Semi-Blind Joint Channel and Symbol Estimation for Beyond Diagonal Reconfigurable Surfaces
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arXiv
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| Autori principali: | , , , |
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| Natura: | Preprint |
| Pubblicazione: |
2025
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| _version_ | 1866915863733469184 |
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| author | de Araújo, Gilderlan Tavares de Almeida, André L. F. Sokal, Buno Fodor, Gabor |
| author_facet | de Araújo, Gilderlan Tavares de Almeida, André L. F. Sokal, Buno Fodor, Gabor |
| contents | The beyond-diagonal reconfigurable intelligent surface (BD-RIS) is a recent architecture in which scattering elements are interconnected to enhance the degrees of freedom for wave control, yielding performance gains over traditional single-connected RISs. For BD-RIS, channel estimation, which is well studied for conventional RIS, becomes more challenging due to complex connections and a larger number of coefficients. Previous works relied on pilot-assisted estimation followed by data decoding. This paper introduces a semi-blind tensor-based approach to joint channel and symbol estimation that eliminates the need for training sequences by directly leveraging data symbols. A practical scenario with time-varying user terminal-RIS channels under mobility is considered. By reformulating the received signal from a tensor-decomposition perspective, we develop two semi-blind receivers: a two-stage method that transforms the fourth-order PARATUCK model into a third-order PARAFAC model, and a single-stage iterative process based on the fourth-order TUCKER decomposition. Identifiability conditions for reliable joint recovery are derived, and numerical results demonstrate the performance advantages and trade-offs of the proposed schemes over existing solutions. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2512_15441 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Semi-Blind Joint Channel and Symbol Estimation for Beyond Diagonal Reconfigurable Surfaces de Araújo, Gilderlan Tavares de Almeida, André L. F. Sokal, Buno Fodor, Gabor Signal Processing The beyond-diagonal reconfigurable intelligent surface (BD-RIS) is a recent architecture in which scattering elements are interconnected to enhance the degrees of freedom for wave control, yielding performance gains over traditional single-connected RISs. For BD-RIS, channel estimation, which is well studied for conventional RIS, becomes more challenging due to complex connections and a larger number of coefficients. Previous works relied on pilot-assisted estimation followed by data decoding. This paper introduces a semi-blind tensor-based approach to joint channel and symbol estimation that eliminates the need for training sequences by directly leveraging data symbols. A practical scenario with time-varying user terminal-RIS channels under mobility is considered. By reformulating the received signal from a tensor-decomposition perspective, we develop two semi-blind receivers: a two-stage method that transforms the fourth-order PARATUCK model into a third-order PARAFAC model, and a single-stage iterative process based on the fourth-order TUCKER decomposition. Identifiability conditions for reliable joint recovery are derived, and numerical results demonstrate the performance advantages and trade-offs of the proposed schemes over existing solutions. |
| title | Semi-Blind Joint Channel and Symbol Estimation for Beyond Diagonal Reconfigurable Surfaces |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2512.15441 |