• Deep learning-based algorithms...

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

Title:
Deep learning-based algorithms for high capacity transmission of orthogonal multiple access and non-orthogonal multiple access systems
Authors:
Xu, Chuang
Contributors:
Teh Kah Chan, School of Electrical and Electronic Engineering, EKCTeh@ntu.edu.sg
Publisher Information:
Nanyang Technological University
Publication Year:
2023
Collection:
DR-NTU (Digital Repository at Nanyang Technological University, Singapore)
Subject Terms:
Engineering::Electrical and electronic engineering::Antennas, wave guides, microwaves, radar, radio
Document Type:
other/unknown material
File Description:
application/pdf
Language:
English
Relation:
https://hdl.handle.net/10356/172966
Availability:
https://hdl.handle.net/10356/172966
Accession Number:
edsbas.789FCF22
Database:
BASE

Weitere Informationen

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)