Phases Calibration of RIS Using Backpropagation Algorithm
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arXiv
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| Hauptverfasser: | , , , , |
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| Format: | Preprint |
| Veröffentlicht: |
2024
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| _version_ | 1866913432470552576 |
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| author | Zhang, Wei Zhou, Bin Zhang, Tianyi Jiang, Yi Bu, Zhiyong |
| author_facet | Zhang, Wei Zhou, Bin Zhang, Tianyi Jiang, Yi Bu, Zhiyong |
| contents | Reconfigurable intelligent surface (RIS) technology has emerged in recent years as a promising solution to the ever-increasing demand for wireless communication capacity. In practice, however, elements of RIS may suffer from phase deviations, which need to be properly estimated and calibrated. This paper models the problem of over-the-air (OTA) estimation of the RIS elements as a quasi-neural network (QNN) so that the phase estimates can be obtained using the classic backpropagation (BP) algorithm. We also derive the Cramér Rao Bounds (CRBs) for the phases of the RIS elements as a benchmark of the proposed approach. The simulation results verify the effectiveness of the proposed algorithm by showing that the root mean square errors (RMSEs) of the phase estimates are close to the CRBs. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2407_11329 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | Phases Calibration of RIS Using Backpropagation Algorithm Zhang, Wei Zhou, Bin Zhang, Tianyi Jiang, Yi Bu, Zhiyong Signal Processing Reconfigurable intelligent surface (RIS) technology has emerged in recent years as a promising solution to the ever-increasing demand for wireless communication capacity. In practice, however, elements of RIS may suffer from phase deviations, which need to be properly estimated and calibrated. This paper models the problem of over-the-air (OTA) estimation of the RIS elements as a quasi-neural network (QNN) so that the phase estimates can be obtained using the classic backpropagation (BP) algorithm. We also derive the Cramér Rao Bounds (CRBs) for the phases of the RIS elements as a benchmark of the proposed approach. The simulation results verify the effectiveness of the proposed algorithm by showing that the root mean square errors (RMSEs) of the phase estimates are close to the CRBs. |
| title | Phases Calibration of RIS Using Backpropagation Algorithm |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2407.11329 |