Showing papers in "IEEE Transactions on Broadcasting in 2018"

Blind Image Quality Estimation via Distortion Aggravation

Abstract: Traditional blind image quality assessment (IQA) measures generally predict quality from a sole distorted image directly. In this paper, we first introduce multiple pseudo reference images (MPRIs) by further degrading the distorted image in several ways and to certain degrees, and then compare the similarities between the distorted image and the MPRIs. Via such distortion aggravation, we can have some references to compare with, i.e., the MPRIs, and utilize the full-reference IQA framework to compute the quality. Specifically, we apply four types and five levels of distortion aggravation to deal with the commonly encountered distortions. Local binary pattern features are extracted to describe the similarities between the distorted image and the MPRIs. The similarity scores are then utilized to estimate the overall quality. More similar to a specific pseudo reference image (PRI) indicates closer quality to this PRI. Owning to the availability of the created multiple PRIs, we can reduce the influence of image content, and infer the image quality more accurately and consistently. Validation is conducted on four mainstream natural scene image and screen content image quality assessment databases, and the proposed method is comparable to or outperforms the state-of-the-art blind IQA measures. The MATLAB source code of the proposed measure will be publicly available.

Radio Resource Management Optimization of Flexible Satellite Payloads for DVB-S2 Systems

Abstract: The increasing demand for high-rate broadcast and multicast services over satellite networks has pushed for the development of high throughput satellites characterized by a large number of beams (e.g., more than 100). This, together with the variable distribution of data traffic request across beams and over time, has called for the design of a new generation of satellite payloads, able to flexibly allocate bandwidth and power. In this context, this paper studies the problem of radio resource allocation in the forward link of multibeam satellite networks adopting the digital video broadcasting-satellite-second generation standard. We propose a novel objective function with the aim to meet as close as possible the requested traffic across the beams while taking fairness into account. The resulting non-convex optimization problem is solved using a modified version of the simulated annealing algorithm, for which a detailed complexity analysis is presented. Simulation results obtained under realistic conditions confirm the effectiveness of the proposed approach and shed some light on possible payload design implications.

5G-QoE: QoE Modelling for Ultra-HD Video Streaming in 5G Networks

Abstract: Traffic on future fifth-generation (5G) mobile networks is predicted to be dominated by challenging video applications such as mobile broadcasting, remote surgery and augmented reality, demanding real-time, and ultra-high quality delivery. Two of the main expectations of 5G networks are that they will be able to handle ultra-high-definition (UHD) video streaming and that they will deliver services that meet the requirements of the end user’s perceived quality by adopting quality of experience (QoE) aware network management approaches. This paper proposes a 5G-QoE framework to address the QoE modeling for UHD video flows in 5G networks. Particularly, it focuses on providing a QoE prediction model that is both sufficiently accurate and of low enough complexity to be employed as a continuous real-time indicator of the “health” of video application flows at the scale required in future 5G networks. The model has been developed and implemented as part of the EU 5G PPP SELFNET autonomic management framework, where it provides a primary indicator of the likely perceptual quality of UHD video application flows traversing a realistic multi-tenanted 5G mobile edge network testbed. The proposed 5G-QoE framework has been implemented in the 5G testbed, and the high accuracy of QoE prediction has been validated through comparing the predicted QoE values with not only subjective testing results but also empirical measurements in the testbed. As such, 5G-QoE would enable a holistic video flow self-optimisation system employing the cutting-edge Scalable H.265 video encoding to transmit UHD video applications in a QoE-aware manner.

A Quality-of-Experience Database for Adaptive Video Streaming

Abstract: The dynamic adaptive streaming over HTTP provides an inter-operable solution to overcome the volatile network conditions, but its complex characteristic brings new challenges to objective video quality-of-experience (QoE) measurement. To test the generalizability and to facilitate the wide usage of QoE measurement techniques in real-world applications, we establish a new database named Waterloo Streaming QoE Database III (SQoE-III). Unlike existing databases constructed with hand-crafted test sequences, the SQoE-III database, so far the largest and most realistic of its kind, consists of a total of 450 streaming videos created from diverse source content and diverse distortion patterns, with six adaptation algorithms of diverse characteristics under 13 representative network conditions. All streaming videos are assessed by 34 subjects, and a comprehensive evaluation is conducted on the performance of 15 objective QoE models from four categories with regards to their efficacy in predicting subjective QoE. Detailed correlation analysis and statistical hypothesis testing are carried out. The results of this paper shed light on the future development of adaptive bitrate streaming algorithm and video QoE monitoring system. The subjective database is available online at https://ece.uwaterloo.ca/~zduanmu/tbc2018qoe/ .

Network Resource Allocation System for QoE-Aware Delivery of Media Services in 5G Networks

Abstract: The explosion in the variety and volume of video services makes bandwidth and latency performance of networks more critical to the user experience. The media industry’s response, HTTP-based Adaptive Streaming technology, offers media players the possibility to dynamically select the most appropriate bitrate according to the connectivity performance. Moving forward, the telecom industry’s move is 5G. 5G aims efficiency by dynamic network optimization to make maximum use of the resources to get as high capacity and Quality of Service (QoS) as possible. These networks will be based on software defined networking (SDN) and network function virtualization (NFV) techniques, enabling self-management functions. Here, machine learning is a key technology to reach this 5G vision. On top of machine learning, SDN and NFV, this paper provides a network resource allocator system as the main contribution which enables autonomous network management aware of quality of experience (QoE). This system predicts demand to foresee the amount of network resources to be allocated and the topology setup required to cope with the traffic demand. Furthermore, the system dynamically provisions the network topology in a proactive way, while keeping the network operation within QoS ranges. To this end, the system processes signals from multiple network nodes and end-to-end QoS and QoE metrics. This paper evaluates the system for live and on-demand dynamic adaptive streaming over HTTP and high efficiency video coding services. From the experiment results, it is concluded that the system is able to scale the network topology and to address the level of resource efficiency, required by media streaming services.

Subjective Panoramic Video Quality Assessment Database for Coding Applications

Abstract: With the development of virtual reality, higher quality panoramic videos are in great demand to guarantee the immersive viewing experience. Therefore, quality assessment attaches much importance to correlated technologies. Considering the geometric transformation in projection and the limited resolution of head-mounted device (HMD), a modified display protocol of the high resolution sequences for the subjective rating test is proposed, in which an optimal display resolution is determined based on the geometry constraints between screen and human eyes. By sampling the videos to the optimal resolution before coding, the proposed method significantly alleviates the interference of HMD sampling while displaying, thus ensuring the reliability of subjective quality opinion in terms of video coding. Using the proposed display protocol, a subjective quality database for panoramic videos is established for video coding applications. The proposed database contains 50 distorted sequences obtained from ten raw panoramic video sequences. Distortions are introduced with the High Efficiency Video Coding compression. Each sequence is evaluated by 30 subjects on video quality, following the absolute category rating with hidden reference method. The rating scores and differential mean opinion scores (DMOSs) are recorded and included in the database. With the proposed database, several state-of-the-art objective quality assessment methods are further evaluated with correlation analysis. The database, including the video sequences, subjective rating scores and DMOS, can be used to facilitate future researches on coding applications.

Buffer State is Enough: Simplifying the Design of QoE-Aware HTTP Adaptive Video Streaming

Abstract: Recently, the prevalence of mobile devices together with the outburst of user-generated contents has fueled the tremendous growth of the Internet traffic taken by video streaming. To improve user-perceived quality-of-experience (QoE), dynamic adaptive streaming via HTTP (DASH) has been widely adopted by practical systems to make streaming smooth under limited bandwidth. However, previous DASH approaches mostly performed complicated rate adaptation based on bandwidth estimation, which has been proven to be unreliable over HTTP. In this paper, we simplify the design by only exploiting client-side buffer state information and propose a pure buffer-based DASH scheme to optimize user QoE. Our approach can not only get rid of the drawback caused by inaccurate bandwidth estimation, but also incur very limited overhead. We explicitly define an integrated user QoE model, which takes playback freezing, bitrate switch, and video quality into account, and then formulate the problem into a non-linear stochastic optimal control problem. Next, we utilize control theory to design a dynamic buffer-based controller for DASH, which determines video bitrate of each chunk to be requested and stabilize the buffer level in the meanwhile. Extensive experiments have been conducted to validate the advantages of our approach, and the results show that our approach can achieve the best performance compared with other alternative approaches.

A Review of Predictive Quality of Experience Management in Video Streaming Services

Abstract: Satisfying the requirements of devices and users of online video streaming services is a challenging task. It requires not only managing the network quality of service but also to exert real-time control, addressing the user’s quality of experience (QoE) expectations. QoE management is an end-to-end process that, due to the ever-increasing variety of video services, has become too complex for conventional “reactive” techniques. Herein, we review the most significant “predictive” QoE management methods for video streaming services, showing how different machine learning approaches may be used to perform proactive control. We pinpoint a selection of the best suited machine learning methods, highlighting advantages and limitations in specific service conditions. The review leads to lessons learned and guidelines to better address QoE requirements in complex video services.

Fuzzy SVM-Based Coding Unit Decision in HEVC

Abstract: The latest video compression standard, High Efficiency Video Coding (HEVC), has greatly improved the coding efficiency compared to the predecessor H.264/AVC. However, equipped with the quadtree structure of coding tree unit partition and other sophisticated coding tools, HEVC brings a significant increase in the computational complexity. To address this issue, a coding unit (CU) decision method based on fuzzy support vector machine (SVM) is proposed for rate-distortion-complexity (RDC) optimization, where the process of CU decision is formulated as a cascaded multi-level classification task. The optimal feature set is selected according to a defined misclassification cost and a risk area is introduced for an uncertain classification output. To further improve the RDC performance, different regulation parameters in SVM are adopted and outliers in training samples are eliminated. Additionally, the proposed CU decision method is incorporated into a joint RDC optimization framework, where the width of risk area is adaptively adjusted to allocate flexible computational complexity to different CUs, aiming at minimizing computational complexity under a configurable constraint in terms of RD performance degradation. Experimental results show that the proposed approach can reduce 58.9% and 55.3% computational complexity on average with the values of Bjonteggard delta peak-signal-to-noise ratio as −0.075 dB and −0.085 dB and the values of Bjontegaard delta bit rate as 2.859% and 2.671% under low delay ${P}$ and random access configurations, respectively, which has outperformed the state-of-the-art fast algorithms based on statistical information and machine learning.

Evaluation of the Concept of Dynamic Adaptive Streaming of Light Field Video

Abstract: Light field visualization has progressed and developed significantly in the past years. At the time of this paper, light field displays are utilized in the industry and they are commercially available as well. Although their appearance on the consumer market is approaching, many potential applications of light field technology have not yet been addressed, such as video streaming. In this paper, we present our research on the dynamic adaptive streaming of light field video. In order to evaluate the presented concept of quality switching, we carried out a series of subjective tests, where test participants were shown light field videos containing stallings and switches in spatial and angular resolution.

QoE Assessment for IoT-Based Multi Sensorial Media Broadcasting

Abstract: One of the goals of next generation TV broadcast services is to provide realistic media contents to the users. The user’s sense of reality can be reinforced by adding to conventional media multiple sensorial effects, through five-sense stimulus (i.e., taste, sight, touch, smell, and hearing). In a smart TV broadcasting context, especially in a home environment, to deliver the additional effects, customary devices (e.g., air conditioning, lights, etc.), provided of opportune smart features, have to be preferred to ad-hoc devices, often deployed in other applications as for example in gaming systems. In this context, a key issue is the interconnection among the smart TV and the customary devices that deliver the additional sensorial effects to the user. In smart home use cases, the Internet of Things (IoT) paradigm has been widely adopted to connect smart devices and this paper presents an IoT-based architecture for multi sensorial media delivery to TV users in a home entertainment scenario. In such a framework, home customary devices, act as smart objects interconnected via IoT network to the smart TV and play a role to implement additional effects to the conventional broadcast TV service. In this paper, the requirements in terms of synchronization between media and devices is analyzed and the architecture of the system is defined accordingly. Furthermore, a prototype is implemented in a real smart home scenario with real customary devices, which allowed a subjective test measurement campaign to assess the quality of experience of the users and the feasibility of the proposed multi sensorial media TV service.

E 3 DOAS: Balancing QoE and Energy-Saving for Multi-Device Adaptation in Future Mobile Wireless Video Delivery

Abstract: Smart devices (e.g., smartphones, tablets, smart-home devices, etc.) have become important companions to most people in their daily activities, and are very much used for multimedia content exchange (i.e., video sharing, real-time/non-real-time multimedia streaming), contributing to the exponential increase in mobile traffic over the current wireless networks. While the next generation mobile networks will provide higher capacity than the current 4G systems, the network operators will face important challenges associated with the outstanding increase of both video traffic and user expectations in terms of their levels of perceived quality or quality of experience (QoE). Furthermore, the heterogeneity of mobile devices (e.g., screen resolution, battery life, and hardware performance) also impacts severely the end-user QoE. In this context, this paper proposes an evolved QoE-aware energy-saving device-oriented adaptive scheme (E3DOAS) for mobile multimedia delivery over future wireless networks. E3DOAS makes use of a coalition game-based rate allocation strategy within the multi-device heterogeneous environment, and optimizes the trade-off between the end-user perceived quality of the multimedia delivery and the mobile device energy-saving. Testing has involved a prototype of E3DOAS, a crowd-sourcing-based QoE assessment method to model non-reference perceptual video quality, and an energy measurement testbed introduced to collect power consumption parameters of the mobile devices. Simulation-based performance evaluation showed how E3DOAS outperformed other state of the art multimedia adaptive solutions in terms of energy saving, end-to-end quality of service metrics and end-user perceived quality.

Hybrid Broadcast/Broadband TV Services and Media Synchronization: Demands, Preferences and Expectations of Spanish Consumers

Abstract: The combination of broadcast and broadband (hybrid) technologies for delivering TV related media contents is already a reality. It has been motivated by the large amount and diversity of media contents, together with the ubiquity and multiple connectivity capabilities of modern consumption devices. The use of connected TVs and companion devices (e.g., tablets, smartphones etc.) is gaining momentum. It enables personalized and enriched TV media experiences, by also exploiting social communication opportunities. Likewise, the media consumption paradigm is worldwide evolving from passive and isolated consumer experiences toward interactive and group shared experiences between remote consumers. Nevertheless, despite the specification of standards, such as hybrid broadcast broadband TV, and the efforts from operators and content providers in the last years, the adoption of hybrid TV media services in Europe is still not as high as expected. This paper presents the concept and some examples of hybrid TV media services , emphasizing the importance of including a combination of media synchronization solutions, known as hybrid sync , to guarantee a satisfactory level of quality of experience. Additionally, it includes the summary and discussion of the results of a research study focused on more than 1000 Spanish users’ habits, preferences, and expectations regarding four representative hybrid TV media services. Many valuable insights and conclusions have been derived. For instance, the current low market adoption of hybrid TV media services, despite their advantages and the high interest of consumers, and that key technological challenges still need to be overcome. The obtained results and impressions foresee the impact (or potential) of such services in the upcoming TV related media consumption landscape. Therefore, devising proper standard-compliant technological solutions (paying special attention to hybrid sync) and equipment should be continued producing appropriate contents, deploying proper hybrid TV media services and applications. As well, it should be convenient to undertake marketing and commercial efforts to boost their deployment. The contributions of this paper can be very valuable to the interested agents to be aware of the remaining challenges, envisage the opportunities, and drive their efforts to maximize the market adoption of such services.

Efficient No-Reference Quality Assessment and Classification Model for Contrast Distorted Images

Abstract: In this paper, an efficient Minkowski distance-based metric for no-reference (NR) quality assessment of contrast distorted images is proposed. It is shown that higher orders of Minkowski distance and entropy provide accurate quality prediction for the contrast distorted images. The proposed metric performs predictions by extracting only three features from the distorted images followed by a regression analysis. Furthermore, the proposed features are able to classify type of the contrast distorted images with a high accuracy. Experimental results on four datasets CSIQ, TID2013, CCID2014, and SIQAD show that the proposed metric with a very low complexity provides better quality predictions than the state-of-the-art NR metrics. The MATLAB source code of the proposed metric is available to public at http://www.synchromedia.ca/system/files/MDM.zip .

Toward a Blind Quality Metric for Temporally Distorted Streaming Video

Abstract: With the rapid progress of mobile Internet, the streaming video service has boom over wireless networks in recent years. A smooth playback experience is crucial for the popularization of these services. However, limited by fluctuating bandwidth and various network impairments, the streaming video inevitably suffers kinds of stalling events, which significantly distorts its temporal structures and results in annoying jerky playback. In this paper, we propose an efficient quality metric to blindly evaluate the user experience for stalled streaming video without using its original sequence. Instead of requiring buffer or manifest information like existing methods, we only access to the decoded video and extract two complementary image features, i.e., global intensity and local texture, to estimate the stall number and duration. Then, by means of a straightforward and easy-to-use linear combination model, we can map the normalized stall number and duration information to a quantitative quality score. Experimental results on the publicly available LIVE-Avvasi mobile video database show that our predicted video quality is highly consistent with the user experience and outperforms many existing quality-of-experience models.

A Constrained Optimization Approach to Compander Design for OFDM PAPR Reduction

Abstract: In this paper, we derive new multi-component companders for reducing peak-to-average power ratio (PAPR) in orthogonal frequency-division multiplexing signals, using a constrained optimization approach. The new companders provide out-of-band power rejection performance improvements over current state-of-the art companders, while maintaining comparable demodulation performance. The newly designed companders are derived by minimally perturbing the Rayleigh signal amplitude distribution, while enforcing the constant power and probability density function constraints. The use of a multi-component approach to compander construction provides design flexibility, and expands the space of tradeoffs between demodulation performance, PAPR reduction, and out-of-band power rejection. Furthermore, the new companders provide solutions in operating regions where certain current companders fail to exist due to violation of one or more constraints; for example, solutions may be derived for cutoff amplitude values that are unobtainable using other companders. We formulate the constrained optimization problem for compander design and derive the compander and decompander forms. Through numerical simulation, we generate performance results demonstrating the capability of the new companders.

No Reference Quality Assessment of Stereo Video Based on Saliency and Sparsity

Abstract: With the popularity of video technology, stereoscopic video quality assessment (SVQA) has become increasingly important. Existing SVQA methods cannot achieve good performance because the videos’ information is not fully utilized. In this paper, we consider various information in the videos together, construct a simple model to combine and analyze the diverse features, which is based on saliency and sparsity. First, we utilize the 3-D saliency map of sum map, which remains the basic information of stereoscopic video, as a valid tool to evaluate the videos’ quality. Second, we use the sparse representation to decompose the sum map of 3-D saliency into coefficients, then calculate the features based on sparse coefficients to obtain the effective expression of videos’ message. Next, in order to reduce the relevance between the features, we put them into stacked auto-encoder, mapping vectors to higher dimensional space, and adding the sparse restraint, then input them into support vector machine subsequently, and finally, get the quality assessment scores. Within that process, we take the advantage of saliency and sparsity to extract and simplify features. Through the later experiment, we can see the proposed method is fitting well with the subjective scores.

On Improving Video Streaming Efficiency, Fairness, Stability, and Convergence Time Through Client–Server Cooperation

Abstract: Many studies have shown that the dynamic adaptive streaming over HTTP scheme is limited in achieving efficiency, fairness, and stability. Solutions proposed in the recent literature target these objectives, but tackle them from either client or server side separately. This paper argues the use of a client–server cooperation-based approach to achieve the three objectives. Effectively, information available at the client side, such as buffer occupancy, available throughput, and previous played representation levels, can be used to better control the video streaming efficiency and stability at the client side. On the other hand, information available at the server side, such as the server’s shared bandwidth capacity, and the number of connected clients and their corresponding downloading bitrates, can be leveraged to better tune the system fairness at the server side. Furthermore, the envisioned client–server cooperation aims at shortening the convergence time of the different clients to the fair bitrate allocation without affecting the overall system smoothness while increasing or decreasing the bitrates. The proposed approach is evaluated through extensive simulations using the Network Simulator, NS-3. Its performance is compared against that of notable algorithms, such as the FESTIVE [1] and PANDA [2] schemes. The obtained results show that the cooperation between the client and the server defines a promising approach in enhancing the efficiency, the fairness, the stability as well as shortening the convergence time to the fair bandwidth share.

An Optimized Hybrid Unicast/Multicast Adaptive Video Streaming Scheme Over MBMS-Enabled Wireless Networks

Abstract: Mobile multimedia services have been increasingly popular. However, radio resources are limited. The quality of experience of all users in wireless networks can be enriched by resource allocation, which is affected by many factors in current wireless networks. In this paper, we focus on a hybrid unicast-multicast (HUM) video streaming scheme, and develop an adaptive resource allocation framework for HUM by combining adaptive cooperative transmission and base station handoff. The optimization problem is formulated as a multi-dimensional, complexity-constrained nonlinear NP-hard problem. To solve the problem, a greedy algorithm and a genetic algorithm are proposed. Simulation results demonstrate that our scheme has superior performance than other transmission methods in the literature. The genetic algorithm has better performance, but the greedy algorithm can maintain better balance between performance and resource consumption.

Quality of Experience for 3-D Immersive Media Streaming

Abstract: Recent advances in media capture and processing technologies have enabled new forms of true 3-D media content that increase the degree of user immersion. The demand for more engaging forms of entertainment means that content distributors and broadcasters need to fine-tune their delivery mechanisms over the Internet as well as develop new models for quantifying and predicting user experience of these new forms of content. In the work described in this paper, we undertake one of the first studies into the quality of experience (QoE) of real-time 3-D media content streamed to virtual reality (VR) headsets for entertainment purposes, in the context of game spectating. Our focus is on tele-immersive media that embed real users within virtual environments of interactive games. A key feature of engaging and realistic experiences in full 3-D media environments, is allowing users unrestricted viewpoints. However, this comes at the cost of increased network bandwidth and the need of limiting network effects in order to transmit a realistic, real-time representation of the participants. The visual quality of 3-D media is affected by geometry and texture parameters while the temporal aspects of smooth movement and synchronization are affected by lag introduced by network transmission effects. In this paper, we investigate varying network conditions for a set of tele-immersive media sessions produced in a range of visual quality levels. Further, we investigate user navigation issues that inhibit free viewpoint VR spectating of live 3-D media. After reporting on a study with multiple users we analyze the results and assess the overall QoE with respect to a range of visual quality and latency parameters. We propose a neural network QoE prediction model for 3-D media, constructed from a combination of visual and network parameters.

The Adjustment/Satisfaction Test (A/ST) for the Evaluation of Personalization in Broadcast Services and Its Application to Dialogue Enhancement

Abstract: Media consumption in broadcasting is heading towards high degrees of content personalization also in audio thanks to next-generation audio systems. It is thus crucial to assess the benefit of personalized media delivery. To this end, the adjustment/satisfaction test was recently proposed. This is a perceptual test where subjects interact with a user-adjustable system and their adjustments and the resulting satisfaction levels are studied. Two configurations of this test paradigm are implemented and compared for the evaluation of Dialogue Enhancement (DE). This is an advanced broadcast service which enables the personalization of the relative level of the dialog and the background sounds. The test configuration closer to the final application is found to provide less noisy data and to be more conclusive about the quality of experience. For this configuration, DE is tested both in the case in which the original audio objects are readily available and in the case in which they are estimated by blind source separation. The results show that personalization is extensively used, resulting in increased user satisfaction, in both cases.

New PTS Schemes With Adaptive Selection Methods of Dominant Time-Domain Samples in OFDM Systems

Abstract: In orthogonal frequency division multiplexing (OFDM) systems, high peak-to-average power ratio (PAPR) of OFDM signals is one of the most important problems. As a solution to the PAPR problem in OFDM systems, the partial transmit sequence (PTS) is a fairly suitable scheme due to its PAPR reduction performance and distortionless characteristic. However, high computational complexity is a serious problem in the PTS scheme. In this paper, in an effort to reduce its computational complexity, new PTS schemes are proposed using dominant time-domain samples of OFDM signals. Although the proposed PTS schemes use dominant time-domain samples in a manner similar to several existing low-complexity PTS schemes, we propose more efficient selection methods for dominant time-domain samples. The proposed PTS schemes lower the computational complexity compared to the conventional PTS schemes while achieving the optimal PAPR reduction performance.

Field Comparison Tests of LDM and TDM in ATSC 3.0

Abstract: In this paper, we present laboratory and field test results of layered division multiplexing (LDM) and time division multiplexing (TDM) technologies based on Advanced Television Systems Committee 3.0. The presented field test results include analysis in several scenarios such as rooftop, indoor, and mobile receptions. In order to provide performance comparison of the LDM and TDM technologies, reception power (field strength) and successful reception rate are measured for all the considered scenarios. For in-depth analysis in real field environment, further field measurements such as threshold of visibility, marginal (minimal) reception power, and erroneous second ratio are used for rooftop, indoor, and mobile receptions, respectively. The laboratory and field test results show that the LDM technology not only shows superior performance compared to the TDM technology in all the considered scenarios (rooftop, indoor, and mobile receptions), but also enables broadcaster to efficiently provide a variety of services (e.g., mobile, pedestrian, indoor, and stationary services) with different robustness within a single radio frequency channel.

Resilience of Video Streaming Services to Network Impairments

Abstract: When dealing with networks, performance management through conventional quality of service (QoS)-based methods becomes difficult and is often ineffective. In fact, quality emerges as an end-to-end factor, for it is particularly sensitive to the end-user perception of the overall service, i.e., the user’s quality of experience (QoE). However, the two are not independent from each other and their relationship has to be studied through metrics that go beyond the typical network parameters. To better explore the value of assessing QoE alongside QoS in high-speed, lossy networks, this paper presents an experimental methodology to understand the relation between network QoS onto service QoE, with the aim to perform a combined network-service assessment. Using video streaming services as the test-case (given their extended usage nowadays), in this paper, we provide studies on three network-impaired video-sets with the aim to provide a comprehensive evaluation of the effects of networks on video quality. First, the ReTRIeVED video set provides the means to understand the most impairing effects on networks. Furthermore, it triggered the idea to create our own sets, specialized in the most impairing conditions for 2-D and 3-D: the LIMP Video Quality Database and the 3-D-HEVC-Net Video Quality Database. Our study and methodology are meant to provide service providers with the means to pinpoint the working boundaries of their video-sets in face of different network conditions. At the same time, network operators may use our findings to predict how network control policies affect the user’s perception of the service.

Generalized Spatial Modulation-Based Multi-User and Signal Detection Scheme for Terrestrial Return Channel With NOMA

Abstract: The terrestrial return channel provides interactive services in digital television terrestrial broadcasting systems to meet various consumers’ demands around the world. The extension of non-orthogonal multiple access and generalized spatial modulation multiple-input multiple-output to the terrestrial return channel improves both the spectral and energy efficiencies of the system, but it puts forward detection challenges. In this paper, a joint user activity and signal detection scheme based on the block-sparse compressive sensing (BS-CS) method in the terrestrial return channel is proposed, in which the generalized spatial modulation technology is used. By exploiting the structure and sparsity of the multi-user generalized spatial modulation signal, we formulate the detection problem into a block-sparse recovery problem. Then a BS-CS-based detection algorithm, enhanced structured block-sparse compressive sampling matching pursuit (ESB-CoSaMP), is proposed to detect the active users and transmitted data efficiently. Moreover, the information of active antennas at each user is exploited in ESB-CoSaMP to further improve the accuracy. Simulations show that the proposed detection scheme outperforms the conventional CS and BS-CS-based schemes.

Efficient Transmission of Multiple Broadcasting Services Using LDM and SHVC

Abstract: In this paper, we present an efficient transmission method of multiple broadcasting services using layered division multiplexing (LDM) and scalable high efficiency video coding (SHVC) based on the next generation terrestrial digital broadcasting standard, advanced television systems committee 3.0. In a two-layer LDM system, each layer forms a physical layer pipe that carries base layer and enhancement layer video streams of SHVC, respectively. This combination of physical and presentation layers technologies can maximize channel utilization when multiple broadcasting services are delivered in a single radio frequency channel with different robustness and reception conditions. An intensive performance analysis is provided when the proposed combination of LDM and SHVC is compared with other approaches, such as time division multiplexing and/or high efficiency video coding simulcast broadcasting. Several performance measurements are also introduced, such as constant data rate measurement and constant quality measurement, which are used to evaluate the performance of video codecs in conjunction with different physical layer system parameters. A prototype hardware system with LDM and SHVC capable of selecting different parameter combinations is tested in the laboratory and in real field environments to verify the performance and feasibility of the proposed LDM and SHVC combination. Results show that the proposed LDM and SHVC combination provides significant gains on video service quality as well as reception robustness.

Subband CQI Feedback-Based Multicast Resource Allocation in MIMO-OFDMA Networks

Abstract: Multicast transmission is one of the key enablers toward a more spectral- and energy-efficient distribution of multimedia content in current and envisaged cellular networks. In order to ensure that all users in a multicast group are able to correctly decode the received data, most multicast techniques adopt rather conservative strategies that select a very robust modulation and coding scheme (MCS) whose characteristics are determined by the propagation conditions experienced by the worst user in the group. Obviously, this robustness comes at the prize of a low spectral efficiency. Moreover, in the specific context of wideband communication systems, the selection of the multicast MCS has often relied on the use of wideband channel quality indicators (CQIs) providing rather imprecise information regarding the potential capacity of the multicast channel. Only recently has the per-subband CQI been used to improve the spectral efficiency of the system without compromising the link robustness. However, most subband-CQI multicast schemes proposed so far rely on overpessimistic assumptions that preclude the achievement of high data rates. In this paper, novel subband CQI-based multicast strategies are proposed that, relying on the selection of more spectrally efficient transmission modes, lead to increased data rates while still being able to fulfill prescribed quality of service metrics. To this end, a constrained optimization problem is posed that seeks to maximize the data rate of the whole multicast group while ensuring that the average block error rate for all users remains below a threshold and that a minimum data rate is guaranteed for all users in the group.

HbbTV-Compliant Platform for Hybrid Media Delivery and Synchronization on Single- and Multi-Device Scenarios

Abstract: The combination of broadcast and broadband (hybrid) technologies for delivering TV related media contents can bring fascinating opportunities. It is motivated by the large amount and diversity of media contents, together with the ubiquity and multiple connectivity capabilities of modern consumption devices. This paper presents an end-to-end platform for the preparation, delivery, and synchronized consumption of related hybrid (broadcast/broadband) media contents on a single device and/or on multiple close-by devices (i.e., a multi-device scenario). It is compatible with the latest version of the Hybrid Broadcast Broadband TV (HbbTV) standard (version 2.0.1). Additionally, it provides adaptive and efficient solutions for key issues not specified in that standard, but that are necessary to successfully deploy hybrid and multi-device media services. Moreover, apart from MPEG-DASH and HTML5, which are the broadband technologies adopted by HbbTV, the platform also provides support for using HTTP Live Streaming and Real-time Transport Protocol and its companion RTP Control Protocol broadband technologies. The presented platform can provide support for many hybrid media services. In this paper, in order to evaluate it, the use case of multi-device and multi-view TV service has been selected. The results of both objective and subjective assessments have been very satisfactory, in terms of performance (stability, smooth playout, delays, and sync accuracy), usability of the platform, usefulness of its functionalities, and the awaken interest in these kinds of platforms.

Blind Reconstruction of Reed-Solomon Encoder and Interleavers Over Noisy Environment

Abstract: Blind estimation of code and interleaver parameters is useful in smart storage systems and ubiquitous communication applications such as adaptive modulation and coding, reconfigurable radio systems, non-cooperative radio systems, etc. In this paper, we analyze Reed-Solomon (RS) encoded data stream and propose blind estimation algorithms to identify RS code parameters. We also provide algorithms to estimate block interleaver parameters from RS coded and block interleaved data stream. In addition, synchronization compensation through appropriate bit/symbol positioning is integrated with the proposed code and interleaver parameter estimation algorithms. Simulation results validating the proposed algorithms are given for various test cases involving both erroneous and non-erroneous scenarios. Moreover, the accuracy of estimation of RS code and block interleaver parameters are also given with detailed inferences for different modulation schemes, codeword length, and code dimension values. It has been inferred that the accuracy of parameter estimation improves with decrease in code dimension and codeword length values of RS codes. Further, the accuracy of estimation of lower modulation order schemes is better when compared to higher modulation order schemes as expected. It has also been noted that the proposed code and interleaver parameter estimation algorithms for noisy environment consistently outperform the algorithms proposed in the prior works.

R-FFT: Function Split at IFFT/FFT in Unified LTE CRAN and Cable Access Network

Abstract: The remote-PHY (R-PHY) modular cable network for data over cable service interface specification (DOCSIS) service conducts the physical layer processing for the transmissions over the broadcast cable in a remote node. In contrast, the cloud radio access network (CRAN) for long-term evolution (LTE) cellular wireless services conducts all baseband physical layer processing in a central baseband unit and the remaining physical layer processing steps toward radio frequency (RF) transmission in remote nodes. Both DOCSIS and LTE are based on orthogonal frequency division multiplexing physical layer processing. We propose to unify cable and wireless cellular access networks by utilizing the hybrid fiber-coax (HFC) cable network infrastructure as fiber fronthaul network for cellular wireless services. For efficient operation of such a unified access network, we propose a novel remote-fast-Fourier transform (R-FFT) node that conducts the physical layer processing from the FFT module toward the RF transmission, whereby DOCSIS and LTE share a common FFT module. The frequency domain in-phase and quadrature (I/Q) symbols for both DOCSIS and LTE are transmitted over the fiber between remote node and cable headend, where the remaining physical layer processing is conducted. We further propose to cache repetitive quadrature amplitude modulation (QAM) symbols in the R-FFT node to reduce the fronthaul bitrate requirements and enable statistical multiplexing. We evaluate the fronthaul bitrate reductions achieved by R-FFT node caching, the fronthaul transmission bitrates arising from the unified DOCSIS and LTE service, and illustrate the delay implications of moving part of the cable R-PHY remote node physical layer processing to the headend. Overall, our evaluations indicate that the proposed R-FFT node can effectively support unified DOCSIS and LTE services over the HFC cable plant while substantially reducing the fronthaul bitrate requirements of the existing CRAN structures.