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| Autores principales: | , , , , , , |
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| Formato: | Preprint |
| Publicado: |
2024
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| Materias: | |
| Acceso en línea: | https://arxiv.org/abs/2412.02778 |
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| _version_ | 1866918528405209088 |
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| author | Benício, Kenneth Fazal-E-Asim Sokal, Bruno de Almeida, André L. F. Makki, Behrooz Fodor, Gabor Swindlehurst, A. Lee |
| author_facet | Benício, Kenneth Fazal-E-Asim Sokal, Bruno de Almeida, André L. F. Makki, Behrooz Fodor, Gabor Swindlehurst, A. Lee |
| contents | We study a monostatic multiple-input multiple-output sensing scenario assisted by a reconfigurable intelligent surface using tensor signal modeling. We propose a method that exploits the intrinsic multidimensional structure of the received echo signal, allowing us to recast the target sensing problem as a nested tensor-based decomposition problem to jointly estimate the delay, Doppler, and angular information of the target. We derive a two-stage approach based on the alternating least squares algorithm followed by the estimation of the signal parameters via rotational invariance techniques to extract the target parameters. Simulation results show that the proposed tensor-based algorithm yields accurate estimates of the sensing parameters with low complexity. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2412_02778 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | RIS-Assisted Sensing: A Nested Tensor Decomposition-Based Approach Benício, Kenneth Fazal-E-Asim Sokal, Bruno de Almeida, André L. F. Makki, Behrooz Fodor, Gabor Swindlehurst, A. Lee Signal Processing We study a monostatic multiple-input multiple-output sensing scenario assisted by a reconfigurable intelligent surface using tensor signal modeling. We propose a method that exploits the intrinsic multidimensional structure of the received echo signal, allowing us to recast the target sensing problem as a nested tensor-based decomposition problem to jointly estimate the delay, Doppler, and angular information of the target. We derive a two-stage approach based on the alternating least squares algorithm followed by the estimation of the signal parameters via rotational invariance techniques to extract the target parameters. Simulation results show that the proposed tensor-based algorithm yields accurate estimates of the sensing parameters with low complexity. |
| title | RIS-Assisted Sensing: A Nested Tensor Decomposition-Based Approach |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2412.02778 |