基于H.264 (SVC)的4G广播/组播无线视频通信中速率划分的最优量化参数选择

Nitin Khanna, A. Jagannatham
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引用次数: 1

摘要

本文提出了一种基于H.264可扩展视频编码(SVC)的4G无线广播和组播视频传输中视频质量最大化的新方案。典型的无线多播组由具有不同无线链路质量的多媒体客户端组成。因此,为了在组播视频传输中实现QoS公平性,传统的公平速率静态视频(FRSV)传输方案受到链路容量最差的BMG用户的速率和质量限制。因此,我们提出了一种新的基于速率划分的可扩展视频(RPSV)传输框架来克服这一限制。提出的RPSV方案对多播组进行了优化划分,以实现H.264编码基的传输,增强了视频层的可扩展性。这是基于H.264 SVC中增强层编码的中粒度可伸缩性(MGS)特征。通过求解一系列凸目标最小化问题,证明了基于BMG划分和相关量化、时间分数参数的最优无线链路质量。RPSV避免了最差链路用户导致的速率瓶颈,从而自然地显著提高了网络多播组视频质量,同时避免了最差链路用户的业务饥饿,从而实现了QoS公平性。我们将提出的基于RPSV的量化参数自适应范式与简化的FRSV方案的性能进行了比较,并证明了前者的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Rate partitioning for optimal quantization parameter selection in H.264 (SVC) based 4G broadcast/multicast wireless video communication
In this paper we present a novel scheme for video quality maximization in the context of H.264 scalable video coding (SVC) based 4G wireless broadcast and multicast video transmission. A typical wireless multicast group comprises of multimedia clients with varying wireless link qualities. Thus, the conventional fair rate static video (FRSV) transmission scheme, which aims to achieve QoS fairness in multicast video transmission is rate and hence quality constrained by the BMG subscriber with the worst link capacity. Hence, we propose a novel rate partitioning based scalable video (RPSV) transmission framework to overcome this limitation. The proposed RPSV scheme optimally partitions the multicast group for transmission of the H.264 coded base and enhancement scalable video layers. This is based on the Medium Grain Scalability (MGS) feature for enhancement layer coding in H.264 SVC. We demonstrate that the optimal wireless link quality based BMG partition and the associated quantization, time-fraction parameters can be computed by solving a series of convex objective minimization problems. RPSV naturally leads to a significant enhancement in the net multicast group video quality by avoiding the rate bottleneck otherwise caused by the worst link user, while simultaneously resulting in QoS fairness by avoiding service starvation of the user with the poorest link quality. We compare the resulting video quality obtained from the proposed RPSV based quantization parameter adaptation paradigm with the performance of the simplistic FRSV scheme and demonstrate the superiority of the former.
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