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

arXiv: https://arxiv.org/abs/2405.00979 · HTML: https://mlsanity.com/paper/2405.00979/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 2 May 2024.

## Built on by (most cited first, 1 of 1)

- [Learning MMSE Filters for OFDM Channel Estimation: Attention Transformer Gains at Linear Inference](https://mlsanity.com/paper/2506.00452/) (2025)

## Abstract (arXiv)

A critical hindrance in realizing frequency division duplex (FDD) massive multi-input multi-output (MIMO) systems is the overhead associated with the downlink (DL) channel state information at the transmitter (CSIT) acquisition. To address this, we propose a novel framework that eliminates the need for CSI feedback, while achieving robust sum spectral efficiency (SE). Specifically, by leveraging partial frequency invariance of channel parameters, we reconstruct the DL CSIT using uplink (UL) pilots with the 2D-Newtonized orthogonal matching pursuit (2D-NOMP) algorithm. Due to discrepancies between the two disjoint bands, however, perfect DL CSIT acquisition is infeasible; resulting in multi-user interference (MUI). To account for this, we reformulate the sum SE maximization problem using the reconstructed channel and its error covariance matrix (ECM). Then, we propose an ECM estimation method based on the observed Fisher information matrix and introduce a precoder optimization technique with rate-splitting multiple access (RSMA). Our simulation results verify the validity of the proposed framework in the practical FDD massive MIMO scenarios, highlighting the essential role of ECM estimation in mitigating MUI to attain RSMA gains.