Please use this identifier to cite or link to this item: https://hdl.handle.net/10356/158133
Title: Development of deep leaning algorithm for multiple-input multiple-output communication system
Authors: Chen, Xingchen
Keywords: Engineering::Electrical and electronic engineering
Issue Date: 2022
Publisher: Nanyang Technological University
Source: Chen, X. (2022). Development of deep leaning algorithm for multiple-input multiple-output communication system. Final Year Project (FYP), Nanyang Technological University, Singapore. https://hdl.handle.net/10356/158133
Abstract: Multiple Input Multiple Output (MIMO) is the key technology of the fifth-generation (5G) communication technology. In order to meet the increasing communication needs of users, MIMO technology is also developing rapidly. MIMO signal detection plays a very important role in ensuring the accuracy of MIMO signal transmission. In order to further improve the signal detection accuracy and efficiency of MIMO system, people try to design MIMO system detector by using machine learning. This project will evaluate the performance of several conventional MIMO detection algorithms commonly used and several algorithms combined with machine learning. In this project, we will first introduce several commonly used detection algorithms, and theoretically analyze the advantages and problems of these methods. Then we make a comprehensive evaluation of each method through simulation experiment. Through our comprehensive analysis, the detection algorithm combining machine learning and iterative algorithm can effectively improve the efficiency and accuracy of signal detection.
URI: https://hdl.handle.net/10356/158133
Fulltext Permission: restricted
Fulltext Availability: With Fulltext
Appears in Collections:EEE Student Reports (FYP/IA/PA/PI)

Files in This Item:
File Description SizeFormat 
Final_report - Chen Xingchen.pdf
  Restricted Access
874.42 kBAdobe PDFView/Open

Page view(s)

10
Updated on Jun 25, 2022

Download(s)

1
Updated on Jun 25, 2022

Google ScholarTM

Check

Items in DR-NTU are protected by copyright, with all rights reserved, unless otherwise indicated.