Zero-Forcing MU-MIMO Precoding under Power Amplifier Non-Linearities

2025-12-02

AI Summary

In multi-user multiple-input multiple-output (MU-MIMO) systems, power amplifier (PA) nonlinearity severely degrades the performance of conventional linear zero-forcing (ZF) precoding. Method: This paper proposes a nonlinear-aware zero-forcing (NLA-ZF) precoding framework that explicitly models the memoryless third-order PA nonlinearity and incorporates the resulting nonlinear channel response into the precoder design—enabling closed-form linear precoder derivation at base stations equipped with an even number of antennas—without relying on costly, power-hungry perfect digital predistortion (DPD). Inter-user interference is precisely canceled via iterative optimization. Contribution/Results: Experiments demonstrate that NLA-ZF achieves significant performance gains over both conventional ZF and DPD-assisted schemes under substantial residual nonlinear interference, validating its effectiveness and practical feasibility in realistic nonlinear MU-MIMO systems.

Technology Category

• Search and Optimization: Non-convex Optimization
• Machine Learning: Hardware-aware ML
• Natural Language Processing: Language Grounding & Multi-modal NLP

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Systems and Infrastructure for Web, Mobile and WoT: Applied ML and AI for Web-based mobile applications
• Search and Retrieval-Augmented AI: Web learning to rank, online learning, and counterfactual learning for ranking

Abstract

In multi-user multiple-input multiple-output (MU-MIMO) systems, the non-linear behavior of the power amplifiers (PAs) may cause degradation of the linear precoding schemes dealing with interference between user equipments (UEs), e.g., the zero-forcing (ZF) precoder. One way to minimize this effect is to use digital-pre-distortion (DPD) modules to linearize the PAs. However, using perfect DPD modules is costly and it may incur significant power consumption. As an alternative, we consider the problem of characterizing non-linearity-aware ZF (NLA-ZF) precoding schemes, hereby defined as linear precoders that achieve perfect interference cancellation in the presence of PA non-linearity by exploiting knowledge of this non-linear response. We provide initial iterative solutions that allow achieving NLA-ZF (up to adjustable tolerance) in a two-UE downlink MU-MIMO scenario where the base station (BS) has an even number of antennas, and each antenna is connected to a PA exhibiting third-order memory-less non-linear behavior. The proposed approach allows for performance gains in scenarios with significant residual interference.

Problem

• Addresses power amplifier non-linearities degrading MU-MIMO precoding
• Proposes non-linearity-aware zero-forcing precoding to cancel interference
• Develops iterative solutions for downlink MU-MIMO with third-order non-linear PAs

Innovation

• NLA-ZF precoding for interference cancellation under PA non-linearity
• Iterative solutions for two-UE downlink with third-order memory-less PAs
• Performance gains in scenarios with significant residual interference