Joint BS Deployment and Power Optimization for Minimum EMF Exposure with RL in Real-World Based Urban Scenario
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arXiv
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| Autores principales: | , , , , |
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| Formato: | Preprint |
| Publicado: |
2025
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| _version_ | 1866914235571765248 |
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| author | Long, Xueyun Li, Yueheng Pauli, Mario Nuss, Benjamin Zwick, Thomas |
| author_facet | Long, Xueyun Li, Yueheng Pauli, Mario Nuss, Benjamin Zwick, Thomas |
| contents | Base station (BS) deployment remains a critical task with successive wireless communication generations and increasing data rates demands, while the electromagnetic field (EMF) exposure is often underrated, yielding potential health implications. Therefore, this paper proposes a workflow that adjusts BS deployment and radiated power in a 3D urban scenario to jointly consider EMF exposure and coverage. To achieve this ambition, firstly, a novel least-time shoot-and-bounce ray (SBR) ray-launching (RL) tool is developed to improve computational efficiency, and simultaneously enhance diffraction modeling} for accurate EMF exposure calculation, validated with real-world measurements. To efficiently extend the computation across the target urban area, the adaptive grid refinement (AGR) algorithm is designed based on the spatial stability of the effective channel while accounting for BS beamforming, enabling global estimation of EMF exposure and signal coverage. Subsequently, to better represent real-world communication network behaviors, the actual maximum transmit power, intercell interference, and channel state information imperfection are incorporated on the BS side, while mobility over the EMF exposure averaging interval is captured on the user equipment side. Upon the aforementioned aspects, the coverage-guaranteed EMF exposure minimization problem is formulated in a realistic and accurate manner, and solved by a geometry-aware algorithm adapted to deterministic channel models, yielding the optimal BS deployment and power configuration. In comparison to a baseline that relies on an empirical channel model, the proposed workflow delivers more reliable estimation of EMF exposure and provides practical guidance for BS construction and operations. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2504_05017 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Joint BS Deployment and Power Optimization for Minimum EMF Exposure with RL in Real-World Based Urban Scenario Long, Xueyun Li, Yueheng Pauli, Mario Nuss, Benjamin Zwick, Thomas Signal Processing Base station (BS) deployment remains a critical task with successive wireless communication generations and increasing data rates demands, while the electromagnetic field (EMF) exposure is often underrated, yielding potential health implications. Therefore, this paper proposes a workflow that adjusts BS deployment and radiated power in a 3D urban scenario to jointly consider EMF exposure and coverage. To achieve this ambition, firstly, a novel least-time shoot-and-bounce ray (SBR) ray-launching (RL) tool is developed to improve computational efficiency, and simultaneously enhance diffraction modeling} for accurate EMF exposure calculation, validated with real-world measurements. To efficiently extend the computation across the target urban area, the adaptive grid refinement (AGR) algorithm is designed based on the spatial stability of the effective channel while accounting for BS beamforming, enabling global estimation of EMF exposure and signal coverage. Subsequently, to better represent real-world communication network behaviors, the actual maximum transmit power, intercell interference, and channel state information imperfection are incorporated on the BS side, while mobility over the EMF exposure averaging interval is captured on the user equipment side. Upon the aforementioned aspects, the coverage-guaranteed EMF exposure minimization problem is formulated in a realistic and accurate manner, and solved by a geometry-aware algorithm adapted to deterministic channel models, yielding the optimal BS deployment and power configuration. In comparison to a baseline that relies on an empirical channel model, the proposed workflow delivers more reliable estimation of EMF exposure and provides practical guidance for BS construction and operations. |
| title | Joint BS Deployment and Power Optimization for Minimum EMF Exposure with RL in Real-World Based Urban Scenario |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2504.05017 |