5G NR downlink AOD-based localization

Large antenna arrays, millimeter-wave signals, large bandwidth and dense deployment are the characteristics of 5G networks. These technologies not only enable high-data rate communications but also have the potential superiority of accurate positioning. This dissertation aims to study the millimeter...

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Main Author: Liang, Wenfei
Other Authors: Tay Wee Peng
Format: Thesis-Master by Coursework
Language:English
Published: Nanyang Technological University 2022
Subjects:
Online Access:https://hdl.handle.net/10356/157291
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Institution: Nanyang Technological University
Language: English
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spelling sg-ntu-dr.10356-1572912023-07-04T17:47:39Z 5G NR downlink AOD-based localization Liang, Wenfei Tay Wee Peng School of Electrical and Electronic Engineering wptay@ntu.edu.sg Engineering::Electrical and electronic engineering Large antenna arrays, millimeter-wave signals, large bandwidth and dense deployment are the characteristics of 5G networks. These technologies not only enable high-data rate communications but also have the potential superiority of accurate positioning. This dissertation aims to study the millimeter-wave positioning properties and existing angle of departure (AoD) based localization algorithms for 5G communication networks and integrate existing methods and add new contents to realize three-dimensional non-line-of-sight (NLOS) based localization with the assumption that received NLOS path signals only reflect once. To achieve the objective, the SAGE algorithm is applied to estimate channel parameters due to its faster convergence and lower complexity. The position of a mobile station (MS) is recovered using the estimated channel parameters through the geometrical relationship between base station (BS) and MS in three-dimensional scenario. The method can achieve sub-meter localization error with probability of 0.9 in NLOS scenario. Master of Science (Communications Engineering) 2022-05-12T00:24:35Z 2022-05-12T00:24:35Z 2022 Thesis-Master by Coursework Liang, W. (2022). 5G NR downlink AOD-based localization. Master's thesis, Nanyang Technological University, Singapore. https://hdl.handle.net/10356/157291 https://hdl.handle.net/10356/157291 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
spellingShingle Engineering::Electrical and electronic engineering
Liang, Wenfei
5G NR downlink AOD-based localization
description Large antenna arrays, millimeter-wave signals, large bandwidth and dense deployment are the characteristics of 5G networks. These technologies not only enable high-data rate communications but also have the potential superiority of accurate positioning. This dissertation aims to study the millimeter-wave positioning properties and existing angle of departure (AoD) based localization algorithms for 5G communication networks and integrate existing methods and add new contents to realize three-dimensional non-line-of-sight (NLOS) based localization with the assumption that received NLOS path signals only reflect once. To achieve the objective, the SAGE algorithm is applied to estimate channel parameters due to its faster convergence and lower complexity. The position of a mobile station (MS) is recovered using the estimated channel parameters through the geometrical relationship between base station (BS) and MS in three-dimensional scenario. The method can achieve sub-meter localization error with probability of 0.9 in NLOS scenario.
author2 Tay Wee Peng
author_facet Tay Wee Peng
Liang, Wenfei
format Thesis-Master by Coursework
author Liang, Wenfei
author_sort Liang, Wenfei
title 5G NR downlink AOD-based localization
title_short 5G NR downlink AOD-based localization
title_full 5G NR downlink AOD-based localization
title_fullStr 5G NR downlink AOD-based localization
title_full_unstemmed 5G NR downlink AOD-based localization
title_sort 5g nr downlink aod-based localization
publisher Nanyang Technological University
publishDate 2022
url https://hdl.handle.net/10356/157291
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