Graceful Degradation Of Video Quality Research Articles

A metadata-free pure soft broadcast scheme for image and video transmission

The SoftCast, as an analog-like transmission scheme, has been proposed to provide graceful video quality degradation for wireless communication scenarios where channel condition usually varies dynamically and unpredictably. It attempts to eliminate the cliff effect that conventional communication systems usually suffer from. The unequal power allocation minimizes the total distortion by optimally scaling the transform coefficients according to their statistics. However, the sender has to transmit considerable amount of metadata over a digital channel with strong channel codes to assist in decoding at the receiver. And the transmission will still break down completely if the metadata are corrupted. Hence, SoftCast can just alleviate the cliff effect. To eliminate the cliff effect while maintaining the image and video quality, a feasible metadata-free pure soft broadcast scheme for image and video transmission is proposed in this paper. Specifically, we apply an effective chunk-based blind estimation method to reconstruct the original signal from the received noisy signal without using power scaling factors. Thus, our scheme can eliminate the cliff effect. In addition, since smaller chunks can be used, better performance than SoftCast has been achieved. Experimental results show that our scheme outperforms SoftCast by about 4dB and provides graceful quality degradation for a wide channel signal to noise ratio range.

QoE-driven multi-user scheduling and rate adaptation with reduced cross-layer signaling for scalable video streaming over LTE wireless systems

The scarcity of the available radio spectrum coupled with the growing popularity of bandwidth intensive mobile video applications poses a huge challenge to network operators. The solution of over-provisioning the network is not economical; hence, an appropriate strategy for scheduling and resource allocation among the users in the system is of crucial importance. This work focuses on scheduling multiple video flows on the downlink of a wireless system based on orthogonal frequency division multiple access (OFDMA), such as Long-Term Evolution (LTE) and LTE-A (LTE-Advanced) standards. We propose a joint multi-user scheduling and multi-user rate adaptation strategy providing an appropriate trade-off between efficiency and fairness, while ensuring high quality of experience (QoE) for the end users. We consider Scalable Video Coding (SVC) which facilitates the truncation of bit streams, thus allowing graceful degradation of video quality in the event of wireless channel variations or network congestion. The proposed scheduler utilizes QoE-aware priority marking, where video layers are mapped to priority classes and targets at minimizing delay bound violations for the most important priority classes under congestion. In order to reduce congestion, we propose multi-user rate adaptation at the MAC layer via a novel dynamic filtering policy for QoE-based priority classes. Simulation results show that the proposed approach delivers to the end users a similar QoE as delivered by the state-of-the-art cross-layer approaches, where extensive cross-layer signaling, additional video rate adaptation modules at the core network, and frequent link probing from the wireless access network to the rate adaptation modules are required. The latter approaches are not implemented in real systems due to the aforementioned drawbacks, while our approach can be implemented without major modifications in the standard behavior of existing networks and equipment. The proposed framework can deliver delay-sensitive traffic as well as delay-tolerant best-effort traffic.

QoS-aware scalable video streaming using data distribution service

Enabling Real-Time video streaming over wireless networks is a challenging task due to the time-varying channel conditions and the limited network resources. The instability of wireless networks leads to problems such as limited and time-varying bandwidth, and unexpected traffic congestion when transmitting a burst of video streams. In Real-Time video streaming, each frame must be delivered and decoded by its playback time. Recently, layer coding (LC) has enabled Real-Time and scalable video streaming to clients of heterogeneous capabilities by dropping upper enhancement layers without the need of re-encoding and with much less bit rate. However, layer coding still facing unfair layer protection problem in which packets from the base or lower layers might be dropped while there is a chance to drop packets from the upper enhancement layers. Losing packets from the base layer can significantly affect the delivered video quality and sometimes lead to an interruption especially in error-prone networks as wireless networks. Architectural solutions at the middleware level introduce higher flexibility, more efficiency in development time and more QoS control. This work investigates the behavior of video streaming over Real-Time publish-subscribe based middleware. We propose and develop an unequal layer protection mechanism for Real-Time video streaming based on the Data Distribution Service (DDS) middleware. A combination of video quality of service (QoS) is proposed to adapt the video transmission to the time-varying network changes. The performance of Real-Time video streaming is measured over IEEE 802.11 g WLAN network. The results show a graceful degradation of video quality while maintaining a robust video streaming free of visible error or interruptions. This is due to the intentionally dropping of some enhancement video stream layers in order to protect lower layers, and therefore maintain a continuous video flow of acceptable quality. Numerical results indicate that the proposed scheme is able to achieve higher throughput and improve the average received video quality especially in a large number of video subscribers.

GOP-based channel rate allocation using genetic algorithm for scalable video streaming over error-prone networks

In this paper, we address the problem of unequal error protection (UEP) for scalable video transmission over wireless packet-erasure channel. Unequal amounts of protection are allocated to the different frames (I- or P-frame) of a group-of-pictures (GOP), and in each frame, unequal amounts of protection are allocated to the progressive bit-stream of scalable video to provide a graceful degradation of video quality as packet loss rate varies. We use a genetic algorithm (GA) to quickly get the allocation pattern, which is hard to get with other conventional methods, like hill-climbing method. Theoretical analysis and experimental results both demonstrate the advantage of the proposed algorithm.

Joint loss pattern characterization and unequal interleaved FEC protection for robust H.264 video distribution over wireless LAN

The recently adopted H.264 standard achieves efficient video encoding and bandwidth savings. Thus, designing communication protocols and QoS control mechanisms for H.264 video distribution over wireless IP networks is a topic of intense research interest. Delivering video streams to terminals via a wireless last hop is indeed a challenging task due to the varying nature of the wireless link. While a common approach suggests exploiting the variations of the wireless channel, an alternative is to exploit characteristics of the video stream to improve the transmission. In this paper, we combine both approaches through an efficient wireless loss characterization and a low-delay unequal interleaved FEC protection. Besides deriving new QoS metrics for FEC block allocation, the wireless loss characterization is as well used to adjust the interleaving level depending on the loss correlation exhibited by the wireless channel. This novel unequal interleaved FEC (UI-FEC) protocol allows graceful video quality degradation over error-prone wireless links while minimizing the overall bandwidth consumption and the end-to-end latency.

Unequal loss protection for robust transmission of motion compensated video over the internet

This paper presents an unequal loss protection (ULP) scheme for robust transmission of motion compensated video over the Internet. By exploiting the temporal dependency between frames, forward error correction (FEC) codes across packets are assigned to different frames in a group of pictures in the sense of minimizing the effect of error propagation, thus improving video quality significantly. To achieve optimal allocation of FEC codes, we formulate the effect of packet loss on video quality degradation as an expected length of error propagation (ELEP) model, which makes sense intuitively, as fewer frames corrupted implies better quality of reconstructed video. Experimental results show the validity of the proposed ELEP model and that the associated ULP scheme is robust to burst packet loss in the Internet. More importantly, graceful degradation of video quality is achieved by the proposed scheme as the packet loss rate of an Internet connection increases.