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From Sparse Probes to Sum-Rate Maximization: Electromagnetic Twin Beamforming

Tuo Wu, Kangda Zhi, Jie Tang, Jianchao Zheng, Naofal Al-Dhahir, Fumiyuki Adachi

eess.SParXiv:2608.20846

Abstract

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.

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