Over-the-Air Computation with Spatial-and-Temporal Correlated Signals
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arXiv
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| Main Authors: | , , , |
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| Format: | Preprint |
| Published: |
2021
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| _version_ | 1866910667692310528 |
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| author | Liu, Wanchun Zang, Xin Vucetic, Branka Li, Yonghui |
| author_facet | Liu, Wanchun Zang, Xin Vucetic, Branka Li, Yonghui |
| contents | Over-the-air computation (AirComp) leveraging the superposition property of wireless multiple-access channel (MAC), is a promising technique for effective data collection and computation of large-scale wireless sensor measurements in Internet of Things applications. Most existing work on AirComp only considered computation of spatial-and-temporal independent sensor signals, though in practice different sensor measurement signals are usually correlated. In this letter, we propose an AirComp system with spatial-and-temporal correlated sensor signals, and formulate the optimal AirComp policy design problem for achieving the minimum computation mean-squared error (MSE). We develop the optimal AirComp policy with the minimum computation MSE in each time step by utilizing the current and the previously received signals. We also propose and optimize a low-complexity AirComp policy in closed form with the performance approaching to the optimal policy. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2102_00664 |
| institution | arXiv |
| publishDate | 2021 |
| record_format | arxiv |
| spellingShingle | Over-the-Air Computation with Spatial-and-Temporal Correlated Signals Liu, Wanchun Zang, Xin Vucetic, Branka Li, Yonghui Information Theory Systems and Control Signal Processing Over-the-air computation (AirComp) leveraging the superposition property of wireless multiple-access channel (MAC), is a promising technique for effective data collection and computation of large-scale wireless sensor measurements in Internet of Things applications. Most existing work on AirComp only considered computation of spatial-and-temporal independent sensor signals, though in practice different sensor measurement signals are usually correlated. In this letter, we propose an AirComp system with spatial-and-temporal correlated sensor signals, and formulate the optimal AirComp policy design problem for achieving the minimum computation mean-squared error (MSE). We develop the optimal AirComp policy with the minimum computation MSE in each time step by utilizing the current and the previously received signals. We also propose and optimize a low-complexity AirComp policy in closed form with the performance approaching to the optimal policy. |
| title | Over-the-Air Computation with Spatial-and-Temporal Correlated Signals |
| topic | Information Theory Systems and Control Signal Processing |
| url | https://arxiv.org/abs/2102.00664 |