Hybrid Precoding Revisited: Low-Dimensional Subspace Perspective for MU-MIMO Systems
Abstract
This paper 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 digital 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.
Fields of Study & Subjects
Advanced MIMO Systems Optimization
Advanced Wireless Communication Techniques
Millimeter-Wave Propagation and Modeling
Publication details
- Journal / source
- IEEE Transactions on Vehicular Technology
- Publisher
- Institute of Electrical and Electronics Engineers (IEEE)
- Volume
- 75
- Issue
- 10
- Pages
- 1–6
- Publication date
- 1 January 2026
- Language
- EN