发表机构
Xidian University; The Hong Kong University of Science and Technology (Guangzhou)（西安电子科技大学; 香港科技大学（广州））
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
提出BeamRMX框架，将空间辐射图作为BeamRM查询学习场景几何到接收功率场的转换，实验显示在未见场景和配置上平均绝对误差显著降低，跨配置证据可改善重建与波束细化。
AI 中文摘要
第六代（6G）无线网络的演进推动了更大规模的天线阵列和高度定向的多波束传输，这使得对波束相关空间覆盖的准确掌握对于波束管理和环境感知型网络运行至关重要。无线电地图（RM）提供了此类表示，但传统RM预测假设采用全向或发射机级辐射。在波束成形多输入多输出（MIMO）系统中，同一传播场景会产生许多与配置相关的波束无线电地图（BeamRM），这给波束表示和泛化带来了挑战。现有方法要么基于波束描述符进行预测，要么将波束图作为通用架构的辅助输入。我们提出了BeamRMX，据我们所知，这是首个将空间辐射图作为主要BeamRM查询并学习场景几何如何将其转换为接收功率场的专用框架。XBase学习辐射查询与场景几何之间的多尺度交互，而可选的证据适配器则使用来自同一场景的少量跨配置BeamRM。匹配域和零样本实验显示，与确定性和扩散基线相比取得了一致的性能提升，包括在未见场景上平均绝对误差降低26.1%，在未见配置上降低47.8%。跨配置证据进一步改善了重建和扇区内波束细化。
英文摘要
The evolution toward sixth-generation (6G) wireless networks is driving larger antenna arrays and highly directional multi-beam transmission, making accurate knowledge of beam-dependent spatial coverage important for beam management and environment-aware network operation. Radio maps (RMs) provide such a representation, yet conventional RM prediction assumes omnidirectional or transmitter-level radiation. In beamformed multiple-input multiple-output (MIMO) systems, one propagation scene instead gives rise to many configuration-dependent beam radio maps (BeamRMs), creating challenges in beam representation and generalization. Existing methods either condition prediction on beam descriptors or use beam maps as auxiliary inputs to generic architectures. We propose BeamRMX, which, to the best of our knowledge, is the first dedicated framework to treat the spatial radiation pattern as the primary BeamRM query and learn how scene geometry transforms it into the received power field. XBase learns multiscale interactions between the radiation query and scene geometry, while an optional Evidence Adapter uses a few cross-configuration BeamRMs from the same scene. Matched-domain and zero-shot experiments show consistent gains over deterministic and diffusion baselines, including mean absolute error reductions of 26.1\% on unseen scenes and 47.8\% on an unseen configuration. Cross-configuration evidence further improves reconstruction and intra-sector beam refinement.
Comments13 pages
