Machine learning-enabled dimensioning of slicing-based private mobile communication networks:
Gespeichert in:
1. Verfasser: | |
---|---|
Format: | Abschlussarbeit Buch |
Sprache: | English |
Veröffentlicht: |
Düren
Shaker Verlag
2024
|
Ausgabe: | 1. Auflage |
Schriftenreihe: | Dortmunder Beiträge zu Kommunikationsnetzen und -systemen
Band 23 |
Schlagworte: | |
Online-Zugang: | Inhaltsverzeichnis |
Beschreibung: | xvii, 144 Seiten Illustrationen, Diagramme, Karten 21 cm x 14.8 cm, 243 g |
ISBN: | 9783844095487 3844095489 |
Internformat
MARC
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100 | 1 | |a Bektas, Caner |d 1991- |e Verfasser |0 (DE-588)1335962115 |4 aut | |
245 | 1 | 0 | |a Machine learning-enabled dimensioning of slicing-based private mobile communication networks |c Caner Bektas |
264 | 1 | |a Düren |b Shaker Verlag |c 2024 | |
300 | |a xvii, 144 Seiten |b Illustrationen, Diagramme, Karten |c 21 cm x 14.8 cm, 243 g | ||
336 | |b txt |2 rdacontent | ||
337 | |b n |2 rdamedia | ||
338 | |b nc |2 rdacarrier | ||
490 | 1 | |a Dortmunder Beiträge zu Kommunikationsnetzen und -systemen |v Band 23 | |
502 | |b Dissertation |c Technische Universität Dortmund |d 2024 | ||
650 | 0 | 7 | |a 5G |0 (DE-588)1188755676 |2 gnd |9 rswk-swf |
650 | 0 | 7 | |a Corporate Network |0 (DE-588)4402944-5 |2 gnd |9 rswk-swf |
653 | |a 5G Network Slicing | ||
653 | |a Private 5G Networks | ||
653 | |a Automated Network Planning | ||
655 | 7 | |0 (DE-588)4113937-9 |a Hochschulschrift |2 gnd-content | |
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Datensatz im Suchindex
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adam_text |
CONTENTS
ACKNOWLEDGMENT
III
ABSTRACT
V
KURZFASSUNG
VII
LIST
OF
ABBREVIATIONS
XIII
1
INTRODUCTION
1
1.1
MOTIVATION
FOR
NETWORK
SLICING-BASED
(PRIVATE)
5G
AND
BEYOND
COMMUNICATION
NETWORKS
.
1
1.2
OVERVIEW
OF
RESEARCH
TOPICS,
METHODOLOGIES
AND
STRUCTURE
.
7
2
RELATED
WORK
REGARDING
PRIVATE
5G
NETWORKS,
5G
NETWORK
SLICING,
AND
AUTOMATED
NETWORK
PLANNING
11
2.1
RECENT
DEVELOPMENTS
CONCERNING
PRIVATE
5G
NETWORKS
.
11
2.1.1
GENERAL
OVERVIEWS
AND
SURVEYS
.
12
2.1.2
EMPIRICAL
RESULTS
AND
ANALYSES
.
12
2.1.3
SUMMARY
.
14
2.2
RELATED
WORK
IN
NETWORK
SLICING
FOR
THE
RADIO
ACCESS
NETWORK
.
15
2.2.1
RAN
SLICING
WITHOUT
MACHINE
LEARNING
.
16
2.2.2
MACHINE
LEARNING-BASED
RAN
SLICING
.
17
2.2.3
SUMMARY
.
19
2.3
RELATED
WORK
IN
AUTOMATED
NETWORK
PLANNING
.
22
2.3.1
TRADITIONAL
AUTOMATED
NETWORK
PLANNING
.
22
2.3.2
AUTOMATED
NETWORK
PLANNING
BASED
ON
MACHINE
LEARNING
23
2.3.3
SUMMARY
.
24
3
DEVELOPMENT
AND
EVALUATION
OF
DYNAMIC
RADIO
NETWORK
SLICING
BASED
ON
EXPERIMENTAL
AND
SIMULATIVE
APPROACHES
27
3.1
FIRST
EVALUATION
OF
NETWORK
SLICING
USING
4G
CONCEPTS
.
27
3.1.1
ARCHITECTURE
OF
THE
DEVELOPED
4G-BASED
END-TO-END
NET
WORK
SLICING
SYSTEM
.
28
3.1.2
TESTING
ENVIRONMENT
AND
EVALUATION
SCENARIO
OF
THE
DE
VELOPED
4G-BASED
END-TO-END
NETWORK
SLICING
SYSTEM
.
.
31
3.1.3
EVALUATION
RESULTS
OF
THE
DEVELOPED
4G-BASED
END-TO-END
NETWORK
SLICING
SYSTEM
.
34
CONTENTS
3.1.4
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
37
3.2
DEVELOPMENT
AND
EVALUATION
OF
A
FIRST
SDR-BASED
RADIO
ACCESS
NETWORK
SLICING
SCHEDULER
.
38
3.2.1
DESIGN
AND
DEVELOPMENT
OF
THE
SDR-BASED
RAN
SLICING
SCHEDULER
.
38
3.2.2
LABORATORY
SETUP
BASED
ON
SDR
AND
SDN
.
40
3.2.3
EMPIRICAL
EVALUATION
OF
THE
DEVELOPED
RAN
SLICING
SCHEDULER
41
3.2.4
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
47
3.3
DESIGN
AND
SIMULATIVE
EVALUATION
OF
A
MACHINE
LEARNING-BASED
SCHEDULER
FOR
RELIABLE
5G
NETWORK
SLICING
.
48
3.3.1
MOTIVATION
FOR
DEVELOPING
A
5G
NETWORK
SLICING
SCHEDULER
BASED
ON
MACHINE
LEARNING
.
48
3.3.2
DESIGN
OF
THE
DEVELOPED
5G
RESOURCE
GRID
SIMULATION
(5G-RGS)
FOR
SCHEDULER
PROTOTYPING
.
52
3.3.3
TECHNICAL
DESIGN
AND
IMPLEMENTATION
OF
THE
SLICE-AWARE
MACHINE
LEARNING-BASED
ULTRA-RELIABLE
SCHEDULING
(SAMUS)
PROTOTYPE
.
54
3.3.4
EVALUATION
OF
THE
SAMUS
PROTOTYPE
BASED
ON
REALISTIC
SCENARIOS
AND
DATASETS
.
56
3.3.5
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
65
4
DEVELOPMENT
AND
EVALUATION
OF
AUTOMATED
NETWORK
PLANNING
FOR
NETWORK
SLICING-BASED
COMMUNICATION
NETWORKS
67
4.1
BENEFITS
OF
DEMAND-BASED
PLANNING
AND
CONFIGURATION
OF
PRIVATE
5
G
NETWORKS
.
68
4.1.1
MOTIVATION
AND
BASIC
ARCHITECTURE
OF
AUTOMATIC
DEMAND
BASED
NETWORK
PLANNING
AND
CONFIGURATION
.
68
4.1.2
DESCRIPTION
OF
THE
DEVELOPED
EXPERIMENT
SHOWCASE
VIDEO
69
4.1.3
THEORETICAL
UNDERPINNINGS
AND
OUTCOMES
OF
THE
SIMULATIVE
VALIDATION
.
75
4.1.4
VISION
FOR
COMBINED
PRIVATE
5G
NETWORK
AND
EVENT
OPERATION
79
4.1.5
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
81
4.2
RAPID
AND
AUTOMATED
NETWORK
PLANNING
OF
PRIVATE
5G
NETWORKS
BASED
ON
UNSUPERVISED
MACHINE
LEARNING
.
82
4.2.1
DESCRIPTION
OF
THE
DEVELOPED
METHOD
FOR
RAPID
AUTOMATED
NETWORK
PLANNING
.
82
4.2.2
DETAILED
DESCRIPTION
OF
CLUSTERING
ANALYSIS
FOR
AUTOMATED
NETWORK
PLANNING
.
89
4.2.3
IMPORTANCE
OF
CLUSTERING
OR
UNSUPERVISED
LEARNING
FOR
AUTOMATED
NETWORK
PLANNING
.
92
4.2.4
EVALUATION
OF
THE
AUTOMATED
NETWORK
PLANNING
METHOD
.
94
4.2.5
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
101
CONTENTS
4.3
AUTOMATED
COVERAGE
AND
CAPACITY
PLANNING
FOR
NETWORK
SLICING
BASED
PRIVATE
5G
NETWORKS
.
102
4.3.1
WHY
NOVEL
CONCEPTS
IN
CAPACITY
PLANNING
ARE
NEEDED
FOR
FUTURE
MOBILE
COMMUNICATION
NETWORKS
.
103
4.3.2
DATA
PREDICTABILITY
IN
THE
CONTEXT
OF
CAPACITY
PLANNING
.
105
4.3.3
OVERALL
ARCHITECTURE
OF
THE
DEVELOPED
COVERAGE
AND
CA
PACITY
PLANNING
FRAMEWORK
.
107
4.3.4
EVALUATION
OF
THE
IMPACT
OF
DATA
UNCERTAINTY
IN
ML-BASED
NETWORK
SLICING
ON
NETWORK
PLANNING
.
112
4.3.5
SUMMARY,
CONCLUSION,
AND
NEXT
STEPS
.
117
4.4
PERFORMANCE
COMPARISON
OF
THE
DEVELOPED
NETWORK
PLANNING
METHOD
WITH
THE
OPTIMAL
SOLUTION
(EXHAUSTIVE
SEARCH)
.
118
4.4.1
SUMMARY
AND
CONCLUSION
.
122
5
CONCLUSION
AND
FUTURE
WORK
125
5.1
CLOSING
SUMMARY
.
125
5.2
DERIVED
POTENTIALS
AND
FUTURE
WORK
.
128
BIBLIOGRAPHY
131
SCIENTIFIC
ACTIVITY
REPORT
141 |
any_adam_object | 1 |
author | Bektas, Caner 1991- |
author_GND | (DE-588)1335962115 |
author_facet | Bektas, Caner 1991- |
author_role | aut |
author_sort | Bektas, Caner 1991- |
author_variant | c b cb |
building | Verbundindex |
bvnumber | BV049804276 |
classification_rvk | ZN 6560 |
ctrlnum | (OCoLC)1466924170 (DE-599)DNB1331203503 |
discipline | Elektrotechnik / Elektronik / Nachrichtentechnik |
edition | 1. Auflage |
format | Thesis Book |
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genre_facet | Hochschulschrift |
id | DE-604.BV049804276 |
illustrated | Illustrated |
indexdate | 2024-12-06T13:07:17Z |
institution | BVB |
institution_GND | (DE-588)1064118135 |
isbn | 9783844095487 3844095489 |
language | English |
oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-035144823 |
oclc_num | 1466924170 |
open_access_boolean | |
owner | DE-83 |
owner_facet | DE-83 |
physical | xvii, 144 Seiten Illustrationen, Diagramme, Karten 21 cm x 14.8 cm, 243 g |
publishDate | 2024 |
publishDateSearch | 2024 |
publishDateSort | 2024 |
publisher | Shaker Verlag |
record_format | marc |
series | Dortmunder Beiträge zu Kommunikationsnetzen und -systemen |
series2 | Dortmunder Beiträge zu Kommunikationsnetzen und -systemen |
spelling | Bektas, Caner 1991- Verfasser (DE-588)1335962115 aut Machine learning-enabled dimensioning of slicing-based private mobile communication networks Caner Bektas Düren Shaker Verlag 2024 xvii, 144 Seiten Illustrationen, Diagramme, Karten 21 cm x 14.8 cm, 243 g txt rdacontent n rdamedia nc rdacarrier Dortmunder Beiträge zu Kommunikationsnetzen und -systemen Band 23 Dissertation Technische Universität Dortmund 2024 5G (DE-588)1188755676 gnd rswk-swf Corporate Network (DE-588)4402944-5 gnd rswk-swf 5G Network Slicing Private 5G Networks Automated Network Planning (DE-588)4113937-9 Hochschulschrift gnd-content 5G (DE-588)1188755676 s Corporate Network (DE-588)4402944-5 s DE-604 Dortmunder Beiträge zu Kommunikationsnetzen und -systemen Band 23 (DE-604)BV041418989 23 DNB Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035144823&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p vlb 20240530 DE-101 https://d-nb.info/provenance/plan#vlb |
spellingShingle | Bektas, Caner 1991- Machine learning-enabled dimensioning of slicing-based private mobile communication networks Dortmunder Beiträge zu Kommunikationsnetzen und -systemen 5G (DE-588)1188755676 gnd Corporate Network (DE-588)4402944-5 gnd |
subject_GND | (DE-588)1188755676 (DE-588)4402944-5 (DE-588)4113937-9 |
title | Machine learning-enabled dimensioning of slicing-based private mobile communication networks |
title_auth | Machine learning-enabled dimensioning of slicing-based private mobile communication networks |
title_exact_search | Machine learning-enabled dimensioning of slicing-based private mobile communication networks |
title_full | Machine learning-enabled dimensioning of slicing-based private mobile communication networks Caner Bektas |
title_fullStr | Machine learning-enabled dimensioning of slicing-based private mobile communication networks Caner Bektas |
title_full_unstemmed | Machine learning-enabled dimensioning of slicing-based private mobile communication networks Caner Bektas |
title_short | Machine learning-enabled dimensioning of slicing-based private mobile communication networks |
title_sort | machine learning enabled dimensioning of slicing based private mobile communication networks |
topic | 5G (DE-588)1188755676 gnd Corporate Network (DE-588)4402944-5 gnd |
topic_facet | 5G Corporate Network Hochschulschrift |
url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=035144823&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
volume_link | (DE-604)BV041418989 |
work_keys_str_mv | AT bektascaner machinelearningenableddimensioningofslicingbasedprivatemobilecommunicationnetworks |