We consider the problem of type estimation over unsourced multiple access fading channels in distributed multiple-input multiple-output (D-MIMO) systems. Unlike classical unsourced multiple access, type-based unsourced multiple access (TUMA) aims to estimate the type, i.e., the empirical distribution of transmitted messages. We extend our prior work on TUMA over additive white Gaussian channels to fading scenarios in which neither the transmitters nor the receiver have channel state information. To mitigate the impact of path-loss variability, we employ location-based codebook partitioning: users with similar large-scale fading coefficients use the same codebook. The decoder is built on the multisource approximate message passing algorithm proposed by Cakmak et al. (2025), and supports both centralized and distributed implementations. As an application, we demonstrate how TUMA enables efficient communication in a multi-target localization setting, where distributed sensors report to a D-MIMO receiver quantized target positions. We propose a performance cost function that combines localization errors with a misdetection penalty, and use it to characterize how performance depends on the fraction of resources assigned to sensing vs. communication, as well as on the number of bits used to quantize the positions of the targets.

翻译：本文研究分布式多输入多输出系统中衰落信道下基于类型的无源多址接入问题。与经典无源多址接入不同，基于类型的无源多址接入旨在估计类型，即传输消息的经验分布。我们将先前在加性高斯白噪声信道上的TUMA研究扩展至衰落场景，其中发射端与接收端均不掌握信道状态信息。为减轻路径损耗变异性的影响，我们采用基于位置的码本划分方案：具有相似大尺度衰落系数的用户使用相同码本。解码器基于Cakmak等人提出的多源近似消息传递算法构建，支持集中式与分布式两种实现方式。作为应用案例，我们展示了TUMA如何在多目标定位场景中实现高效通信——分布式传感器向D-MIMO接收器上报量化后的目标位置。我们提出了一种融合定位误差与漏检惩罚的性能代价函数，并借此刻画性能如何依赖于分配给感知与通信的资源比例，以及用于量化目标位置的比特数。