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We consider end-to-end live video streaming in mobile edge networks with fluctuating but predictable throughput. We employ scalable video coding (SVC) to adapt the bitrate of each frame to the throughput evolution in a timely manner. When streaming SVC-encoded live video, the video source should dynamically derive and configure a set of coding parameters for each upcoming chunk, which consists of a number of consecutive frames. The coding parameters quantify the throughput evolution of an upcoming chunk by providing a few bitrate options for the frames within this chunk to encode with. Unlike the majority of existing works that simply treat the coding parameters as given (i.e., taking them for granted), in this paper, we derive the coding parameters from a comprehensive mathematical modeling and optimization perspective. Our approach consists of an optimization problem that captures the fundamental trade-off in determining the coding parameters and a customized search algorithm based on the analysis of the optimization problem's solution structure. Numerical results produced by the NS-3 network simulator show that our approach outperforms the state-of-the-art benchmarks. [ABSTRACT FROM AUTHOR]

Aided by scalable video coding, multirate multicast has become a promising technique of providing differentiated quality of experience (QoE) for massive numbers of video subscribers operating in heterogeneous channel conditions. Nevertheless, due to the time-varying nature of wireless channels and the subscribers’ diverse requirements, it is challenging to dynamically control the video rate in the light of the available radio resource to achieve the best QoE. To elaborate a little further, the time scale of resource scheduling is of short-term nature, which determines the short-term video quality variation, but from a service provider's perspective the design objective is to optimize the long-term QoE for all subscribers. Despite its importance, this problem has not been considered before. Explicitly, we formulated this problem as a time-averaged stochastic optimization problem which avoids the impact of both the short-term channel quality fluctuation and that of the video bitrates, whilst maintaining both inter- and intra- group fairness. The stratified structure of the problem inspires us to decompose it into a two-phase optimization: coarse grained assignment for each user group and fine grained assignment for each subgroup. We propose an adaptive multicast algorithm based on Lyapunov's optimization theory for solving this problem, by striking a compelling trade-off between the system's utility and its queue stability. We quantify the achievable performance of our proposed solution based on realistic video traces. [ABSTRACT FROM AUTHOR]

This paper presents a novel transmission scheme to support massive machine-type communications (MTC) devices sending very short packets for Internet-of-Things (IoT) applications. The proposed scheme, termed as pilot-less one-shot (PLOS) transmission, does not require the pilot signaling. The key idea behind PLOS is to encode information into the inter-block nonzero positions and intra-block nonzero positions of a sparse vector. In the receiver, we propose a deep neural network-based scheme, referred to as deep learning-based PLOS (DL-PLOS) to recover the nonzero positions of the sparse vector. From the simulations results, we demonstrate that PLOS is effective in the short packet transmission and DL-PLOS outperforms the conventional greedy algorithms. [ABSTRACT FROM AUTHOR]

The problem of adaptive multi-user scalable layered video transmission is considered in energy harvesting (EH) aided wireless communication systems. With the goal of improving the quality of video services while providing fairness amongst the users despite the random nature of both energy harvesting and the channel quality, we formulate our Scalable Video Coding (SVC) design as a Constrained Utility Function Maximization (CUFM) problem. The proportional fairness and playback smoothness of our design is guaranteed by maximizing the log-sum of the users’ video qualities, while satisfying the battery fullness constraint and video layer (quality) fluctuation constraint. By invoking the classical Lyapunov drift based optimization technique, we further decompose the CUFM problem into two parallel subproblems, i.e., a dynamic transmission power allocation problem and a dynamic layer selection problem. By solving these two subproblems, we derive a joint power allocation and video layer selection strategy for multi-user SVC video transmission. The theoretical performance bound of the proposed solution is also presented. Numerical simulations are conducted with real H.264 SVC video traces and the experimental results demonstrate the reduced playback interruption rate and layer switching rate compared to a heuristic algorithm ProNTO. The results also illustrate a tradeoff between the system's utility function and the playback smoothness experienced by the users. [ABSTRACT FROM AUTHOR]

We investigate the near-optimal video layer placement in cache-enabled small-cell networks to provide on-demand video services with differential perceptual experiences. By employing scalable video coding, each video file is encoded into multiple layers, which are then stored in the local cache of small-cell base stations (SBSs). Based on the proposed caching scheme, we define the concept of average offloaded traffic (AOT), which quantitatively indicates the total amount of data traffic that can be sourced from the local cache of SBSs. Relying on stochastic geometry, we derive the expression for the successful transmission probability, based on which the closed form of AOT is obtained. Afterwards, under the cache size constraint of each SBS, the AOT maximization problem is formulated. Due to the NP-hard property of this integer programming problem, it is first relaxed into the convex form. Then, a greedy-strategy based heuristic algorithm is proposed, which can yield the near-optimal layer caching indicators. Numerical results validate our derivations and demonstrate that the proposed layer caching scheme outperforms the benchmark in terms of the AOT performance. [ABSTRACT FROM AUTHOR]

This paper focuses on the transmission of layered source information, such as scalable video coding, over heterogeneous cellular networks. Scalable transmission enables dynamic adaption of source information to the condition of user equipment (UE) devices and, thus, is suitable for cellular networks in which the transmission link quality substantially varies over space and time. Two novel transmission schemes are proposed, namely, layered digital transmission and layered hybrid digital–analog (LHDA) transmission. Leveraging tools from stochastic geometry, a comprehensive analysis is conducted focusing on three key performance metrics: outage probability, high-definition probability, and average distortion. The results show that both proposed transmission schemes can provide a scalable video experience for UE devices. For LHDA transmission, the optimal power allocation between digital and analog transmissions is also analyzed. When the proportion of frequency resource allocated to the femtotier exceeds a certain threshold, LHDA transmission is preferable by enabling continuous quality scalability, thus avoiding the cliff effect. [ABSTRACT FROM PUBLISHER]

The growing demand for mobile multicast services, such as Internet Protocol television (IPTV) and video streaming, requires effective radio resource management (RRM) to handle traffic with strict quality-of-service constraints over Long-Term Evolution (LTE) and beyond systems. Special care is needed to limit system performance degradation when multiple multicast streams are simultaneously transmitted. To this aim, this paper proposes an RRM policy based on a subgrouping technique for the delivery of scalable multicast video flows in a cell. Our proposal enhances the legacy multicast transmission over LTE systems by exploiting multiuser diversity and the users' channel quality feedbacks. Moreover, it is designed to take advantage of the frequency selectivity in the subgroup formation. Simulation results demonstrate the effectiveness of the proposed scheme, which outperforms existing approaches from the literature. It succeeds in achieving higher spectral efficiency and guaranteeing adequate video quality to all multicast receivers and improved quality to those with good channel conditions. [ABSTRACT FROM AUTHOR]

Scalable video coding (SVC) is a promising technology for video multicast to users with different available transmission capacities. On the other hand, adaptive modulation and coding (AMC) schemes provide an efficient way to better utilize wireless network resources. However, the resource-allocation problem to support SVC multicast over wireless relay networks is a challenging one due to the existence of relay stations (RSs). We simplify the resource-allocation problem in this paper by assuming that the modulation and coding schemes (MCSs) assigned to lower video layers have equal or better coverage area than that assigned to higher video layers at each base station (BS)/RS. We discuss the optimal solution to the simplified problem and its relation with the orienteering problem (OP). Then, we propose a tabu search (TS)-based metaheuristic algorithm for dealing with the problem, which has been proven to be an effective and efficient algorithm for OP. The simulation results reveal that the proposed algorithm outperforms other algorithms under the assumptions of two-hop wireless relay networks or separated transmissions for the relay and access links, and it maintains a good approximation to the optimal results. [ABSTRACT FROM PUBLISHER]

In conventional wireless systems with layered architectures, the physical (PHY) layer equally treats all data streams from the upper layers and applies the same modulation and coding schemes to them. Newer systems such as Digital Video Broadcast start to introduce hierarchical modulation schemes with SuperPosition Coding (SPC) and support data streams of different priorities. However, SPC requires specialized hardware and has high complexity, which is not desirable for handheld devices. In this paper, we propose scalable modulation (s-mod) by reusing the current mainstream modulation schemes with software-based bit remapping. The performance evaluation has shown that s-mod can achieve the same and, in some cases, even better performance than SPC with much lower complexity. We further propose how to optimize the configuration of the PHY-layer s-mod and coding schemes to maximize the utility of video streaming with scalable video coding (SVC). Simulation results demonstrate substantial performance gains using s-mod and cross-layer optimization, indicating that s-mod and SVC are a good combination for video transmission in wireless networks. [ABSTRACT FROM PUBLISHER]