Type-Based Unsourced Multiple Access Over Fading Channels in Distributed MIMO With Application to Multi-Target Localization

TL;DR

This paper introduces a type-based unsourced multiple access method for fading channels in distributed MIMO systems, enabling efficient multi-target localization without channel state information by leveraging location-based codebook partitioning and advanced message passing algorithms.

Contribution

It extends prior TUMA work to fading scenarios without channel state info and applies it to multi-target localization with a novel cost function for performance evaluation.

Findings

Effective type estimation over fading channels without CSI.

Location-based codebook partitioning mitigates path-loss variability.

Performance depends on sensing resources and quantization bits.

Abstract

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.