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RETRACTED ARTICLE: Design of precoder for a MIMO–NOMA system using Gaussian mixture modelling
Multi-Input Multi-Output system (MIMO) is a wireless technology that employs transmitters and receivers for simultaneously transferring more amount of data. And Non-Orthogonal Multiple Access (NOMA) is a new technology that accommodates multiple users in the same spectrum to ensure efficient spectra...
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Published in: | Optical and quantum electronics 2024, Vol.56 (1), Article 60 |
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Main Authors: | , , , , , |
Format: | Article |
Language: | English |
Subjects: | |
Citations: | Items that this one cites |
Online Access: | Get full text |
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Summary: | Multi-Input Multi-Output system (MIMO) is a wireless technology that employs transmitters and receivers for simultaneously transferring more amount of data. And Non-Orthogonal Multiple Access (NOMA) is a new technology that accommodates multiple users in the same spectrum to ensure efficient spectral usage. A combination of MIMO-NOMO systems meets the data demands of more users, while ensuring spectral efficiencies. This paper presents a new precoding algorithm using the Gaussian Mixture Modelling (GMM), which is a type of Machine Learning (ML) algorithm used for Clustering, for the MIMO–NOMA systems. Clustering refers to the grouping of data points into clusters. The use of optimal precoding methods would help eliminate inter–cluster interferences. The suggested precoding approach supports multi-layer transmission in multi-antenna wireless communications, incorporating the idea of GMM in a Multiple antenna system at both the transmitting and receiving ends along with a special case of its multiple access methodology being non-Orthogonal. Hence, the resultant MIMO–NOMA system would result in better spectral efficiency and energy efficiency. The simulation results prove this. |
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ISSN: | 0306-8919 1572-817X |
DOI: | 10.1007/s11082-023-05655-2 |