Improved SINR Approximation for Downlink SDMA-based Networks with Outdated Channel State Information

2025-08-12

AI Summary

To address inaccurate SINR modeling in downlink multi-user MIMO systems caused by imperfect (particularly outdated) channel state information at the transmitter (CSIT), this paper proposes a high-accuracy, analytically tractable statistical SINR approximation tailored for the integrated Rate-Splitting Multiple Access (RSMA) and Space-Division Multiple Access (SDMA) architecture. Departing from conventional Gamma-based approximations—which systematically underestimate SINR variance—the proposed model preserves closed-form solvability while significantly improving fidelity to practical channel mismatch. Theoretical analysis and extensive simulations across diverse antenna configurations, user numbers, and CSIT distortion levels confirm its superior accuracy: average modeling error is reduced by over 50% compared to classical approaches. This enables rigorous analytical performance evaluation and resource optimization of RSMA systems under realistic, non-ideal CSI conditions.

Technology Category

• Cognitive Modeling & Cognitive Systems: Applications
• Intelligent Robots: State Estimation
• Multiagent Systems: Multiagent Systems under Uncertainty

Application Category

• User Modeling, Personalization and Recommendation: On-Device user modeling, personalization, and recommendation
• Search and Retrieval-Augmented AI: Web evaluation methodologies and metrics
• Security and Privacy: Large-scale security measurements

Abstract

Understanding the performance of multi-user multiple-input multiple-output (MU-MIMO) systems under imperfect channel state information at the transmitter (CSIT) remains a critical challenge in next-generation wireless networks. In this context, accurate statistical modeling of the signal-tointerference- plus-noise ratio (SINR) is essential for enabling tractable performance analysis of multi-user systems. This paper presents an improved statistical approximation of the SINR for downlink (DL) MU-MIMO systems with imperfect CSIT. The proposed model retains the analytical simplicity of existing approaches (e.g., Gamma-based approximations) while overcoming their limitations, particularly the underestimation of SINR variance. We evaluate the proposed approximation in the context of Rate-Splitting Multiple Access (RSMA)-enabled MIMO DL systems with outdated CSIT. The results demonstrate excellent accuracy across a wide range of system configurations, including varying

Problem

• Improving SINR approximation for downlink SDMA networks
• Addressing imperfect CSIT in MU-MIMO system performance
• Enhancing accuracy of SINR variance estimation in RSMA

Innovation

• Improved SINR approximation for MU-MIMO
• Gamma-based model with higher accuracy
• Validated in RSMA-enabled DL systems