Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Develop A Predictive Model & Analyze The Impact On Common Memory Usage In A 5G Radio Unit
Blekinge Institute of Technology, Faculty of Computing, Department of Computer Science.
2024 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Place, publisher, year, edition, pages
2024.
Keywords [en]
Common Memory, EMCA, Machine Learning, 5G, SHAP
National Category
Computer Sciences
Identifiers
URN: urn:nbn:se:bth-26008OAI: oai:DiVA.org:bth-26008DiVA, id: diva2:1842132
External cooperation
Ericsson
Subject / course
DV2572 Master´s Thesis in Computer Science
Educational program
DVADA Master Qualification Plan in Computer Science
Supervisors
Examiners
Available from: 2024-03-12 Created: 2024-03-03 Last updated: 2024-03-12Bibliographically approved

Open Access in DiVA

fulltext(1935 kB)130 downloads
File information
File name FULLTEXT01.pdfFile size 1935 kBChecksum SHA-512
c61de9430faa6461cf4e529dd2ff411b0b6818d4879a530a5444ffe9cf6c53076f17e475b44eac03d923f6a85c81f6dfd5144f999db66cd7b29f467e17a4de7a
Type fulltextMimetype application/pdf

By organisation
Department of Computer Science
Computer Sciences

Search outside of DiVA

GoogleGoogle Scholar
Total: 130 downloads
The number of downloads is the sum of all downloads of full texts. It may include eg previous versions that are now no longer available

urn-nbn

Altmetric score

urn-nbn
Total: 537 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf