Hybrid TRP-UE Sensing for Enhanced Target Localization

2026-06-18

AI Summary

This study addresses the challenge of low localization accuracy for passive mobile targets in complex propagation environments, such as indoor factories. To overcome this limitation, the authors propose a hybrid TRP–UE cooperative sensing mechanism that, for the first time, deeply integrates user equipment (UE)-assisted sensing with base station (TRP) sensing within a 3GPP-compliant integrated sensing and communication (ISAC) architecture. By synergistically combining these two sensing modalities, the proposed approach significantly enhances the robustness and accuracy of target localization in challenging scenarios. Experimental results demonstrate that, in a representative indoor factory setting, the hybrid sensing scheme achieves substantial performance gains over a conventional TRP-only configuration, confirming its effectiveness in improving localization precision under realistic and complex channel conditions.

Abstract

Integrated Sensing and Communication (ISAC) refers to the capability for the network to provide communications services whilst also being able to sense the environment in a scalable manner. One of the key functions of ISAC is the accurate localization of passive and mobile sensing targets. This paper introduces a novel hybrid TRP-UE sensing mechanism that improves network-based sensing performance. Evaluation results are provided using 3GPP-compliant ISAC channel models. The results demonstrate the significant benefit in complimenting TRP-based sensing with UE-assisted sensing in challenging propagation environments such as indoor factory.

Problem

• Integrated Sensing and Communication
• target localization
• TRP-UE sensing
• challenging propagation environments
• 3GPP-compliant ISAC

Innovation

• Hybrid TRP-UE sensing
• Integrated Sensing and Communication (ISAC)
• Target localization
• UE-assisted sensing
• 3GPP-compliant channel model