GSVD Based Precoding Scheme for Nonlinear Massive MIMO-RSMA Networks

In this paper, we consider the precoder design for multiuser multiple input multiple output (MU-MIMO) systems based on orthogonal frequency domain multiplexing (OFDM) with rate splitting at the transmitter. We propose precoding and decoding schemes based on generalized singular value decomposition (GSVD), both for underloaded and overloaded communication systems that support the transmission of multiple common and private streams. To address performance degradation caused by nonlinearities from GSVD-RSMA, an iterative distortion canellation receiver-aided precoding method is introduced. The approach improves stream detection without requiring successive interference cancellation, enhancing robustness in nonlinear environments<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1.</sup>

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Published
2025-06-17
DOI
https://doi.org/10.1109/vtc2025-spring65109.2025.11174910
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

GSVD Based Precoding Scheme for Nonlinear Massive MIMO-RSMA Networks

Rui Dinis, Oussama Belkacem
Advanced MIMO Systems Optimization
article

GSVD Based Precoding Scheme for Nonlinear Massive MIMO-RSMA Networks

Rui Dinis, Oussama Belkacem
article en

Abstract

In this paper, we consider the precoder design for multiuser multiple input multiple output (MU-MIMO) systems based on orthogonal frequency domain multiplexing (OFDM) with rate splitting at the transmitter. We propose precoding and decoding schemes based on generalized singular value decomposition (GSVD), both for underloaded and overloaded communication systems that support the transmission of multiple common and private streams. To address performance degradation caused by nonlinearities from GSVD-RSMA, an iterative distortion canellation receiver-aided precoding method is introduced. The approach improves stream detection without requiring successive interference cancellation, enhancing robustness in nonlinear environments<sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">1.</sup>

University of Carthage (TN), Instituto de Telecomunicações (PT)
Openalex Percentile: Top 73%
Advanced MIMO Systems Optimization
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