CARTS: Cooperative and Adaptive Resource Triggering and Stitching for 5G ISAC
Cheng Jiang, Yihe Yan, Yanxiang Wang, Jiawei Hu, Chun Tung Chou, Wen Hu

TL;DR
CARTS is an adaptive 5G uplink sensing scheme that fuses CSI streams from DMRS and SRS signals to enhance sensing accuracy and scalability without extra radio resources.
Contribution
CARTS introduces a novel channel stitching method and real-time SRS triggering to improve CSI update frequency and sensing opportunities in 5G ISAC systems.
Findings
Achieves a channel estimation error (NMSE) of 0.167.
Provides UE tracking accuracy of 85 cm.
Supports twice the number of users compared to baseline.
Abstract
This paper presents CARTS, an adaptive 5G uplink sensing scheme designed to provide Integrated Sensing and Communication (ISAC) services. The performance of both communication and sensing fundamentally depends on the availability of accurate and up-to-date channel state information (CSI). In modern 5G networks, uplink CSI is derived from two reference signals: the demodulation reference signal (DMRS) and the sounding reference signal (SRS). However, current base station implementations treat these CSI measurements as separate information streams. The key innovation of CARTS is to fuse these two CSI streams, thereby increasing the frequency of CSI updates and extending sensing opportunities to more users. CARTS addresses two key challenges: (i) a novel channel stitching and compensation method that integrates asynchronous CSI estimates from DMRS and SRS, despite their different time and…
Peer Reviews
No public reviews on file for this paper yet. If you reviewed it on a platform where reviews are public (OpenReview, ICLR, NeurIPS, ICML), you can paste yours below so the community can read it here.
Videos
No videos yet. Explain this paper in a talk, walkthrough, or lecture? Add one.
Taxonomy
TopicsIndoor and Outdoor Localization Technologies · Sparse and Compressive Sensing Techniques · Radar Systems and Signal Processing
