In closed-loop distributed multi-sensor integrated sensing and communication (ISAC) systems, performance often hinges on transmitting high-dimensional sensor observations over rate-limited networks. In this paper, we first present a general framework for rate-limited closed-loop distributed ISAC systems, and then propose an autoencoder-based observation compression method to overcome the constraints imposed by limited transmission capacity. Building on this framework, we conduct a case study using a closed-loop linear quadratic regulator (LQR) system to analyze how the interplay among observation, compression, and state dimensions affects reconstruction accuracy, state estimation error, and control performance. In multi-sensor scenarios, our results further show that optimal resource allocation initially prioritizes low-noise sensors until the compression becomes lossless, after which resources are reallocated to high-noise sensors.
View on arXiv@article{pan2025_2505.01780,
title={ Rate-Limited Closed-Loop Distributed ISAC Systems: An Autoencoder Approach },
author={ Guangjin Pan and Zhixing Li and Ayça Özçelikkale and Christian Häger and Musa Furkan Keskin and Henk Wymeersch },
journal={arXiv preprint arXiv:2505.01780},
year={ 2025 }
}