represented regions. Since light and radio waves may respond differently to the same object surfaces due to wavelength mismatch, relying solely on optical guidance may neglect RF-informative areas. Therefore, CORF-GS performs coupled optical-RF optimization to jointly refine the shared Gaussians. Compared with the existing two-stage training pipelines, this prevents WRF from passively adapting to a frozen optical geometry and encourages the shared Gaussians to adapt to both optical structures and RF power distributions. Simulations show that CORF-GS achieves state-of-the-art RF spectrum synthesis quality and reduces the reconstruction time by $6.4\times$ compared with existing WRF methods.

Problem

• wireless radiance field
• real-time reconstruction
• 3D Gaussian Splatting
• channel modeling
• optical-RF fusion

Innovation

• Gaussian Splatting
• Wireless Radiance Field
• Real-Time Reconstruction
• Optical-RF Fusion
• Coupled Optimization