Hybrid Precoding Revisited: Low-Dimensional Subspace Perspective for MU-MIMO Systems
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arXiv
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| Format: | Preprint |
| Published: |
2025
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| _version_ | 1866915658509320192 |
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| author | Oh, Mintaek Choi, Jinseok |
| author_facet | Oh, Mintaek Choi, Jinseok |
| contents | This letter presents a low-complexity hybrid precoding framework for multiuser multiple-input multiple-output (MIMO) systems by leveraging a low-dimensional subspace property. Under the low-dimensional subspace perspective, we first identify an unconstrained optimal radio-frequency (RF) precoder. We then optimize a hybrid precoder via a reduced-complexity precoding method. We further extend the proposed framework to (i) a dynamic-subarray antenna partitioning algorithm that adaptively allocates subsets of antennas associated with RF chains, and (ii) a channel covariance-based approach to exploit statistical channel state information at a transmitter (CSIT), ensuring robustness with partial CSIT. Simulations validate that our proposed algorithms achieve superior performance while significantly reducing complexity compared to existing methods. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2508_16218 |
| institution | arXiv |
| publishDate | 2025 |
| record_format | arxiv |
| spellingShingle | Hybrid Precoding Revisited: Low-Dimensional Subspace Perspective for MU-MIMO Systems Oh, Mintaek Choi, Jinseok Signal Processing This letter presents a low-complexity hybrid precoding framework for multiuser multiple-input multiple-output (MIMO) systems by leveraging a low-dimensional subspace property. Under the low-dimensional subspace perspective, we first identify an unconstrained optimal radio-frequency (RF) precoder. We then optimize a hybrid precoder via a reduced-complexity precoding method. We further extend the proposed framework to (i) a dynamic-subarray antenna partitioning algorithm that adaptively allocates subsets of antennas associated with RF chains, and (ii) a channel covariance-based approach to exploit statistical channel state information at a transmitter (CSIT), ensuring robustness with partial CSIT. Simulations validate that our proposed algorithms achieve superior performance while significantly reducing complexity compared to existing methods. |
| title | Hybrid Precoding Revisited: Low-Dimensional Subspace Perspective for MU-MIMO Systems |
| topic | Signal Processing |
| url | https://arxiv.org/abs/2508.16218 |