# Stability Conditions for Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels

arXiv: https://arxiv.org/abs/2104.04181 · HTML: https://mlsanity.com/paper/2104.04181/

## Key facts

- Cited by 4 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 9 Apr 2021.

## Built on by (most cited first, 4 of 4)

- [Structure-Enhanced DRL for Optimal Transmission Scheduling](https://mlsanity.com/paper/2212.12704/) (2022)
- [Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling](https://mlsanity.com/paper/2211.10827/) (2022)
- [Wireless Human-Machine Collaboration in Industry 5.0](https://mlsanity.com/paper/2410.14153/) (2024)
- [Goal-oriented Transmission Scheduling: Structure-guided DRL with a Unified Dual On-policy and Off-policy Approach](https://mlsanity.com/paper/2501.11921/) (2025)

## Abstract (arXiv)

We investigate the stability conditions for remote state estimation of multiple linear time-invariant (LTI) systems over multiple wireless time-varying communication channels. We answer the following open problem: what is the fundamental requirement on the multi-sensor-multi-channel system to guarantee the existence of a sensor scheduling policy that can stabilize the remote estimation system? We propose a novel policy construction and analytical framework and derive the necessary-and-sufficient stability condition in terms of the LTI system parameters and the channel statistics.