A Dimension-Reduced Second-Order Method for One-Bit Precoding over MU-MISO Channels

This paper addresses the one-bit multi-user precoding problem, which involves sending multiple data streams to multiple single-antenna users using one-bit digital-to-analog converters (DACs) at the Base Station (BS). This problem is of great interest due to its potential to achieve high spectral efficiency with low-cost hardware and low power consumption, particularly in massive multi-input multi-output (MIMO) systems. To solve this problem, a unified (first-order) method, called GEMM was introduced by Shao et al. in [1]. In this work, we revisit the one-bit precoding problem in [1] and develop a more computationally efficient algorithm than GEMM by leveraging on a dimension reduced second-order method to iteratively update the solution. Each update can be easily done by solving a trust-region subproblem with only two variables, which admits a closed-form solution. Therefore, the proposed algorithm possesses similar fast convergence speed as the standard second-order method and meanwhile avoids its high iteration complexity. Numerical results demonstrate that the proposed method can reduce the runtime of GEMM by up to 62% without sacrificing the bit error rate performance.

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Publication Details

Published
2025-08-10
DOI
https://doi.org/10.1109/iccc65529.2025.11149012
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

A Dimension-Reduced Second-Order Method for One-Bit Precoding over MU-MISO Channels

Hongli Liu, Ying Zhang, Qiang Li, Zixuan Jiang
Advanced MIMO Systems Optimization
article

A Dimension-Reduced Second-Order Method for One-Bit Precoding over MU-MISO Channels

Hongli Liu, Ying Zhang, Qiang Li, Zixuan Jiang
article en

Abstract

This paper addresses the one-bit multi-user precoding problem, which involves sending multiple data streams to multiple single-antenna users using one-bit digital-to-analog converters (DACs) at the Base Station (BS). This problem is of great interest due to its potential to achieve high spectral efficiency with low-cost hardware and low power consumption, particularly in massive multi-input multi-output (MIMO) systems. To solve this problem, a unified (first-order) method, called GEMM was introduced by Shao et al. in [1]. In this work, we revisit the one-bit precoding problem in [1] and develop a more computationally efficient algorithm than GEMM by leveraging on a dimension reduced second-order method to iteratively update the solution. Each update can be easily done by solving a trust-region subproblem with only two variables, which admits a closed-form solution. Therefore, the proposed algorithm possesses similar fast convergence speed as the standard second-order method and meanwhile avoids its high iteration complexity. Numerical results demonstrate that the proposed method can reduce the runtime of GEMM by up to 62% without sacrificing the bit error rate performance.

University of Electronic Science and Technology of China (CN), Hong Kong University of Science and Technology (HK)
Openalex Percentile: Top 77%
Advanced MIMO Systems Optimization
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