GSBF: Gaussian Splatting for Environment-Aware Beamforming
Abstract
Beamforming plays a key role in multiple-input-multiple-output (MIMO) communication systems. However, conventional beamforming design normally requires accurate instantaneous channel state information (CSI) and iterative optimization, which incur substantial pilot overhead and computational complexity. Recognizing that radio propagation is intrinsically governed by the physical geometry, we develop a 3D Gaussian splatting for environment-aware beamforming (GSBF) pipeline based on multi-modal data, which characterizes the environment through a persistent 3D Gaussian representation. Specifically, GSBF models the environmental scattering response with reciprocity-preserving bidirectional spherical Gaussian (Bi-SG) kernels and performs two-sided electromagnetic rasterization to render an angular propagator map. The rendered map is then aggregated through an over-complete array-manifold dictionary and projected to the constant-modulus beamformers, thereby synthesizing beams directly from the access point (AP) pose and user position without online instantaneous CSI. Simulations demonstrate that GSBF consistently outperforms baselines such as exhaustive beam alignment (EBA) with lower latency.
Related
- Task-Aware Beamforming for Semantic Wireless Localization
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- Universal CKM for Environment-Aware Wireless Networks: Enabling Cross-Device and Cross-Task Channel Knowledge Transfer
- Geometry-Aware Block Selection for Sparse Variational Gaussian Processes
- Deep Reinforcement Learning for Blind Passive Beamforming in RIS-Assisted MIMO Systems
BibTeX
@misc{bian2026gsbf,
title = {{GSBF: Gaussian Splatting for Environment-Aware Beamforming}},
author = {Yijie Bian and Wei Guo and Zixin Wang and Shenghui Song and Jun Zhang and Khaled B. Letaief},
howpublished = {arXiv},
year = {2026},
month = aug,
doi = {10.48550/arxiv.2608.05896},
eprint = {2608.05896},
archivePrefix = {arXiv},
url = {https://arxiv.org/abs/2608.05896},
}
RIS
TY - UNPB
TI - GSBF: Gaussian Splatting for Environment-Aware Beamforming
AU - Yijie Bian
AU - Wei Guo
AU - Zixin Wang
AU - Shenghui Song
AU - Jun Zhang
AU - Khaled B. Letaief
PY - 2026
DA - 2026/08/16
PB - arXiv
DO - 10.48550/arxiv.2608.05896
UR - https://arxiv.org/abs/2608.05896
AB - Beamforming plays a key role in multiple-input-multiple-output (MIMO) communication systems. However, conventional beamforming design normally requires accurate instantaneous channel state information (CSI) and iterative optimization, which incur substantial pilot overhead and computational complexity. Recognizing that radio propagation is intrinsically governed by the physical geometry, we develop a 3D Gaussian splatting for environment-aware beamforming (GSBF) pipeline based on multi-modal data, which characterizes the environment through a persistent 3D Gaussian representation. Specifically, GSBF models the environmental scattering response with reciprocity-preserving bidirectional spherical Gaussian (Bi-SG) kernels and performs two-sided electromagnetic rasterization to render an angular propagator map. The rendered map is then aggregated through an over-complete array-manifold dictionary and projected to the constant-modulus beamformers, thereby synthesizing beams directly from the access point (AP) pose and user position without online instantaneous CSI. Simulations demonstrate that GSBF consistently outperforms baselines such as exhaustive beam alignment (EBA) with lower latency.
ER -