Models and analysis of video streaming end-to-end distortion over LTE network

Fu, Huayong; Yuan, Hui; Li, Mengyu; Sun, Zhenzhen; Li, Fengrong

doi:10.1109/iciea.2016.7603638

Cited by 4 publications

(4 citation statements)

References 13 publications

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“…These cellular technologies can offer extra grades of freedom to customers, which can be utilized to ensure reducing the noise, fade, and hardware impairments when signals from a large number of antennas are collected in common air. Consequently, it can rise the capacity by many times and it can improve energy efficiency radiating by many times, which can ensure the quality of received signal and achieve a high reliable link [6,7].…”

Section: Introductionmentioning

confidence: 99%

Developing a Video Buffer Framework for Video Streaming in Cellular Networks

Jabbar

Kadhim

2018

Wireless Communications and Mobile Computing

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This work proposes a new video buffer framework (VBF) to acquire a favorable quality of experience (QoE) for video streaming in cellular networks. The proposed framework consists of three main parts: client selection algorithm, categorization method, and distribution mechanism. The client selection algorithm was named independent client selection algorithm (ICSA), which is proposed to select the best clients who have less interfering effects on video quality and recognize the clients’ urgency based on buffer occupancy level. In the categorization method, each frame in the video buffer is given a specific number for better estimation of the playout outage probability, so it can efficiently handle so many frames from different videos at different bitrates. Meanwhile, at the proposed distribution mechanism, a predetermined threshold value is selected for lower and upper levels of playout outage probability. Then, the control unit at the base station will distribute the radio resources and decide the minimum rate requirement based on clients’ urgency categories. Simulation results showed that the VBF grantees fairness of resources distribution among different clients within the same cellular network while minimizing the interruption duration and controlling the video buffer at an acceptable level. Also, the results showed that the system throughput of the proposed framework outperforms other existing algorithms such as playout buffer and discontinuous reception aware scheduling (PBDAS), maximum carrier-to-interface ratio (MAX-CIR), and proportional fair (PF) due to enhancing the quality of experience for video streaming by increasing the radio resources in fairness manner.

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Section: Introductionmentioning

confidence: 99%

Developing a Video Buffer Framework for Video Streaming in Cellular Networks

Jabbar

Kadhim

2018

Wireless Communications and Mobile Computing

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“…They refine the distortion model in [30] to support both source and channel distortion. Fu et al [12] investigate the source and channel distortion over LTE networks. All the above works apply GoP-level FEC, allowing them to cancel out error propagation at the cost of high motion to photon latency.…”

Section: Mobile Cloud Gamingmentioning

confidence: 99%

“…Video encoding and decoding take the time, 20.8 and 9.1 ms respectively as the libvpx operates solely on CPU. By leveraging hardware-level video encoding and decoding as it would be the case on mobile devices, we expect to reduce these values to 5-10 ms 12 , and achieve a pipeline latency below 30 ms. Nebula thus does not introduce significant latency compared to typical cloud gaming systems, while bringing loss recovery capabilities in a lossy transmission environment.…”

Section: Pipeline Characterizationmentioning

confidence: 99%

“…Figure 7.a represents the MTP latency, network RTT, and average PSNR for all solutions. Only BO satisfies the requirement of MTP latency below 130 ms in such constrained environment, while 12 https://developer.nvidia.com/nvidia-video-codec-sdk Nebula and WebRTC remain close (138.6 ms and 144.8 ms respectively). TCP Cubic collapses under the abrupt bandwidth changes and presents the highest motion-to-photon latency (807.6 ms), with a high variance caused by the loss retransmission.…”

Section: Emulated Networkmentioning

confidence: 99%

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Nebula: Reliable Low-latency Video Transmission for Mobile Cloud Gaming

Alhilal¹,

Braud²,

Han³

et al. 2022

Preprint

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Mobile cloud gaming enables high-end games on constrained devices by streaming the game content from powerful servers through mobile networks. Mobile networks suffer from highly variable bandwidth, latency, and losses that affect the gaming experience. This paper introduces Nebula, an end-to-end cloud gaming framework to minimize the impact of network conditions on the user experience. Nebula relies on an end-to-end distortion model adapting the video source rate and the amount of frame-level redundancy based on the measured network conditions. As a result, it minimizes the motion-to-photon (MTP) latency while protecting the frames from losses. We fully implement Nebula and evaluate its performance 1 https://www.windowscentral.com/early-tests-call-google-stadias-picture-qualityquestion-and-thats-shame

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