AI 中文总结
该研究针对传统波束成形依赖瞬时CSI导致开销高的问题，提出GSBF方法，通过3D高斯表示刻画环境，利用Bi-SG核与电磁光栅化合成波束，仿真显示其性能优于EBA且延迟更低。
AI 中文摘要
波束成形在多输入多输出（MIMO）通信系统中发挥关键作用，但传统波束成形设计通常需要准确的瞬时信道状态信息（CSI）和迭代优化，导致显著的导频开销和计算复杂度。鉴于无线电传播本质上受物理几何约束，我们开发了基于多模态数据的环境感知波束成形高斯溅射（GSBF）流程，通过持久的3D高斯表示刻画环境。具体而言，GSBF采用保持互易性的双向球形高斯（Bi-SG）核建模环境散射响应，并执行双向电磁光栅化以渲染角度传播子图；该渲染图随后通过超完备阵列流形字典聚合，并投影到恒模波束成形器，从而无需在线瞬时CSI，仅从接入点（AP）位姿和用户位置直接合成波束。仿真结果表明，GSBF始终优于穷举波束对齐（EBA）等基线方法，且延迟更低。
英文摘要
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.
