Change search
ReferencesLink to record
Permanent link

Direct link
A study on adaptive real time video over LTE
2007 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
Abstract [en]

LTE, The next generation mobile network system by 3GPP, only allows IP-based transport. Traditional telephony services such as voice and video real-time communication will be provided through the use of IMS (IP Multimedia Subsystem) Multimedia Telephony (MTSI) which imposes high demands on the transport channel. In a packet switched network any intermediary node can act like a congestion bottle neck leading to delay or packet loss. In this scenario a fast end to end adaptation scheme at the media layer can play a vital role to secure service performance by ensuring high quality throughout the session, even in extreme conditions, and keeps the service alive avoiding session termination. This thesis report describes a study of perceived video quality improvement using end to end congestion control depending on both “pre-warning” for congestion and packet loss observed at receiver in IMS video telephony over 3GPP LTE system according to 3GPP TS 26.114 V7.0.0. In the process of achieving the goal a new adaptation state machine was developed with different strategies to address the early congestion notification and packet losses. Simulations has been carried out with different adaptation schemes to compare results and benefits of newly proposed scheme. This thesis shows the effectiveness of early congestion notification for real-time video transmission and reveals some important aspects of adaptation procedure which need to be considered while designing adaptation for video traffic to avoid the congestion in a LTE network. The results found in the study suggest the inclusion of ECN for UDP traffic for future network like LTE.

Place, publisher, year, edition, pages
Keyword [en]
Keyword [sv]
URN: urn:nbn:se:ltu:diva-48362ISRN: LTU-PB-EX--07/064--SELocal ID: 5d07167d-c24e-45fe-9fe8-b2b7f194d4ceOAI: diva2:1021704
Subject / course
Student thesis, at least 30 credits
Educational program
Computer Science and Engineering, master's level
Validerat; 20101217 (root)Available from: 2016-10-04 Created: 2016-10-04Bibliographically approved

Open Access in DiVA

fulltext(1925 kB)0 downloads
File information
File name FULLTEXT01.pdfFile size 1925 kBChecksum SHA-512
Type fulltextMimetype application/pdf

Search outside of DiVA

GoogleGoogle Scholar
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

ReferencesLink to record
Permanent link

Direct link