Quality and Usability

Mobisense - Multimedia User Perception of Mobility in NGN

Motivation & Project Description:
The Next Generation Networks (NGNs) offer independent access to multimedia services (e.g. mobile TV, VoIP) and the possibility of seamless roaming among heterogeneous networks during active sessions. It is important for network operators to provide high quality transmission and mobility support that enable users to experience seamless services as “always best connected”. So far, networks are planned and deployed using limited information about actual user perception of multimedia services (i.e. mobile TV) and  real-time applications (i.e. Video conferencing) running on top of these networks, and these processes are merely limited to network performance metrics only. 

Mobisense goes video deals with the user perception of audio-visual services  in the context of Next Generation Networks and seamless mobility. Therefore, it contributes to close the gap between network performancemetrics and real user perception of these services. Using this two-viewed evaluation approach, Mobisense goes video enables to answer the question of how future audio-visual services will be experienced in the context of NGNs, mobile technologies, and seamless mobility. For this vision of future networks, it is important to correlate user perception (of audio-visual services) and network performance, tightly coupling these important metrics.

Expected Outcome:

  • Complete case study on user perception of audio/video services in
    heterogeneous Next Generation Networks.(Focus: Video conferencing and mobile TV)
  • Subjective test methodology, which enables to assess impact of mobility on perception of multimedia users in wireless NGNs.
  • High-customizable test environment, which enables to measure user perception of video/audio services under NGN conditions.
  • Prototype solution for mobility management and audio/video service adaptation, which copes with extreme changes in underlying network technologies.
  • Contribution to existing quality prediction models for audio/video services, including information about the targeted phenomena.

Time Frame: 10/2008 - 12/2010

T-labs Team Members:Benjamin Belmudez, Blazej Lewcio, Sebastian Möller, Alexander Raake, Pablo Vidales, Marcel Wältermann

Partners: DAI-Labor (Frank Steuer), TKN TU Berlin

Funding by: Deutsche Telekom Laboratories