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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2503.13043 |
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| _version_ | 1866917008262561792 |
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| author | Schmitt, Eva Julia Noack, Benjamin |
| author_facet | Schmitt, Eva Julia Noack, Benjamin |
| contents | Resources such as bandwidth and energy are limited in many wireless communications use cases, especially when large numbers of sensors and fusion centers need to exchange information frequently. One opportunity to overcome resource constraints is the use of event-based transmissions and estimation to transmit only information that contributes significantly to the reconstruction of the system's state. The design of efficient triggering policies and estimators is crucial for successful event-based transmissions. While previously deterministic and stochastic event triggering policies have been treated separately, this paper unifies the two approaches and gives insights into the design of consistent trigger-matching estimators. Two different estimators are presented, and different pairs of triggers and estimators are evaluated through simulation studies. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2503_13043 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | A Unified Framework for Innovation-based Stochastic and Deterministic Event Triggers Schmitt, Eva Julia Noack, Benjamin Systems and Control Resources such as bandwidth and energy are limited in many wireless communications use cases, especially when large numbers of sensors and fusion centers need to exchange information frequently. One opportunity to overcome resource constraints is the use of event-based transmissions and estimation to transmit only information that contributes significantly to the reconstruction of the system's state. The design of efficient triggering policies and estimators is crucial for successful event-based transmissions. While previously deterministic and stochastic event triggering policies have been treated separately, this paper unifies the two approaches and gives insights into the design of consistent trigger-matching estimators. Two different estimators are presented, and different pairs of triggers and estimators are evaluated through simulation studies. |
| title | A Unified Framework for Innovation-based Stochastic and Deterministic Event Triggers |
| topic | Systems and Control |
| url | https://arxiv.org/abs/2503.13043 |