Splitting Messages in the Dark-Rate-Splitting Multiple Access for FDD Massive MIMO Without CSI Feedback

Abstract

In this work, we propose a novel rate-splitting multiple access (RSMA) scheme for frequency-division duplex (FDD) massive MIMO systems that operates without requiring explicit channel state information (CSI) feedback. The proposed approach addresses the fundamental challenge of CSI acquisition in FDD massive MIMO by developing sophisticated error covariance estimation techniques and generalized power iteration methods.

Key Contributions

• No CSI Feedback Required: The proposed scheme eliminates the need for explicit CSI feedback in FDD massive MIMO systems
• Error Covariance Estimation: Novel techniques for estimating error covariance matrices without direct channel knowledge
• Generalized Power Iteration: Advanced power iteration methods for precoding design
• Rate-Splitting Optimization: Efficient RSMA implementation for improved spectral efficiency

Keywords

Massive MIMO, Channel estimation, Rate-splitting multiple access, Error covariance estimation, FDD systems, Deep learning applications, Antenna arrays

Impact

This work contributes to the advancement of massive MIMO systems by providing practical solutions for CSI acquisition challenges in FDD scenarios, with potential applications in 5G and beyond wireless communication systems.