相干直接D-MIMO定位

中文摘要 AI 辅助

分布式多输入多输出（D-MIMO）被视为未来无线系统的关键部署架构，可通过空间分离提升覆盖范围与鲁棒性，还具备利于定位与感知的良好几何结构。其在定位方面的最大潜力在于分布式天线面板间的联合相干处理，但严苛的频率同步、相位校准要求，以及多模态似然函数阻碍了估计过程。因此，多数现有算法以非相干方式处理面板，可能牺牲定位精度。本文提出一类统一的贝叶斯状态空间滤波器，基于集中的I型和边缘II型似然函数，适用于宽带近场D-MIMO系统，可直接对含噪信道观测值进行处理。I型滤波器明确实现（i）非相干、（ii）相干、（iii）载波相位处理。对于II型滤波，研究表明零均值模型在分布式处理下本质为非相干，而观测值堆叠可恢复相干性；非零均值模型能自动适配数据中可用的相干性，该特性被称为“软相干”。本文推导了三种相干水平下的后验克拉美-罗下界（PCRLB），证明每种水平与用于定位或作为冗余参数处理的相位参数数量根本相关。数值结果显示，对应相干水平的滤波器性能接近各自的PCRLB，且相干处理可大幅优于非相干处理。本文还推导了基于粒子的置信传播方法，该方法可在粒子与分布式面板间并行，随观测数据线性缩放，在GPU加速实现中每时间步运行时间为数十毫秒。

英文摘要

Distributed multiple-input multiple-output (D-MIMO) offers favorable geometry for localization and sensing, with its greatest potential arising from joint coherent processing across panels. However, stringent frequency-synchronization and phase-calibration requirements, together with multimodal likelihood functions, complicate the estimation problem. Consequently, most existing methods process the panels noncoherently, potentially sacrificing localization accuracy. We present a unified family of Bayesian state filters based on concentrated Type-I and marginal Type-II likelihoods for wideband near-field D-MIMO systems. The Type-I filters realize (i) noncoherent, (ii) coherent, and (iii) carrier-phase-based processing. We show that a zero-mean Type-II model is inherently noncoherent under distributed processing, whereas observation stacking restores coherence. A recently proposed nonzero-mean Type-II model adapts to the coherence available in the data, a property termed ``soft coherence.'' We derive posterior Cramér--Rao lower bounds (PCRLBs) for all three coherence levels and show that each level is fundamentally tied to the number of phase parameters used for positioning or treated as nuisance parameters. Numerical results show that the filters closely approach their respective PCRLBs and that coherent processing substantially outperforms noncoherent processing. Our particle-based implementations parallelize over particles and panels, scale linearly with the observed data, and achieve runtimes of tens of milliseconds per time step under GPU acceleration.

发表机构

• Institute of Comm. Networks and Satellite Comms., Graz University of Technology（通信网络与卫星通信研究所，格拉茨工业大学）

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