Combined Deep Learning and SOR Detection Technique for High Reliability in Massive MIMO Systems

Jang, Junyong; Park, Chan-Yeob; Shin, Beom-Sik; Song, Hyoung‐Kyu

doi:10.1109/access.2021.3125002

Cited by 7 publications

(2 citation statements)

References 29 publications

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“…In (Jang et al, 2021;Pereira de Figueiredo, 2022), machine learning is pointed out as an important enabling technology for applications such as MIMO, massive MIMO and beamspace MIMO in the millimeter wave. It is notable that machine learning is gathering special attention from the academic community thanks to its potential to replace statistical driven solvers by generalist and adaptive learning-based techniques.…”

Section: Introductionmentioning

confidence: 99%

A review on principles, performance and complexity of linear estimation and detection techniques for MIMO systems

Gaspar¹,

Mendes

Pimenta

2023

Front. Comms. Net.

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The advent of the fifth generation (5G) of mobile networks has introduced several new use cases that are pushing mobile networks in environments that are typically supported by wired technologies. The initial discussions around the sixth generation (6G) of mobile networks signalizes that different approaches are needed to address all contrasting requirements, where multiple-input multiple-output (MIMO) technique stands as a key technology for most future wireless systems. In this review, we present an introduction on classical linear estimators and coherent detectors along with an innovative and accurate complexity formulation within a common framework, allowing a fair comparison and providing an initial guideline for researchers that are looking for a general view of the main techniques available for spatial multiplexing (SM)-MIMO detection and estimation.

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Section: Introductionmentioning

confidence: 99%

A review on principles, performance and complexity of linear estimation and detection techniques for MIMO systems

Gaspar¹,

Mendes

Pimenta

2023

Front. Comms. Net.

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“…ML methods can learn from data and make predictions for future events. Recently, ML-based approaches have been widely adopted in wireless communication technologies [ 16 , 17 , 18 , 19 ]. IRS-based communication has also adapted different ML techniques for performance enhancement.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review

Sejan

Rahman

Shin

et al. 2022

Sensors

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An intelligent reflecting surface (IRS) is a programmable device that can be used to control electromagnetic waves propagation by changing the electric and magnetic properties of its surface. Therefore, IRS is considered a smart technology for the sixth generation (6G) of communication networks. In addition, machine learning (ML) techniques are now widely adopted in wireless communication as the computation power of devices has increased. As it is an emerging topic, we provide a comprehensive overview of the state-of-the-art on ML, especially on deep learning (DL)-based IRS-enhanced communication. We focus on their operating principles, channel estimation (CE), and the applications of machine learning to IRS-enhanced wireless networks. In addition, we systematically survey existing designs for IRS-enhanced wireless networks. Furthermore, we identify major issues and research opportunities associated with the integration of IRS and other emerging technologies for applications to next-generation wireless communication.

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Variational autoencoder-enhanced deep neural network-based detection for MIMO systems

Omondi,

Olwal

2023

e-Prime - Advances in Electrical Engineering, Electronics and E

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Combined Deep Learning and SOR Detection Technique for High Reliability in Massive MIMO Systems

Cited by 7 publications

References 29 publications

A review on principles, performance and complexity of linear estimation and detection techniques for MIMO systems

A review on principles, performance and complexity of linear estimation and detection techniques for MIMO systems

Machine Learning for Intelligent-Reflecting-Surface-Based Wireless Communication towards 6G: A Review

Variational autoencoder-enhanced deep neural network-based detection for MIMO systems

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