Adaptive and reliable video transmission over UMTS for enhanced performance

Alexiou, Antonios; Antonellis, Dimitrios; Bouras, Christos

doi:10.1002/dac.814

Cited by 16 publications

(7 citation statements)

References 18 publications

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“…In [9] the authors have proposed a bitrate control scheme based on congestion feedback over the Internet. In [25][26][27] authors have presented adaptation based on network state and congestion control over UMTS transport channels. Authors in [28] have presented an adaptive bandwidth allocation scheme based on the queue length and the packet loss probability.…”

Section: Related Workmentioning

confidence: 99%

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

et al. 2010

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Network quality of service (NQoS) of IP networks is unpredictable and impacts the quality of networked multimedia services. Adaptive voice and video schemes are therefore vital for the provision of voice over IP (VoIP) services for optimised quality of experience (QoE). Traditional adaptation schemes based on NQoS do not take perceived quality into consideration even though the user is the best judge of quality. Additionally, uncertainties inherent in NQoS parameter measurements make the design of adaptation schemes difficult and their performance suboptimal. This paper presents a QoE-driven adaptation scheme for voice and video over IP to solve the optimisation problem to provide optimal QoE for networked voice and video applications. The adaptive VoIP architecture was implemented and tested both in NS2 and in an Open IMS Core network to allow extensive simulation and test-bed evaluation. Results show that the scheme was optimally responsive to available network bandwidth and congestion for both voice and video and optimised delivered QoE for different network conditions, and is friendly to TCP traffic.

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Section: Related Workmentioning

confidence: 99%

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

et al. 2010

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“…The use of TFRC for streaming video over UMTS is given in [11]. The round trip time and the packet loss rate are estimated using the standard real time control protocol (RTCP) RR.…”

Section: Congestion Controlmentioning

confidence: 99%

Transmission algorithm for video streaming over cellular networks

2009

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2.5G and 3G cellular networks are becoming more widespread and the need for value added services increases rapidly. One of the key services that operators seek to provide is streaming of rich multimedia content. However, network characteristics make the use of streaming applications very difficult with an unacceptable quality of service (QoS). The 3GPP standardization body has standardized streaming services that will benefit operators and users. There is a need for a mechanism that will enable a good quality multimedia streaming that uses the 3GPP standard. This paper describes an adaptive streaming algorithm that uses the 3GPP standard. It improves significantly the QoS in varying network conditions while monitoring its performance using queueing methodologies. The algorithm utilizes the available buffers on the route of the streaming data in a unique way that guarantees high QoS. The system is analytically modeled: the streaming server, the cellular network and the cellular client are modeled as cascaded buffers and the data is sequentially streamed between them. The proposed Adaptive streaming algorithm (ASA) controls these buffers' occupancy levels by controlling the transmission and the encoding rates of the streaming server to achieve high QoS for the streaming. It overcomes the inherent fluctuations of the network bandwidth. The algorithm was tested on General Packet Radio Service (GPRS), Enhanced Data rates for GSM Evolution (EDGE) and Universal Mobile Telecommunication System (UMTS) networks. The results showed substantial improvements over other standard streaming methods used today.

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“…It is crucial to predict the QoS degradation that may be experienced by multimedia applications over wireless access networks. Video transmissions applications need to be responsive to dynamic changes and different demands [24]. In the presence of packet loss, video quality becomes highly timevariant [24,25].…”

Section: Multimedia Streaming Trafficmentioning

confidence: 99%

“…Similarly, in [21 -23] the authors outline the transmission requirements and the performance of UMTSdedicated channels of UMTS networks for video streaming. In [24], the authors have proposed a mechanism for congestion control for video transmission over UMTS networks, whereas in [25] an error detection scheme is proposed for H.264 encoded videos. In [26] transcoding is used to adapt video content transmitted over UMTS networks.…”

Section: Introductionmentioning

confidence: 99%

Learning models for video quality prediction over wireless local area network and universal mobile telecommunication system networks

2010

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Universal mobile telecommunication system (UMTS) is a third-generation mobile communications system that supports wireless wideband multimedia applications. The primary aim of this study is to present learning models based on neural networks for objective, non-intrusive prediction of video quality over wireless local area network (WLAN) and UMTS networks for video applications. The contributions of this study are twofold: first, an investigation of the impact of parameters both in the application and physical layer on end-to-end video quality is presented. The parameters considered in the application layer are content type (CT), sender bitrate (SBR) and frame rate (FR), whereas in the physical layer block error rate (BLER) and link bandwidth (LBW) are considered. Secondly, learning models based on adaptive neural fuzzy inference system (ANFIS) are developed to predict the visual quality in terms of the mean opinion score for all contents over access networks of UMTS and WLAN. ANFIS is well suited for video quality prediction over error-prone and bandwidth restricted UMTS as it combines the advantages of neural networks and fuzzy systems. The ANFISbased artificial neural network is trained using a combination of physical layer parameters such as BLER and LBW and application layer parameters of CT, SBR and FR. The proposed models are validated using unseen data set. The preliminary results show that good prediction accuracy was obtained from the models. This study should help in the development of a reference-free video prediction model and quality of service control methods for video over UMTS/WLAN networks.

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Adaptive and reliable video transmission over UMTS for enhanced performance

Cited by 16 publications

References 18 publications

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

Quality of experience (QoE) driven adaptation scheme for voice/video over IP

Transmission algorithm for video streaming over cellular networks

Learning models for video quality prediction over wireless local area network and universal mobile telecommunication system networks

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