Application of the Sionna Software for 5G/6G Physical Layer Simulations

The rapid advancement of wireless communication technologies demands sophisticated simulation software capable of accurately modeling and analyzing the physical layer of 5G (Fifth Generation). Advanced applications of the Sionna software provide a comprehensive platform for simulating complex link dynamics and performance metrics. This research focuses on the simulation analyses of 5G NR (New Radio) LDPC (Low-Density Parity-Check) codes and Multi-User MIMO (Multiple Input Multiple Output) OFDM (Orthogonal Frequency Division Multiplexing) techniques, demonstrating significant improvements in system performance and channel efficiency. The integration of ML (Machine Learning) methods is essential for advancing signal processing and decoding efficiency, particularly in next-generation networks. Simulated advanced neural demapping techniques highlight the need for innovative approaches to address the challenges posed by emerging technologies, including anticipated advancements in 6G (Sixth Generation).

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Publication Details

Published
2024-11-26
DOI
https://doi.org/10.1109/telfor63250.2024.10819060
Citations
1
Primary Topic
Millimeter-Wave Propagation and Modeling
Type
article
Field-Weighted Citation Impact
0.21
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article

Application of the Sionna Software for 5G/6G Physical Layer Simulations

Marija Malnar, Nenad Jevtić, Milica Đorđević
1 citations
Millimeter-Wave Propagation and Modeling
0.21
article

Application of the Sionna Software for 5G/6G Physical Layer Simulations

Marija Malnar, Nenad Jevtić, Milica Đorđević
article en
1 citations

Abstract

The rapid advancement of wireless communication technologies demands sophisticated simulation software capable of accurately modeling and analyzing the physical layer of 5G (Fifth Generation). Advanced applications of the Sionna software provide a comprehensive platform for simulating complex link dynamics and performance metrics. This research focuses on the simulation analyses of 5G NR (New Radio) LDPC (Low-Density Parity-Check) codes and Multi-User MIMO (Multiple Input Multiple Output) OFDM (Orthogonal Frequency Division Multiplexing) techniques, demonstrating significant improvements in system performance and channel efficiency. The integration of ML (Machine Learning) methods is essential for advancing signal processing and decoding efficiency, particularly in next-generation networks. Simulated advanced neural demapping techniques highlight the need for innovative approaches to address the challenges posed by emerging technologies, including anticipated advancements in 6G (Sixth Generation).

Rohde & Schwarz (Germany) (DE), University of Belgrade (RS)
Openalex Percentile: Top 44%
Millimeter-Wave Propagation and Modeling
0.21
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Application of the Sionna Software for 5G/6G Physical Layer Simulations — Marija Malnar, Nenad Jevtić, et al. · (2024) | TGRS Research Map | TGRS