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

Hierarchical colour-shift-keying aided layered video streaming for the visible light downlink

Colour-shift keying (CSK) constitutes an important modulation scheme conceived for the visible light communications (VLC). The signal constellation of CSK relies on three different-color light sources invoked for information transmission. The CSK constellation has been optimized for minimizing the bit error rate, but no effort has been invested in investigating the feasibility of CSK aided unequal error protection (UEP) schemes conceived for video sources. Hence, in this treatise, we conceive a hierarchical CSK (HCSK) modulation scheme based on the traditional CSK, which is capable of generating interdependent layers of signals having different error probability, which can be readily reconfigured by changing its parameters. Furthermore, we conceived an HCSK design example for transmitting scalable video sources with the aid of a recursive systematic convolutional (RSC) code. An optimization method is conceived for enhancing the UEP and for improving the quality of the received video. Our simulation results show that the proposed optimized-UEP 16-HCSK-RSC system outperforms the traditional equal error protection scheme by ~ 1.7 dB of optical SNR at a peak signal-to-noise ratio of 37 dB, while optical SNR savings of up to 6.5 dB are attained at a lower PSNR of 36 dB

Wireless Video: An Interlayer Error-Protection-Aided Multilayer Approach

Video clips captured from realworld scenes exhibit intraframe correlation among their pixels. This correlation can be removed by applying video compression to reduce the required the storage space, transmission bandwidth, bitrate, and power. Layered video coding separates the video sequence into partitions having unequal importance, hence allowing the decoder to progressively refine the reconstructed video quality, when an increased bandwidth is available. On the other hand, compressed video signals are sensitive to channel errors. Therefore, forward error correction (FEC) must be applied when communicating over hostile wireless channels. In addition, based on the fact that the different layers have unequal importance, different-rate FEC codes may be applied to the different layers, leading to unequal error protection (UEP). We propose an interlayer (IL) FEC coding technique combined with UEP, where the lower-importance layers are used for protecting the higher-importance layers in the data-partitioned mode of H.264/advanced video coding (AVC). Explicitly, our simulation results show that the IL coded system outperforms the traditional UEP system by providing a better video quality for transmission over a wireless channel having Eb /N0 of 0 dB, when using our multifunctional multiple-input, multiple-output (MIMO) array

Resource Allocation Frameworks for Network-coded Layered Multimedia Multicast Services

The explosive growth of content-on-the-move, such as video streaming to mobile devices, has propelled research on multimedia broadcast and multicast schemes. Multi-rate transmission strategies have been proposed as a means of delivering layered services to users experiencing different downlink channel conditions. In this paper, we consider Point-to-Multipoint layered service delivery across a generic cellular system and improve it by applying different random linear network coding approaches. We derive packet error probability expressions and use them as performance metrics in the formulation of resource allocation frameworks. The aim of these frameworks is both the optimization of the transmission scheme and the minimization of the number of broadcast packets on each downlink channel, while offering service guarantees to a predetermined fraction of users. As a case of study, our proposed frameworks are then adapted to the LTE-A standard and the eMBMS technology. We focus on the delivery of a video service based on the H.264/SVC standard and demonstrate the advantages of layered network coding over multi-rate transmission. Furthermore, we establish that the choice of both the network coding technique and resource allocation method play a critical role on the network footprint, and the quality of each received video layer.Comment: IEEE Journal on Selected Areas in Communications - Special Issue on Fundamental Approaches to Network Coding in Wireless Communication Systems. To appea

Combined Source and Channel Strategies for Optimized Video Communications

ISBN 978-953-7619-70-

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