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
Intelligent Beam Weight Computation for Massive Beamforming
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
Blekinge Institute of Technology, Faculty of Engineering, Department of Applied Signal Processing.
2017 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

LTE (Long Term Evolution) is likely the most complex wireless system ever developed. It incorporates features that could not have been economically implemented as recently as a decade ago. Today, with large-scale ICs, LTE can be easily accommodated in base stations and battery-powered handsets alike. LTE-Advanced is the upgraded version of LTE technology for providing more speed and greater reliability.

In this report, the wireless communication between the user and base station is implemented by creating 4G LTE environment in MATLAB. Impact of Coherence time on beam weight computation varies for different delay profiles. Moreover, SNR of the transmitted signal varies significantly by the time gap between two successive uplink frames in TDD configuration. In this report, computationally efficient algorithm for reducing beam weight computations in system level LTE simulations is proposed.

The wireless channel is modelled in both Rician and Rayleigh fading channel. Efficiency of beam forming algorithms is observed at different channel conditions like delay profile, fading channel, bandwidth, correlation, modulation technique.

The MUSIC algorithm is implemented for detecting the movement of the users in Line of sight condition

Place, publisher, year, edition, pages
2017.
National Category
Signal Processing
Identifiers
URN: urn:nbn:se:bth-15181OAI: oai:DiVA.org:bth-15181DiVA, id: diva2:1144226
External cooperation
Ericsson, Lund
Subject / course
ET2566 Master's Thesis (120 credits) in Electrical Engineering with emphasis on Signal processing
Educational program
ETASX Master of Science Programme in Electrical Engineering with emphasis on Signal Processing
Presentation
2017-06-12, J3423 Aristoteles, Blekinge Institute of Technology, Karlskrona, 14:00 (English)
Supervisors
Examiners
Available from: 2017-11-21 Created: 2017-09-25 Last updated: 2017-11-21Bibliographically approved

Open Access in DiVA

BTH2017Appilla(1209 kB)3231 downloads
File information
File name FULLTEXT02.pdfFile size 1209 kBChecksum SHA-512
e2ecb72a9755e8772bc4e7db9e7ad3ca15d190b0f7c0c32c269cc2854a83e0b4b7950b596fe835c72a3129658b72a7e4a804056a4f2bfc2cda5588d368ff58f3
Type fulltextMimetype application/pdf

By organisation
Department of Applied Signal Processing
Signal Processing

Search outside of DiVA

GoogleGoogle Scholar
Total: 3233 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: 1066 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