Random Linear Network Coding for Wireless Layered Video Broadcast: General Design Methods for Adaptive Feedback-free Transmission

This paper studies the problem of broadcasting layered video streams over heterogeneous single-hop wireless networks using feedback-free random linear network coding (RLNC). We combine RLNC with unequal error protection (UEP) and our main purpose is twofold. First, to systematically investigate the benefits of UEP+RLNC layered approach in servicing users with different reception capabilities. Second, to study the effect of not using feedback, by comparing feedback-free schemes with idealistic full-feedback schemes. To these ends, we study `expected percentage of decoded frames' as a key content-independent performance metric and propose a general framework for calculation of this metric, which can highlight the effect of key system, video and channel parameters. We study the effect of number of layers and propose a scheme that selects the optimum number of layers adaptively to achieve the highest performance. Assessing the proposed schemes with real H.264 test streams, the trade-offs among the users' performances are discussed and the gain of adaptive selection of number of layers to improve the trade-offs is shown. Furthermore, it is observed that the performance gap between the proposed feedback-free scheme and the idealistic scheme is very small and the adaptive selection of number of video layers further closes the gap.Comment: 15 pages, 12 figures, 3 tables, Under 2nd round of review, IEEE Transactions on Communication

Historical information aware unequal error protection of scalable HEVC/H.265 streaming over free space optical channels

Free space optical (FSO) systems are capable of supporting high data rates between fixed points in the context of flawless video communications. Layered video coding facilitates the creation of different-resolution subset layers for variablethroughput transmission scenarios. In this paper, we propose Historical information Aware Unequal Error Protection (HAUEP) for the scalable high efficiency video codec (SHVC) used for streaming over FSO channels. Specifically, the objective function (OF) of the current video frame is designed based on historical information of its dependent frames. By optimizing this OF, specific subset layers may be selected in conjunction with carefully selected forward error correction (FEC) coding rates, where the expected video distortion is minimized and the required bitrate is reduced under the constraint of a specific throughput. Our simulation results show that the proposed system outperforms the traditional equal error protection (EEP) scheme by about 4.5 dB of Eb=N0 at a peak signal-to-noise ratio (PSNR) of 33 dB. From a throughput-oriented perspective, HA-UEP is capable of reducing the throughput to about 30% compared to that of the EEP benchmarker, while achieving an Eb=N0 gain of 4.5 dB

Wireless holographic image communications relying on unequal error protected bitplanes

Holography is considered to be one of the most promising techniques of goggle-free visualization of the nearfuture. We consider wireless transmission of digital holograms, which are partitioned into multiple bitplanes that are then independently encoded by a forward error correction (FEC) code for transmission over wireless channels. The coding rates of these bitplanes will be optimized at the transmitter for the sake of achieving an improved holographic peak signal-to-noise ratio (PSNR) at the receiver. Our simulation results show that up to 2.6 dB of Eb=N0 or 12.5 dB of PSNR improvements may be achieved, when employing a recursive systematic convolutional (RSC) code

GRACE: Loss-Resilient Real-Time Video through Neural Codecs

In real-time video communication, retransmitting lost packets over high-latency networks is not viable due to strict latency requirements. To counter packet losses without retransmission, two primary strategies are employed -- encoder-based forward error correction (FEC) and decoder-based error concealment. The former encodes data with redundancy before transmission, yet determining the optimal redundancy level in advance proves challenging. The latter reconstructs video from partially received frames, but dividing a frame into independently coded partitions inherently compromises compression efficiency, and the lost information cannot be effectively recovered by the decoder without adapting the encoder. We present a loss-resilient real-time video system called GRACE, which preserves the user's quality of experience (QoE) across a wide range of packet losses through a new neural video codec. Central to GRACE's enhanced loss resilience is its joint training of the neural encoder and decoder under a spectrum of simulated packet losses. In lossless scenarios, GRACE achieves video quality on par with conventional codecs (e.g., H.265). As the loss rate escalates, GRACE exhibits a more graceful, less pronounced decline in quality, consistently outperforming other loss-resilient schemes. Through extensive evaluation on various videos and real network traces, we demonstrate that GRACE reduces undecodable frames by 95% and stall duration by 90% compared with FEC, while markedly boosting video quality over error concealment methods. In a user study with 240 crowdsourced participants and 960 subjective ratings, GRACE registers a 38% higher mean opinion score (MOS) than other baselines

Efficient and Effective Schemes for Streaming Media Delivery

The rapid expansion of the Internet and the increasingly wide deployment of wireless networks provide opportunities to deliver streaming media content to users at anywhere, anytime. To ensure good user experience, it is important to battle adversary effects, such as delay, loss and jitter. In this thesis, we first study efficient loss recovery schemes, which require pure XOR operations. In particular, we propose a novel scheme capable of recovering up to 3 packet losses, and it has the lowest complexity among all known schemes. We also propose an efficient algorithm for array codes decoding, which achieves significant throughput gain and energy savings over conventional codes. We believe these schemes are applicable to streaming applications, especially in wireless environments. We then study quality adaptation schemes for client buffer management. Our control-theoretic approach results in an efficient online rate control algorithm with analytically tractable performance. Extensive experimental results show that three goals are achieved: fast startup, continuous playback in the face of severe congestion, and maximal quality and smoothness over the entire streaming session. The scheme is later extended to streaming with limited quality levels, which is then directly applicable to existing systems