SSIM-based error-resilient rate-distortion optimization of H.264/AVC video coding for wireless streaming

The SSIM-based rate-distortion optimization (RDO) has been verified to be an effective tool for H.264/AVC to promote the perceptual video coding performance. However, the current SSIM-based RDO is not efficient for improving the perceptual quality of the video streaming application over the error-prone network, because it does not consider the transmission induced distortion in the encoding process. In this paper, a SSIM-based error-resilient RDO scheme for H.264/AVC is proposed to improve the wireless video streaming performance. Firstly, with the help of the SSE-based RDO, we present a low-complexity Lagrange multiplier decision method for the SSIM-based RDO video coding in the error-free environment. Then, the SSIM-based decoding distortion of the user end is estimated at the encoder and is correspondingly introduced into the RDO to involve the transmission induced distortion into the encoding process. Further, the Lagrange multiplier is theoretically derived to optimize the encoding mode selection in the error-resilient RDO process. Experimental results show that the proposed SSIM-based error-resilient RDO can obtain superior perceptual video quality (more structural information) to the traditional SSE-based error-resilient RDO for wireless video streaming at the same bit rate condition.     

3D visual experience oriented cross-layer optimized scalable texture plus depth based 3D video streaming over wireless networks

3D video streaming over the mobile Internet generally incurs the inferior 3D visual experience due to the time-varying characteristics of wireless channel. The conventional video streaming optimization methods generally neglect the harmony among different networking protocol layers. This paper proposes a cross-layer optimized texture plus depth based scalable 3D video streaming method to improve the expected 3D visual experience of the user by systematically considering the application layer texture-video/depth/FEC bit-rate allocation, MAC layer multi-channel allocation, and physical layer modulation and channel coding scheme (MCS) selection. In the cross-layer optimization, a networking-related 3D visual experience model which fuses the overlapped retinal view visual quality and depth sensation with mimicking human vision system is established to predict the 3D visual experience under the specific parameter configurations of different protocol layers. The efficiency and effectiveness of the proposed cross-layer optimized 3D video streaming method has been validated by subjective and objective experimental results.     

Cross-layer optimized authentication and error control for wireless 3D medical video streaming over LTE

3D video for tele-medicine applications is gradually gaining momentum since the 3D technology can provide precise location information. However, the weak link for 3D video streaming is the necessary wireless link of the communication system. Neglecting the wireless impairments can severely degrade the performance of 3D video streaming that communicates complex critical medical data. In this paper, we propose systematic methodology for ensuring high performance of the 3D medical video streaming system. First, we present a recursive end-to-end distortion estimation approach for MVC (multiview video coding)-based 3D video streaming over error-prone networks by considering the 3D inter-view prediction. Then, based on the previous model, we develop a cross-layer optimization scheme that considers the LTE wireless physical layer (PHY). In this optimization, the authentication requirements of 3D medical video are also taken into account. The proposed cross-layer optimization approach jointly controls and manages the authentication, video coding quantization of 3D video, and the modulation and channel coding scheme (MCS) of the LTE wireless PHY to minimize the end-to-end video distortion. Experimental results show that the proposed approach can provide superior 3D medical video streaming performance in terms of peak signal-to-noise ratio (PSNR) when compared to state-of-the-art approaches that include joint source-channel optimized streaming with multi-path hash-chaining based-authentication, and also conventional video streaming with single path hash-chaining-based authentication.     

OFDM系统中视频传输的调度算法研究

针对OFDM系统,提出了一种基于视频内容的跨层调度方案。该方案采用了基于生存期的包排序策略,根据视频包的生存期大小进行排序,保证视频包能在生存期内发送到接收端,减少丢包数目。同时,采用跨层设计的思想,综合考虑了信道状况和视频包特性,如视频包生存期、重要性、解码器采用的错误掩藏方法,提出改进的比例公平调度算法,不仅有效地利用了多用户分集来进一步提高数据吞吐量,也充分考虑了视频的重要性和时延约束。实验结果表明,采用内容感知的跨层调度算法,解码端的视频质量得到有效提高,从而可以提高主观感知质量。     

Combining the rate adaptation and quality adaptation schemes for wireless video streaming

Video streaming service over wireless networks is a challenging task because of the changes in the wireless channel conditions that can occur due to interference, fading, and station mobility. Moreover, the IEEE 802.11 WLAN standard does not contain any specifications for the rate adaptation scheme which are useful for improving the wireless link utilization. To provide efficient wireless video streaming service, the rate adaptation scheme should be applied at the low layer and the quality adaptation scheme should be considered at the high layer. To meet this requirement of wireless video streaming, we propose a new cross-layer design for video streaming over wireless networks. This design includes the rate adaptation scheme in the data link and physical layers and the quality adaptation scheme in the application layer. The rate adaptation scheme adjusts the data transmission rate based on the measured RSSI at the sender-side and informs the quality adaptation scheme about the rate limits. Then the quality adaptation scheme utilizes this rate limits to adjust the quality of the video stream. Through performance evaluations, we prove that our cross-layer design improves the wireless link utilization and the quality of the video stream simultaneously.     

Joint QoS control for video streaming over wireless multihop networks: A cross-layer approach

In this paper, we propose a novel cross-layer framework for jointly controlling and coding for multiple video streams in wireless multihop networks. At first, we develop a cross-layer flow control algorithm that works at the medium access control (MAC) layer to adjust each link's persistence probability and at the transport layer to adjust flow rates. This proposal is designed in a distributed manner that is amenable to online implementation for wireless networks, and then, a rate-distortion optimized joint source-channel coding (JSCC) approach for error-resilient scalable encoded video is presented, in which the video is encoded into multiple independent streams and each stream is assigned forward error correction (FEC) codes to avoid error propagation. Furthermore, we integrate the JSCC with the specific flow control algorithm, which optimally applies the appropriate channel coding rate given the constraints imposed by the transmission rate obtained from the proposed flow control algorithm and the prevailing channel condition. Simulation results demonstrate the merits and the need for joint quality of service (QoS) control in order to provide an efficient solution for video streaming over wireless multihop networks.     

Rate-distortion based real-time wireless video streaming

This paper presents wireless video streaming techniques that exploit the characteristics of video content, transmission history, and physical layer channels to enable real-time efficient video streaming over wireless networks to a wireless client. The key contribution of the proposed video streaming techniques is the use of rate-distortion based, but simplified, low complexity packet scheduling as well as forward error correction (FEC) rate selection. To this end, we develop an optimization framework that jointly schedules the packets and selects the FEC rates. The rate-distortion optimized packet scheduling and FEC rate selection provides the optimum quality video on the receiver side albeit at a high computational cost. By some intelligent approximations, rate distortion optimized packet scheduling and FEC rate selection technique is transformed into two sub-optimal but low complexity video streaming techniques that can provide high video quality. We perform extensive simulations to understand the performance of our proposed techniques under different scenarios. Results show that, the proposed techniques improve video quality on the average by 4 dB. We conclude that significant benefits to end-user experience can be obtained by using such video streaming methods.     

Enhancing the Performance of Video Streaming in Wireless Mesh Networks

Multihop wireless mesh networks (WMNs) provide ubiquitous wireless access in a large area with less dependence on wired networks. However, some emerging applications with high bandwidth requirement and delay and loss constraints, such as video streaming, suffer poor performance in WMNs, since high compression rates and/or high packet loss rates deteriorate the video quality. In this paper, we propose a novel mechanism composed of (1) a network route selection scheme which provides paths for multiple video streams with the least interference, called Minimum Interference Route Selection (MIROSE) and (2) an optimization algorithm that determines the compression rates depending on the network condition, called Network State Dependent Video Compression Rate (NSDVCR) algorithm. Simulation results of the proposed mechanisms show the significant improvement of the video quality measured with a popular metric, Peak-Signal-to-Noise Ratio (PSNR), compared with standard routing and default compression rates.     

Cross-Layer Optimized Rate Adaptation and Scheduling for Multiple-User Wireless Video Streaming

We present a cross-layer optimized video rate adaptation and user scheduling scheme for multi-user wireless video streaming aiming for maximum quality of service (QoS) for each user,, maximum system video throughput, and QoS fairness among users. These objectives are jointly optimized using a multi-objective optimization (MOO) framework that aims to serve the user with the least remaining playback time, highest delivered video seconds per transmission slot and maximum video quality. Experiments with the IS-856 (1timesEV-DO) standard numerology and ITU pedestrian A and vehicular B environments show significant improvements over the state-of- the-art wireless schedulers in terms of user QoS, QoS fairness, and the system throughput.     

A unified framework for distributed video rate allocation over wireless networks

When multiple video streams share a wireless network, careful rate allocation is needed to prevent congestion, as well as to balance the video qualities among the competing streams. In this paper, we present a unified optimization framework for video rate allocation over wireless networks. Our framework applies to both unicast and multicast sessions, and accommodates both scalable and non-scalable streams. The optimization objective is to minimize the total distortion of all video streams without incurring excessive network utilization. Our system model explicitly accounts for heterogeneity in wireless link capacities, traffic contention among neighboring links, as well as different video rate-distortion (RD) characteristics. The proposed distributed media-aware rate allocation scheme leverages cross-layer information exchange between the MAC and application layers to achieve fast convergence at the optimal allocation.We evaluate performance of the proposed scheme for streaming of high-definition (HD) and standard-definition (SD) video sequences over 802.11-based wireless networks, both in unicast and multicast scenarios. The scheme consistently outperforms conventional TCP-Friendly Rate Control (TFRC) in terms of overall video quality, and achieves more balanced qualities among the streams.     

Design and Implementation of a Network‐Adaptive Mechanism for HTTP Video Streaming

This paper proposes a network‐adaptive mechanism for HTTP‐based video streaming over wireless/mobile networks. To provide adaptive video streaming over wireless/mobile networks, the proposed mechanism consists of a throughput estimation scheme in the time‐variant wireless network environment and a video rate selection algorithm used to increase the streaming quality. The adaptive video streaming system with proposed modules is implemented using an open source multimedia framework and is validated over emulated wireless/mobile networks. The emulator helps to model and emulate network conditions based on data collected from actual experiments. The experiment results show that the proposed mechanism provides higher video quality than the existing system provides and a rate of video streaming almost void of freezing.     

Cross-Layer Architecture for Adaptive Video Multicast Streaming Over Multirate Wireless LANs

Multicast video streaming over multirate wireless LANs imposes strong demands on video codecs and the underlying network. It is not sufficient that only the video codec or only the underlying protocols adapt to changes in the wireless link quality. Research efforts should be applied in both and in a synchronized way. Cross layer design is a new paradigm that addresses this challenge by optimizing communication network architectures across traditional layer boundaries. This paper presents cross-layer architecture for adaptive video multicast streaming over multirate wireless LANs where layer-specific information is passed in both directions, top-down and bottom-up. The authors jointly consider three layers of the protocol stack: the application, data link and physical layers. The authors analyze the performance of the proposed architecture and extensively evaluate it via simulations. The results show that the real-time video quality of the overall system can be greatly improved by cross-layer signaling.     

Cross-Layer Optimized Video Streaming Over Wireless Multihop Mesh Networks

The proliferation of wireless multihop communication infrastructures in office or residential environments depends on their ability to support a variety of emerging applications requiring real-time video transmission between stations located across the network. We propose an integrated cross-layer optimization algorithm aimed at maximizing the decoded video quality of delay-constrained streaming in a multihop wireless mesh network that supports quality-of-service. The key principle of our algorithm lays in the synergistic optimization of different control parameters at each node of the multihop network, across the protocol layers-application, network, medium access control, and physical layers, as well as end-to-end, across the various nodes. To drive this optimization, we assume an overlay network infrastructure, which is able to convey information on the conditions of each link. Various scenarios that perform the integrated optimization using different levels ("horizons") of information about the network status are examined. The differences between several optimization scenarios in terms of decoded video quality and required streaming complexity are quantified. Our results demonstrate the merits and the need for cross-layer optimization in order to provide an efficient solution for real-time video transmission using existing protocols and infrastructures. In addition, they provide important insights for future protocol and system design targeted at enhanced video streaming support across wireless mesh networks     

ARMOR – A system for adjusting repair and media scaling for video streaming

To optimize scarce network resources and present the highest quality video, streaming video systems need adapt to the video content as well as the network conditions. This paper presents ARMOR, a video streaming system that dynamically adjusts repair and media scaling to meet current video and network conditions. In order to adapt effectively, ARMOR, and any dynamic video adaptation system, needs to predict the video quality as perceived by end users over the range of scaling and repair choices. Thus, this paper first proposes a novel video quality metric called distorted playable frame rate that provides estimation of user perceptual quality considering temporal and quality degradations. Comprehensive user studies show distorted playable frame rate is more accurate than other video quality metrics. Analytic experiments with distorted playable frame rate and the ARMOR optimization algorithm illustrate the predictive power of the metric in a dynamic, streaming video system. Lastly, implementation and experiments of a complete, fully-functioning ARMOR system show the effective practicality of the proposed approach.     

Environment-Driven Opportunity Forwarding Cross-Layer Optimization for Ubiquitous Wireless Networks

In this paper, an environment-driven cross-layer optimization scheme is proposed to maximize packet forwarding efficiency. The proposed algorithm is aimed to improve the performance of location-based routing protocol in respect of greedy forwarding and avoid void regions for ubiquitous wireless networks. In greedy forwarding mode, we use a new routing metric IAPS which can estimate the forwarding distance, link quality and the difficulty of channel access during the process of the next hop node selection. When the packet forwarding comes into a local minimum, the proposed scheme uses an opportunistic forwarding method based on competitive advantage to bypass the void regions. NS2 simulation results indicate that the proposed algorithm can improve network resource utilization and the average throughput, and reduce congestion loss rate of wireless multi-hop network comparison with existing GPSR algorithm.     

Resource allocation for downlink multiuser video transmission over wireless lossy networks

Demand for multimedia services, such as video streaming over wireless networks, has grown dramatically in recent years. The downlink transmission of multiple video sequences to multiple users over a shared resource-limited wireless channel, however, is a daunting task. Among the many challenges in this area are the time-varying channel conditions, limited available resources, such as bandwidth and power, and the different transmission requirements of different video content. This work takes into account the time-varying nature of the wireless channels, as well as the importance of individual video packets, to develop a cross-layer resource allocation and packet scheduling scheme for multiuser video streaming over lossy wireless packet access networks. Assuming that accurate channel feedback is not available at the scheduler, random channel losses combined with complex error concealment at the receiver make it impossible for the scheduler to determine the actual distortion of the sequence at the receiver. Therefore, the objective of the optimization is to minimize the expected distortion of the received sequence, where the expectation is calculated at the scheduler with respect to the packet loss probability in the channel. The expected distortion is used to order the packets in the transmission queue of each user, and then gradients of the expected distortion are used to efficiently allocate resources across users. Simulations show that the proposed scheme performs significantly better than a conventional content-independent scheme for video transmission.     

Quality-aware cross-layer scheduling for robust video streaming over wireless channels

In the case of video streaming over wireless channels, burst errors may lead to serious video quality degradation. By jointly exploiting the scheduling mechanism on different communication layers, this paper proposes a quality-aware cross-layer scheduling scheme to achieve unequal error control for each Latency-constraint Frame Set (LFS) of a video stream. After a network-layer agent at base station firstly utilizes the network-layer packet scheduling to provide packet-granularity importance classification for the current LFS, a link-layer agent at base station further utilizes the Radio-Link-Unit (RLU) scheduling to implement finer selective retransmission of the current LFS. Under scheduling delay and bandwidth constraints, the proposed scheme can be aware of the application-layer quality and time-varying channel conditions, and hence burst errors can simply be shifted to lower-priority transmission units in the current LFS. Simulation results demonstrate that the proposed scheme has strong robustness against burst errors, and thus improves the overall received quality of the video stream over wireless channels.     

Visual‐Attention‐Aware Progressive RoI Trick Mode Streaming in Interactive Panoramic Video Service

In the near future, traditional narrow and fixed viewpoint video services will be replaced by high‐quality panorama video services. This paper proposes a visual‐attention‐aware progressive region of interest (RoI) trick mode streaming service (VA‐PRTS) that prioritizes video data to transmit according to the visual attention and transmits prioritized video data progressively. VA‐PRTS enables the receiver to speed up the time to display without degrading the perceptual quality. For the proposed VA‐PRTS, this paper defines a cutoff visual attention metric algorithm to determine the quality of the encoded video slice based on the capability of visual attention and the progressive streaming method based on the priority of RoI video data. Compared to conventional methods, VA‐PRTS increases the bitrate saving by over 57% and decreases the interactive delay by over 66%, while maintaining a level of perceptual video quality. The experiment results show that the proposed VA‐PRTS improves the quality of the viewer experience for interactive panoramic video streaming services. The development results show that the VA‐PRTS has highly practical real‐field feasibility.     

Utility Function Selection for Streaming Videos with a Cognitive Engine Testbed

Cognitive Radio (CR) is a new wireless communication and networking paradigm that is enabled by the Software Defined Radio (SDR) technology and the recent change in spectrum regulation policy. As the first commercial application of CR technology, IEEE 802.22 wireless regional area networks (WRAN) aim to offer broadband wireless access by efficiently utilizing the unoccupied TV channels. In this paper, we investigate the problem of utility function selection and its impact on streaming video quality through an IEEE 802.22 WRAN base station (BS) cognitive engine (CE) testbed developed at Wireless@Virginia Tech. We find that significant improvement on received video quality can be achieved when CE adopts a dynamic, content-aware, video-specific utility function rather than a static, predefined, general purpose utility function. This work indicates the importance of video distortion modeling and cross-layer design, and the need for employing dynamic content-aware utility functions at the CE for cognitive streaming video communication networks.