Vision-Assisted Digital Twin Creation for mmWave Beam Management
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
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2024
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| _version_ | 1866909089332723712 |
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| author | Arnold, Maximilian Major, Bence Massoli, Fabio Valerio Soriaga, Joseph B. Behboodi, Arash |
| author_facet | Arnold, Maximilian Major, Bence Massoli, Fabio Valerio Soriaga, Joseph B. Behboodi, Arash |
| contents | In the context of communication networks, digital twin technology provides a means to replicate the radio frequency (RF) propagation environment as well as the system behaviour, allowing for a way to optimize the performance of a deployed system based on simulations. One of the key challenges in the application of Digital Twin technology to mmWave systems is the prevalent channel simulators' stringent requirements on the accuracy of the 3D Digital Twin, reducing the feasibility of the technology in real applications. We propose a practical Digital Twin creation pipeline and a channel simulator, that relies only on a single mounted camera and position information. We demonstrate the performance benefits compared to methods that do not explicitly model the 3D environment, on downstream sub-tasks in beam acquisition, using the real-world dataset of the DeepSense6G challenge |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2401_17781 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Vision-Assisted Digital Twin Creation for mmWave Beam Management Arnold, Maximilian Major, Bence Massoli, Fabio Valerio Soriaga, Joseph B. Behboodi, Arash Signal Processing Machine Learning In the context of communication networks, digital twin technology provides a means to replicate the radio frequency (RF) propagation environment as well as the system behaviour, allowing for a way to optimize the performance of a deployed system based on simulations. One of the key challenges in the application of Digital Twin technology to mmWave systems is the prevalent channel simulators' stringent requirements on the accuracy of the 3D Digital Twin, reducing the feasibility of the technology in real applications. We propose a practical Digital Twin creation pipeline and a channel simulator, that relies only on a single mounted camera and position information. We demonstrate the performance benefits compared to methods that do not explicitly model the 3D environment, on downstream sub-tasks in beam acquisition, using the real-world dataset of the DeepSense6G challenge |
| title | Vision-Assisted Digital Twin Creation for mmWave Beam Management |
| topic | Signal Processing Machine Learning |
| url | https://arxiv.org/abs/2401.17781 |