3D Cooperative User Tracking for Distributed Integrated Sensing and Communication

TL;DR

This paper introduces a comprehensive framework for cooperative user tracking in distributed integrated sensing and communication systems, utilizing a global PHD filter and AP management to achieve high accuracy with optimized resource use.

Contribution

It proposes a novel framework combining PHD filtering and AP management for accurate, resource-efficient user tracking in DISAC systems, validated through real-world measurements.

Findings

Centimeter-level trajectory accuracy achieved.

APs do not need to be active constantly for high tracking performance.

Framework effectively balances tracking accuracy and AP energy consumption.

Abstract

As integrated sensing and communication (ISAC) becomes an integral part of 6G networks, distributed ISAC (DISAC) is expected to enhance both sensing and communication performance through its decentralized architecture. This paper presents a complete framework to address the challenge of cooperative user tracking in DISAC systems. By incorporating a global probability hypothesis density (PHD) filter and a field-of-view-aware access point (AP) management strategy, the framework enables accurate user tracking using radio signals while optimizing AP scheduling. In addition, a real-world distributed MIMO channel measurement campaign is performed to evaluate the effectiveness of the framework. The results demonstrate that a centimeter-level root mean-square trajectory error can be achieved. Furthermore, the results show that it is not necessary to keep APs active at all times to maintain high tracking accuracy, indicating the need for robust and efficient AP management. These findings provide valuable insights into practical deployments and the further development of cooperative user tracking techniques in DISAC systems.