Gespeichert in:
| Hauptverfasser: | , , , , , |
|---|---|
| Format: | Preprint |
| Veröffentlicht: |
2025
|
| Schlagworte: | |
| Online-Zugang: | https://arxiv.org/abs/2505.23154 |
| Tags: |
Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
|
| _version_ | 1866909626641940480 |
|---|---|
| author | Yilmaz, Osman Mert Yilmaz, Tayfun Gorcin, Ali Hokelek, Ibrahim Guvenkaya, Ertugrul Ilhan, Haci |
| author_facet | Yilmaz, Osman Mert Yilmaz, Tayfun Gorcin, Ali Hokelek, Ibrahim Guvenkaya, Ertugrul Ilhan, Haci |
| contents | By intelligently reconfiguring wireless propagation environment, reconfigurable intelligent surfaces (RISs) can enhance signal quality, suppress interference, and improve channel conditions, thereby serving as a powerful complement to multiple-input multiple-output (MIMO) architectures. However, jointly optimizing the RIS phase shifts and the MIMO transmit precoder in 5G and beyond networks remains largely unexplored. This paper addresses this gap by proposing a singular value ($λ$)-based RIS optimization strategy, where the phase shifts are configured to maximize the dominant singular values of the cascaded channel matrix, and the corresponding singular vectors are utilized for MIMO transmit precoding. The proposed precoder selection does not require mutual information computation across subbands, thereby reducing time complexity. To solve the $λ$-based optimization problem, maximum cross-swapping algorithm (MCA) is applied while an effective rank-based method is utilized for benchmarking purposes. The simulation results show that the proposed precoder selection method consistently outperforms the conventional approach under $λ$-based RIS optimization. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2505_23154 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Joint Phase Shift Optimization and Precoder Selection for RIS-Assisted 5G NR MIMO Systems Yilmaz, Osman Mert Yilmaz, Tayfun Gorcin, Ali Hokelek, Ibrahim Guvenkaya, Ertugrul Ilhan, Haci Signal Processing By intelligently reconfiguring wireless propagation environment, reconfigurable intelligent surfaces (RISs) can enhance signal quality, suppress interference, and improve channel conditions, thereby serving as a powerful complement to multiple-input multiple-output (MIMO) architectures. However, jointly optimizing the RIS phase shifts and the MIMO transmit precoder in 5G and beyond networks remains largely unexplored. This paper addresses this gap by proposing a singular value ($λ$)-based RIS optimization strategy, where the phase shifts are configured to maximize the dominant singular values of the cascaded channel matrix, and the corresponding singular vectors are utilized for MIMO transmit precoding. The proposed precoder selection does not require mutual information computation across subbands, thereby reducing time complexity. To solve the $λ$-based optimization problem, maximum cross-swapping algorithm (MCA) is applied while an effective rank-based method is utilized for benchmarking purposes. The simulation results show that the proposed precoder selection method consistently outperforms the conventional approach under $λ$-based RIS optimization. |
| title | Joint Phase Shift Optimization and Precoder Selection for RIS-Assisted 5G NR MIMO Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2505.23154 |