Enhanced adaptive streaming over LTE-advanced wireless networks

Foerster, J.R.; Oyman, Özgür; Liao, Yi‐Chu; Rehan, M.; Taie, Wafaa

doi:10.1109/acssc.2012.6489149

Cited by 2 publications

(2 citation statements)

References 4 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…It also optimizes bit rate switching [8]. iProxy is a mobile video-centric proxy cache that offers better hit rates and streaming quality as compared to state- [7,9] Playback smoothness Medium Very low [8, 11-14, 28, 31-34, 36-40] Classical objective quality metric Very low Low [4, 15-21, 41, 117] Subjective quality metric Very low Medium [26][27][28][29][30][31][32][33] Subjective quality metric for scalable video coding Medium Medium [43][44][45][46][47][48][49][50] Subjective QoE metric in lossy environment High High [22,42,[59][60][61][62][63][64][65][66][67][68][69][70][71][72][73] Video quality metric for advanced video coding High High [74][75][76][77][78][79][80][81][82]…”

Section: Playback Smoothness As Quality Metricmentioning

confidence: 99%

See 1 more Smart Citation

QoE in video streaming over wireless networks: perspectives and research challenges

Bai

et al. 2015

Wireless Netw

View full text Add to dashboard Cite

The deployment of 3G/LTE networks and advancements in smart mobile devices had led to high demand for multimedia streaming over wireless network. The rapid increasing demand for multimedia content poses challenges for all parties in a multimedia streaming system, namely, content providers, wireless network service providers, and smart device makers. Content providers and mobile network service providers are both striving to improve their streaming services while utilizing advancing technologies. Smart device makers endeavor to improve processing power and displays for better viewing experience. Ultimately, the common goal shared by content providers, network service providers, and smart device manufactures is to improve the QoE for users. QoE is both an objective and a subjective metric measuring the streaming quality experience by end users. It may be measured by streaming bitrate, playback smoothness, video quality metrics like Peak to Signal Noise Ratio, and other user satisfaction factors. There have been efforts made to improve the streaming experiences in all these aspects. In this paper, we conducted a survey on existing literatures on QoE of video streaming to gain a deeper and more complete understanding of QoE quality metrics. The goal is to inspire new research directions in defining better QoE and improving QoE in existing and new streaming services such as adaptive streaming and 3D video streaming.

show abstract

Section: Playback Smoothness As Quality Metricmentioning

confidence: 99%

“…An enhanced adaptive streaming technique for video streaming over LTE networks was designed in [50]. The adaption is based on subjective quality measures and objective estimation.…”

Section: Subjective Quality Mapped From Classical Objective Metricmentioning

confidence: 99%