Base Station Placement Optimization for Networked Sensing Exploiting Target Location Distribution
Fuente:
arXiv
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| Autores principales: | , |
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| Formato: | Preprint |
| Publicado: |
2025
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| Acceso en línea: | |
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| _version_ | 1866909775357280256 |
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| author | Hou, Kaiyue Zhang, Shuowen |
| author_facet | Hou, Kaiyue Zhang, Shuowen |
| contents | This paper studies a networked sensing system with multiple base stations (BSs), which collaboratively sense the unknown and random three-dimensional (3D) location of a target based on the target-reflected echo signals received at the BSs. Considering a practical scenario where the target location distribution is known a priori for exploitation, we aim to design the placement of the multiple BSs to optimize the networked sensing performance. Firstly, we characterize the posterior Cramér-Rao bound (PCRB) of the mean-squared error (MSE) in sensing the target's 3D location. Despite its complex form under networked sensing, we derive its closed-form expression in terms of the BS locations. Next, we formulate the BS placement optimization problem to minimize the sensing PCRB, which is non-convex and difficult to solve. By leveraging a series of equivalent transformations and the iterative inner approximation method, we devise an algorithm with polynomial-time complexity which is guaranteed to converge to a solution satisfying the Karush-Kuhn Tucker (KKT) conditions of the problem. Numerical results show that the proposed placement design significantly outperforms various benchmark designs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_16236 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Base Station Placement Optimization for Networked Sensing Exploiting Target Location Distribution Hou, Kaiyue Zhang, Shuowen Information Theory Signal Processing This paper studies a networked sensing system with multiple base stations (BSs), which collaboratively sense the unknown and random three-dimensional (3D) location of a target based on the target-reflected echo signals received at the BSs. Considering a practical scenario where the target location distribution is known a priori for exploitation, we aim to design the placement of the multiple BSs to optimize the networked sensing performance. Firstly, we characterize the posterior Cramér-Rao bound (PCRB) of the mean-squared error (MSE) in sensing the target's 3D location. Despite its complex form under networked sensing, we derive its closed-form expression in terms of the BS locations. Next, we formulate the BS placement optimization problem to minimize the sensing PCRB, which is non-convex and difficult to solve. By leveraging a series of equivalent transformations and the iterative inner approximation method, we devise an algorithm with polynomial-time complexity which is guaranteed to converge to a solution satisfying the Karush-Kuhn Tucker (KKT) conditions of the problem. Numerical results show that the proposed placement design significantly outperforms various benchmark designs. |
| title | Base Station Placement Optimization for Networked Sensing Exploiting Target Location Distribution |
| topic | Information Theory Signal Processing |
| url | https://arxiv.org/abs/2505.16236 |