On the Value of Base Station Motion Knowledge for Goal-Oriented Remote Monitoring with Energy-Harvesting Sensors
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arXiv
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| Autori principali: | , , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2026
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| _version_ | 1866911457016283136 |
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| author | Siriwardana, Sehani Sant'Ana, Jean Michel de Souza Souza, Richard Demo Zakeri, Abolfazl López, Onel Luis Alcaraz |
| author_facet | Siriwardana, Sehani Sant'Ana, Jean Michel de Souza Souza, Richard Demo Zakeri, Abolfazl López, Onel Luis Alcaraz |
| contents | This paper investigates goal-oriented remote monitoring of an unobservable Markov source using energy-harvesting sensors that communicate with a mobile receiver, such as a Low Earth Orbit (LEO) satellite or Unmanned Aerial Vehicle (UAV). Unlike conventional systems that assume stationary base stations, the proposed framework explicitly accounts for receiver mobility, which induces time-varying channel characteristics modeled as a finite-state Markov process. The remote monitoring problem is formulated as a partially observable Markov decision process (POMDP), which is transformed into a tractable belief-state MDP and solved using relative value iteration to obtain optimal sampling and transmission policies. Two estimation strategies are considered: Maximum Likelihood (ML) and Minimum Mean Distortion (MMD). Numerical results demonstrate that incorporating receiver mobility and channel state information into the optimization reduces the average distortion by 10% to 42% compared to baseline policies and constant-channel assumptions, highlighting the importance of base station motion knowledge for effective goal-oriented communication. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2602_17247 |
| institution | arXiv |
| publishDate | 2026 |
| record_format | arxiv |
| spellingShingle | On the Value of Base Station Motion Knowledge for Goal-Oriented Remote Monitoring with Energy-Harvesting Sensors Siriwardana, Sehani Sant'Ana, Jean Michel de Souza Souza, Richard Demo Zakeri, Abolfazl López, Onel Luis Alcaraz Systems and Control Networking and Internet Architecture This paper investigates goal-oriented remote monitoring of an unobservable Markov source using energy-harvesting sensors that communicate with a mobile receiver, such as a Low Earth Orbit (LEO) satellite or Unmanned Aerial Vehicle (UAV). Unlike conventional systems that assume stationary base stations, the proposed framework explicitly accounts for receiver mobility, which induces time-varying channel characteristics modeled as a finite-state Markov process. The remote monitoring problem is formulated as a partially observable Markov decision process (POMDP), which is transformed into a tractable belief-state MDP and solved using relative value iteration to obtain optimal sampling and transmission policies. Two estimation strategies are considered: Maximum Likelihood (ML) and Minimum Mean Distortion (MMD). Numerical results demonstrate that incorporating receiver mobility and channel state information into the optimization reduces the average distortion by 10% to 42% compared to baseline policies and constant-channel assumptions, highlighting the importance of base station motion knowledge for effective goal-oriented communication. |
| title | On the Value of Base Station Motion Knowledge for Goal-Oriented Remote Monitoring with Energy-Harvesting Sensors |
| topic | Systems and Control Networking and Internet Architecture |
| url | https://arxiv.org/abs/2602.17247 |