Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems

Over the past decade, with the massive spike in the use of data-hungry applications such as streaming Netflix in 4k, playing graphic-intensive PC games, and online learning, there is a need for a faster data transmission rate. In this project, we aim to apply deep learning techniques to current data...

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Main Author:	Xu, Chuang
Other Authors:	Teh Kah Chan
Format:	Thesis-Master by Coursework
Language:	English
Published:	Nanyang Technological University 2024
Subjects:	Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
Online Access:	https://hdl.handle.net/10356/172966
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Institution:	Nanyang Technological University
Language:	English

id	sg-ntu-dr.10356-172966
record_format	dspace
spelling	sg-ntu-dr.10356-1729662024-01-12T15:45:18Z Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems Xu, Chuang Teh Kah Chan School of Electrical and Electronic Engineering EKCTeh@ntu.edu.sg Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio Over the past decade, with the massive spike in the use of data-hungry applications such as streaming Netflix in 4k, playing graphic-intensive PC games, and online learning, there is a need for a faster data transmission rate. In this project, we aim to apply deep learning techniques to current data transmission methods such as orthogonal frequency-division multiple access (OFDMA) and upcoming non-orthogonal multiple access (NOMA) method to improve the capacity of a channel. The student will explore the advantage of deep-learning techniques to improve the system capacity and compare with existing conventional methods. Matlab or Python programming will be used to study the performance of the proposed scheme. Master of Science (Communications Engineering) 2024-01-08T06:18:17Z 2024-01-08T06:18:17Z 2023 Thesis-Master by Coursework Xu, C. (2023). Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/172966 https://hdl.handle.net/10356/172966 en application/pdf Nanyang Technological University
institution	Nanyang Technological University
building	NTU Library
continent	Asia
country	Singapore Singapore
content_provider	NTU Library
collection	DR-NTU
language	English
topic	Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
spellingShingle	Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio Xu, Chuang Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
description	Over the past decade, with the massive spike in the use of data-hungry applications such as streaming Netflix in 4k, playing graphic-intensive PC games, and online learning, there is a need for a faster data transmission rate. In this project, we aim to apply deep learning techniques to current data transmission methods such as orthogonal frequency-division multiple access (OFDMA) and upcoming non-orthogonal multiple access (NOMA) method to improve the capacity of a channel. The student will explore the advantage of deep-learning techniques to improve the system capacity and compare with existing conventional methods. Matlab or Python programming will be used to study the performance of the proposed scheme.
author2	Teh Kah Chan
author_facet	Teh Kah Chan Xu, Chuang
format	Thesis-Master by Coursework
author	Xu, Chuang
author_sort	Xu, Chuang
title	Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
title_short	Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
title_full	Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
title_fullStr	Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
title_full_unstemmed	Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
title_sort	deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
publisher	Nanyang Technological University
publishDate	2024
url	https://hdl.handle.net/10356/172966
_version_	1789482995306987520

Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems

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