Error resilient H.264 coded video transmission over wireless channels

The H.264/AVC recommendation was first published in 2003 and builds on the concepts of earlier standards such as MPEG-2 and MPEG-4. The H.264 recommendation represents an evolution of the existing video coding standards and was developed in response to the growing need for higher compression. Even though H.264 provides for greater compression, H.264 compressed video streams are very prone to channel errors in mobile wireless fading channels such as 3G due to high error rates experienced. Common video compression techniques include motion compensation, prediction methods, transformation, quantization and entropy coding, which are the common elements of a hybrid video codecs. The ITU-T recommendation H.264 introduces several new error resilience tools, as well as several new features such as Intra Prediction and Deblocking Filter. The channel model used for the testing was the Rayleigh Fading channel with the noise component simulated as Additive White Gaussian Noise (AWGN) using QPSK as the modulation technique. The channel was used over several Eb/N0 values to provide similar bit error rates as those found in the literature. Though further research needs to be conducted, results have shown that when using the H.264 error resilience tools in protecting encoded bitstreams to minor channel errors improvement in the decoded video quality can be observed. The tools did not perform as well with mild and severe channel errors significant as the resultant bitstream was too corrupted. From this, further research in channel coding techniques is needed to determine if the bitstream can be protected from these sorts of error rate

Cooperative systems based signal processing techniques with applications to three-dimensional video transmission

Three-dimensional (3-D) video has recently emerged to offer an immersive multimedia experience that can not be offered by two-dimensional (2-D) video applications. Currently, both industry and academia are focused on delivering 3-D video services to wireless communication systems. Modern video communication systems currently adopt cooperative communication and orthogonal frequency division multiplexing (OFDM) as they are an attractive solution to combat fading in wireless communication systems and achieve high data-rates. However, this strong motivation to transmit the video signals over wireless systems faces many challenges. These are mainly channel bandwidth limitations, variations of signal-to-noise ratio (SNR) in wireless channels, and the impairments in the physical layer such as time varying phase noise (PHN), and carrier frequency offset (CFO). In response to these challenges, this thesis seeks to develop efficient 3-D video transmission methods and signal processing algorithms that can overcome the effects of error-prone wireless channels and impairments in the physical layer. In the first part of the thesis, an efficient unequal error protection (UEP) scheme, called video packet partitioning, and a new 3-D video transceiver structure are proposed. The proposed video transceiver uses switching operations between various UEP schemes based on the packet partitioning to achieve a trade- off between system complexity and performance. Experimental results show that the proposed system achieves significantly high video quality at different SNRs with the lowest possible bandwidth and system complexity compared to direct transmission schemes. The second part of the thesis proposes a new approach to joint source-channel coding (JSCC) that simultaneously assigns source code rates, the number of high and low priority packets, and channel code rates for the application, network, and physical layers, respectively. The proposed JSCC algorithm takes into account the rate budget constraint and the available instantaneous SNR of the best relay selection in cooperative systems. Experimental results show that the proposed JSCC algorithm outperforms existing algorithms in terms of peak signal-to-noise ratio (PSNR). In the third part of the thesis, a computationally efficient training based approach for joint channel, CFO, and PHN estimation in OFDM systems is pro- posed. The proposed estimator is based on an expectation conditional maximization (ECM) algorithm. To compare the estimation accuracy of the proposed estimator, the hybrid Cram´er-Rao lower bound (HCRB) of hybrid parameters of interest is derived. Next, to detect the signal in the presence of PHN, an iterative receiver based on the extended Kalman filter (EKF) for joint data detection and PHN mitigation is proposed. It is demonstrated by numerical simulations that, compared to existing algorithms, the performance of the proposed ECM-based estimator in terms of the mean square error (MSE) is closer to the derived HCRB and outperforms the existing estimation algorithms at moderate-to-high SNRs. Finally, this study extends the research on joint channel, PHN, and CFO estimation one step forward from OFDM systems to cooperative OFDM systems. An iterative algorithm based on the ECM in cooperative OFDM networks in the presence of unknown channel gains, PHNs and CFOs is applied. Moreover, the HCRB for the joint estimation problem in both decode-and-forward (DF) and amplify-and-forward (AF) relay systems is presented. An iterative algorithm based on the EKF for data detection and tracking the unknown time-varying PHN throughout the OFDM data packet is also used. For more efficient 3-D video transmission, the estimation algorithms and UEP schemes based packet portioning were combined to achieve a more robust video bit stream in the presence of PHNs. Applying this combination, simulation results demonstrate that promising bit-error-rate (BER) and PSNR performance can be achieved at the destination at different SNRs and PHN variance. The proposed schemes and algorithms offer solutions for existing problems in the techniques for applications to 3-D video transmission

Scalable Multiple Description Coding and Distributed Video Streaming over 3G Mobile Networks

In this thesis, a novel Scalable Multiple Description Coding (SMDC) framework is proposed. To address the bandwidth fluctuation, packet loss and heterogeneity problems in the wireless networks and further enhance the error resilience tools in Moving Pictures Experts Group 4 (MPEG-4), the joint design of layered coding (LC) and multiple description coding (MDC) is explored. It leverages a proposed distributed multimedia delivery mobile network (D-MDMN) to provide path diversity to combat streaming video outage due to handoff in Universal Mobile Telecommunications System (UMTS). The corresponding intra-RAN (Radio Access Network) handoff and inter-RAN handoff procedures in D-MDMN are studied in details, which employ the principle of video stream re-establishing to replace the principle of data forwarding in UMTS. Furthermore, a new IP (Internet Protocol) Differentiated Services (DiffServ) video marking algorithm is proposed to support the unequal error protection (UEP) of LC components of SMDC. Performance evaluation is carried through simulation using OPNET Modeler 9. 0. Simulation results show that the proposed handoff procedures in D-MDMN have better performance in terms of handoff latency, end-to-end delay and handoff scalability than that in UMTS. Performance evaluation of our proposed IP DiffServ video marking algorithm is also undertaken, which shows that it is more suitable for video streaming in IP mobile networks compared with the previously proposed DiffServ video marking algorithm (DVMA)

Machine Learning for Multimedia Communications

Machine learning is revolutionizing the way multimedia information is processed and transmitted to users. After intensive and powerful training, some impressive efficiency/accuracy improvements have been made all over the transmission pipeline. For example, the high model capacity of the learning-based architectures enables us to accurately model the image and video behavior such that tremendous compression gains can be achieved. Similarly, error concealment, streaming strategy or even user perception modeling have widely benefited from the recent learningoriented developments. However, learning-based algorithms often imply drastic changes to the way data are represented or consumed, meaning that the overall pipeline can be affected even though a subpart of it is optimized. In this paper, we review the recent major advances that have been proposed all across the transmission chain, and we discuss their potential impact and the research challenges that they raise

Network streaming and compression for mixed reality tele-immersion

Bulterman, D.C.A. [Promotor]Cesar, P.S. [Copromotor

Combined Industry, Space and Earth Science Data Compression Workshop

The sixth annual Space and Earth Science Data Compression Workshop and the third annual Data Compression Industry Workshop were held as a single combined workshop. The workshop was held April 4, 1996 in Snowbird, Utah in conjunction with the 1996 IEEE Data Compression Conference, which was held at the same location March 31 - April 3, 1996. The Space and Earth Science Data Compression sessions seek to explore opportunities for data compression to enhance the collection, analysis, and retrieval of space and earth science data. Of particular interest is data compression research that is integrated into, or has the potential to be integrated into, a particular space or earth science data information system. Preference is given to data compression research that takes into account the scien- tist's data requirements, and the constraints imposed by the data collection, transmission, distribution and archival systems

Exposing a waveform interface to the wireless channel for scalable video broadcast

Thesis (Ph. D.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.Cataloged from PDF version of thesis.Includes bibliographical references (p. 157-167).Video broadcast and mobile video challenge the conventional wireless design. In broadcast and mobile scenarios the bit-rate supported by the channel differs across receivers and varies quickly over time. The conventional design however forces the source to pick a single bit-rate and degrades sharply when the channel cannot support it. This thesis presents SoftCast, a clean-slate design for wireless video where the source transmits one video stream that each receiver decodes to a video quality commensurate with its specific instantaneous channel quality. To do so, SoftCast ensures the samples of the digital video signal transmitted on the channel are linearly related to the pixels' luminance. Thus, when channel noise perturbs the transmitted signal samples, the perturbation naturally translates into approximation in the original video pixels. Hence, a receiver with a good channel (low noise) obtains a high fidelity video, and a receiver with a bad channel (high noise) obtains a low fidelity video. SoftCast's linear design in essence resembles the traditional analog approach to communication, which was abandoned in most major communication systems, as it does not enjoy the theoretical opimality of the digital separate design in point-topoint channels nor its effectiveness at compressing the source data. In this thesis, I show that in combination with decorrelating transforms common to modern digital video compression, the analog approach can achieve performance competitive with the prevalent digital design for a wide variety of practical point-to-point scenarios, and outperforms it in the broadcast and mobile scenarios. Since the conventional bit-pipe interface of the wireless physical layer (PHY) forces the separation of source and channel coding, to realize SoftCast, architectural changes to the wireless PHY are necessary. This thesis discusses the design of RawPHY, a reorganization of the PHY which exposes a waveform interface to the channel while shielding the designers of the higher layers from much of the perplexity of the wireless channel. I implement SoftCast and RawPHY using the GNURadio software and the USRP platform. Results from a 20-node testbed show that SoftCast improves the average video quality (i.e., PSNR) across diverse broadcast receivers in our testbed by up to 5.5 dB in comparison to conventional single- or multi-layer video. Even for a single receiver, it eliminates video glitches caused by mobility and increases robustness to packet loss by an order of magnitude.by Szymon Kazimierz Jakubczak.Ph.D

Low-complexity video coding for receiver-driven layered multicast

In recent years, the “Internet Multicast Backbone,” or MBone, has risen from a small, research curiosity to a large- scale and widely used communications infrastructure. A driving force behind this growth was the development of multipoint audio, video, and shared whiteboard conferencing applications. Because these real-time media are transmitted at a uniform rate to all of the receivers in the network, a source must either run at the bottleneck rate or overload portions of its multicast distribution tree. We overcome this limitation by moving the burden of rate adaptation from the source to the receivers with a scheme we call receiver-driven layered multicast, or RLM. In RLM, a source distributes a hierarchical signal by striping the different layers across multiple multicast groups, and receivers adjust their reception rate by simply joining and leaving multicast groups. In this paper, we describe a layered video compression algorithm which, when combined with RLM, provides a comprehensive solution for scalable multicast video transmission in heterogeneous networks. In addition to a layered representation, our coder has low complexity (admitting an effi- cient software implementation) and high loss resilience (admitting robust operation in loosely controlled environments like the Inter- net). Even with these constraints, our hybrid DCT/wavelet-based coder exhibits good compression performance. It outperforms all publicly available Internet video codecs while maintaining comparable run-time performance. We have implemented our coder in a “real” application—the UCB/LBL videoconferencing tool vic. Unlike previous work on layered video compression and transmission, we have built a fully operational system that is currently being deployed on a very large scale over the MBone