用3D高斯点云建模环境，实现无瞬时信道信息的快速波束成形。
GSBF: Gaussian Splatting for Environment-Aware Beamforming
- 通过多模态数据构建持久化3D高斯环境表示，利用双向球面高斯核建模散射特性。
- 无需实时信道状态信息，直接从基站姿态和用户位置合成波束，延迟更低。
- 适合低延迟通信场景，尤其适用于动态环境中快速波束对准的系统设计。
波束成形在多输入多输出（MIMO）通信系统中起关键作用。然而，传统波束成形设计通常需要精确的瞬时信道状态信息（CSI）和迭代优化，带来巨大的导频开销和计算复杂度。鉴于无线传播本质上受物理几何结构支配，我们基于多模态数据开发了一种用于环境感知波束成形的3D高斯点云方法（GSBF），通过持续的3D高斯表示刻画环境。具体而言，GSBF使用保持互易性的双向球面高斯（Bi-SG）核建模环境散射响应，并执行双向电磁光栅化以生成角度传播图。该图随后通过过完备阵列流形字典聚合，并投影至恒定模长波束成形器，从而直接从接入点（AP）姿态和用户位置合成波束，无需在线瞬时CSI。仿真表明，GSBF在所有测试条件下均优于穷举波束对齐（EBA）基线，且具有更低延迟。
原文摘要 · Abstract (English)
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.
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