Computationally Efficient Tensor-Based MIMO Precoder

In this paper, a novel Tensor-based MIMO precoder algorithm that significantly reduces computational complexity compared to the classical SVD precoder is proposing. This approach is based on the well-known tensor decomposition (Tucker decomposition), which allows to represent and process of multidimensional data arrays efficiently. The approach significantly reduces the dimensionality of the problem leading to a substantial decrease in computational costs. Numerical experiments demonstrate that the proposed Tensor-based MIMO precoder provides comparable performance to the SVD precoder while significantly reducing computational complexity.

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Publication Details

Published
2024-09-30
DOI
https://doi.org/10.1109/sibircon63777.2024.10758516
Primary Topic
Advanced MIMO Systems Optimization
Type
article
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article

Computationally Efficient Tensor-Based MIMO Precoder

И. М. Колесников, Vladimir Lyashev
Advanced MIMO Systems Optimization
article

Computationally Efficient Tensor-Based MIMO Precoder

И. М. Колесников, Vladimir Lyashev
article en

Abstract

In this paper, a novel Tensor-based MIMO precoder algorithm that significantly reduces computational complexity compared to the classical SVD precoder is proposing. This approach is based on the well-known tensor decomposition (Tucker decomposition), which allows to represent and process of multidimensional data arrays efficiently. The approach significantly reduces the dimensionality of the problem leading to a substantial decrease in computational costs. Numerical experiments demonstrate that the proposed Tensor-based MIMO precoder provides comparable performance to the SVD precoder while significantly reducing computational complexity.

Moscow Institute of Physics and Technology (RU)
Affordable and clean energy
Openalex Percentile: Top 81%
Advanced MIMO Systems Optimization
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