Stability Conditions for Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels
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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.
Key facts. Cited by 4 papers in the map (data through 7 Oct 2026). First posted on arXiv 9 Apr 2021.
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Citing papers per year: 2022: 2; 2023: 0; 2024: 1; 2025: 1.
4 papers.
- 2022Structure-Enhanced DRL for Optimal Transmission Schedulingcited by 6
- 2022Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Schedulingcited by 1
- 2024Wireless Human-Machine Collaboration in Industry 5.0cited by 0
- 2025Goal-oriented Transmission Scheduling: Structure-guided DRL with a Unified Dual On-policy and Off-policy Approachcited by 0
- 2025Goal-oriented Transmission Scheduling: Structure-guided DRL with a Unified Dual On-policy and Off-policy Approach21 Jan 2025
- 2024Wireless Human-Machine Collaboration in Industry 5.018 Oct 2024
- 2022Structure-Enhanced DRL for Optimal Transmission Scheduling24 Dec 2022
- 2022Structure-Enhanced Deep Reinforcement Learning for Optimal Transmission Scheduling20 Nov 2022