2023/12/21 by Ruoxiao Cao, Cao, Ruoxiao, Hengtao He +13 · 1 citation
Engineering · #FOS: Computer and information sciences #FOS: Electrical engineering #Indoor and Outdoor Localization Technologies #Information Theory (cs.IT) #Microwave Imaging and Scattering Analysis #Signal Processing (eess.SP) #Sparse and Compressive Sensing Techniques #electronic engineering #information engineering
paper · pdf · doi:10.48550/arxiv.2312.13683
openalex publication_date 2023/12/21 · openalex created_date 2023/12/23 · openalex updated_date 2026/07/28
The next-generation wireless networks are envisioned to jointly support high-rate communications and ubiquitous sensing. Ultra-Massive Multiple-Input Multiple-Output (UM-MIMO) offers abundant spatial Degrees of Freedom (DoFs) for both functions, yet its large aperture shifts electromagnetic propagation into the near field, invalidating conventional far-field (plane-wave) assumptions. While near-field channel modeling has been studied, existing channel estimation methods are inadequate: on-grid designs suffer from non-orthogonal codebooks, and off-grid methods lack convergence guarantees, yielding unreliable estimates. Moreover, channel estimation and localization are typically designed in isolation, preventing the exchange of information that could otherwise enable mutual performance improvement. To address this difficulty, we propose a unified framework that exploits near-field characteristics to jointly design channel estimation and cooperative localization. Specifically, we develop a Variational Newtonized Near-field Channel Estimation (VNNCE) algorithm that extracts position-aware soft information from the channel, and a Gaussian Fusion Cooperative Localization (GFCL) method that leverages this information across multiple Base Stations (BSs) for enhanced accuracy.