AI 中文总结
针对无线地图更新时全位置探测成本高的问题，提出电磁双（ET）波束成形，通过稀疏探测结合图正则化估计等技术实现和速率最大化，在1%或7%探测下性能优于静态信道知识地图，接近完美协方差波束成形。
AI 中文摘要
在无线地图每次更新时探测所有候选位置的成本很高。本文提出电磁双（ET）波束成形，将稀疏空间探测转化为和速率决策。ET存储与位置相关的角功率谱，通过图正则化估计更新其创新，并查询用户协方差以进行投影波束优化。速率灵敏度边界通过查询加权后验方差减少选择后续探测。在1%随机探测下，ET波束成形达到2.69 bit/s/Hz，而静态信道知识地图为1.12 bit/s/Hz；在7%查询感知探测下，其达到3.03 bit/s/Hz，与完美协方差波束成形的差距为3.4%。
英文摘要
Probing every candidate location at each wireless-map update is costly. This letter develops electromagnetic-twin (ET) beamforming that converts sparse spatial probes into a sum-rate decision. The ET stores a location-dependent angular power spectrum, updates its innovation through graph-regularized estimation, and queries user covariances for projected beam optimization. A rate-sensitivity bound selects subsequent probes by query-weighted posterior-variance reduction. With 1\% random probes, ET beamforming achieves $2.69$ bit/s/Hz versus $1.12$ for a static channel knowledge map; with 7\% query-aware probes, it reaches $3.03$ bit/s/Hz, within 3.4\% of perfect-covariance beamforming.
