Finite-Alphabet Precoding for Massive MU-MIMO with Low-resolution DACs
Chang-Jen Wang, Chao-Kai Wen, Shi Jin, and Shang-Ho Tsai

TL;DR
This paper proposes novel algorithms for finite-alphabet precoding in massive MU-MIMO systems with low-resolution DACs, improving performance and reducing complexity compared to existing methods.
Contribution
It introduces two new ADMM-based algorithms, IDE and IDE2, tailored for nonlinear discrete precoding in massive MU-MIMO with finite alphabets, addressing convergence issues.
Findings
IDE achieves excellent performance in precoding quality.
IDE2 offers significantly lower computational complexity.
Proposed algorithms outperform state-of-the-art techniques in simulations.
Abstract
Massive multiuser multiple-input multiple-output (MU-MIMO) systems are expected to be the core technology in fifth-generation wireless systems because they significantly improve spectral efficiency. However, the requirement for a large number of radio frequency (RF) chains results in high hardware costs and power consumption, which obstruct the commercial deployment of massive MIMO systems. A potential solution is to use low-resolution digital-to-analog converters (DAC)/analog-to-digital converters for each antenna and RF chain. However, using low-resolution DACs at the transmit side directly limits the degree of freedom of output signals and thus poses a challenge to the precoding design. In this study, we develop efficient and universal algorithms for a downlink massive MU-MIMO system with finite-alphabet precodings. Our algorithms are developed based on the alternating direction…
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Taxonomy
TopicsAdvanced MIMO Systems Optimization · Full-Duplex Wireless Communications · Energy Harvesting in Wireless Networks
