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Recently, robust video transmission system that can eliminate the cliff effect in digital video transmission has attracted great interest from both academia and industry. By linearizing the whole system, robust video transmission is intrinsically scalable to channel conditions in mobile networks. However, the heterogeneity of user devices in terms of viewing resolution has not been well studied for robust video broadcast systems. In this paper, we propose a spatial scalability enabled robust video broadcast (SSRVB) system, aiming at accommodating diverse users with both heterogeneous resolutions and heterogeneous channel conditions. In SSRVB, a novel spatial decomposition method based on linear projection is first designed for robust video transmission. Then the transmission distortion minimization problem with joint subcarrier matching and power allocation is formulated. A near-optimal low-complexity subcarrier matching algorithm based on auction theory and an optimal power allocation strategy are also proposed. Furthermore, an iterative algorithm is designed to solve the problem of joint resource allocation. Simulation results demonstrate that SSRVB can achieve an average of 3 dB gain when compared with the reference schemes (i.e., ECast, MCast, discrete wavelet transform (DWT) based scheme, and scalable video coding (SVC) scheme) in terms of average peak signal-to-noise ratio under heterogeneous scenarios. [ABSTRACT FROM AUTHOR]

To cope with rapid growth of video services, we propose a non-orthogonal multiple access (NOMA) based scalable video multicast (NOMA-SVM) framework for mobile networks, by exploiting NOMA's specific potential in scalable video multicast transmission. We consider statistical channels, instead of channels with perfect estimation, in the proposed NOMA-SVM framework in order to capture the realistic channel behaviors. As quality of experience (QoE) is a better metric than throughput for video transmission, QoE-driven power allocation is performed among multiple video layers in the proposed NOMA-SVM framework, in which users can decode video with quality proportional to their channel conditions. Specifically, we formulate the power allocation problem with the goal to maximize the average QoE over all users while guaranteeing the basic services of these users. To solve such a non-convex discrete problem, an optimal algorithm is developed based on the hidden monotonicity of the problem. A suboptimal algorithm is also proposed with much lower complexity in order to meet the practical needs. Simulation results show that the proposed algorithms outperform existing orthogonal multiple access (OMA) and NOMA based algorithms under various multicast scenarios in terms of QoE. [ABSTRACT FROM AUTHOR]

Non-orthogonal multiple access (NOMA) is promising to enable growing video services with requirements of massive traffic and low latency. In this paper, we investigate a novel multi-user NOMA system design for video delivery. Different from data delivery considered in existing NOMA systems, video distortion is taken into consideration for the design and optimization of the proposed scheme. We first propose a cross-layer scalable video delivery scheme over NOMA wireless networks based on given user grouping. By adopting a semi-analytical rate distortion model for encoded video sequences and investigating the physical layer model for the multi-carrier NOMA network, the distortion-aware power allocation problem is formulated with the goal to minimize the system end-to-end distortion with quality-of-service requirements. To solve such a non-convex problem, we design an efficient algorithm by exploiting its hidden monotonic property to approximate the optimal solution. Inspired by the decoding order in NOMA, a fast algorithm is developed by combining water-filling and greedy strategies to further tame the computational complexity. Simulations results have verified the advantages of the proposed cross-layer scheme with distortion-aware power allocation algorithms, against two existing NOMA schemes and an OMA scheme. [ABSTRACT FROM AUTHOR]

Video delivery has been playing an essential role in video services over edge networks. Although HTTP segment-based streaming, e.g., Dynamic Adaptive Streaming over HTTP (DASH), has become the prevailing technique, it cannot provide guaranteed video playback in terms of bitrate to mobile users. In essence, HTTP streaming downloads the video segments in a best effort fashion, i.e., passively responding to the channel dynamics. This can cause unstable playback with frequent rebuffer and multi-client competition that degrades a network-wide performance. In this paper, we present a network-assisted streaming framework for Guaranteed Playback-Experience Streaming over HTTP (GESH) that leverages the proactive control of network resources and joint coordination among multiple clients for service-aware network resource allocation. Specifically, GESH is empowered by a new weighted proportional fair scheduling without modifying existing cellular infrastructure, a per-segment channel variation model, and a suite of algorithms to seek the optimal weights for the scheduling. Extensive evaluations show that GESH can maximally guarantee the video playback of multiple users, as well as significantly outperforming conventional HTTP streaming and current DASH systems. [ABSTRACT FROM AUTHOR]

Wireless body area network (WBAN) has become a promising network for continuous health monitoring of various diseases. The limited energy of sensors in WBAN cannot support the long-term work with the high requirements of Quality of Service (QoS) for health applications. Energy harvesting (EH)-powered WBAN, which can provide uninterrupted work, has attracted more attention from both academic and industry. However, the time-varying and heterogeneous EH states of different sensors become an important factor when designing the resource allocation schemes in EH-powered WBAN. In this paper, we propose a novel two-phase resource allocation scheme, which optimizes the allocation of the transmission power, the source rate and the time slots to improve the QoS performances of EH-powered WBAN. In the first phase, we investigate that the statistical knowledge of energy harvesting to measure the long-term QoS performances, and then a joint power-rate control scheme is proposed to optimize the transmission power and the source rate for ensuring the long-term QoS performance. Moreover, we design a QoS aware slot allocation scheme to dynamically adjust the time slot allocation to cope with the time-varying and heterogeneous EH states for obtaining better short-term QoS performances in the second phase. Finally, numerical simulation results demonstrate that the proposed joint power-rate-slot resource allocation scheme of EH-powered WBANs can efficiently exploit the time-varying EH to improve both the long-term and short-term QoS performances. [ABSTRACT FROM AUTHOR]

We present in this paper a novel proactive interference avoidance scheme for mobile-to-mobile (M2M) communication as an underlay in Long-Term Evolution (LTE) downlink networks. The proposed scheme introduces an intelligent user-selective resource allocation algorithm that aims to proactively avoid interference between M2M pairs and LTE regular users while achieving a satisfactory link budget for both M2M and LTE regular links. The proposed resource allocation algorithm is based on a novel low-complexity interference estimation approach that requires only channel quality indicator (CQI) information (CSI). Since the CQI reporting mechanism has been already implemented in current LTE systems, the proposed algorithm is indeed practical and standard compatible, compared with the existing works that require perfect knowledge of the channel state information (CSI). In this research, achievable data throughput with LTE-compliant adaptive modulation and coding has been adopted as the optimization measurement, rather than the information-theoretic capacity. Therefore, the performance of the proposed scheme is practically realizable in LTE communication systems. Since the performance of the proposed scheme highly relies on the accuracy of CQI feedback, we also carry out performance analysis to evaluate the impact of CQI estimation error and delay. The simulation results show that the total achievable data throughput for LTE networks is dramatically enhanced by M2M communication with this proposed interference avoidance resource allocation scheme. [ABSTRACT FROM PUBLISHER]

This paper presents a novel smart downlink scheduling scheme to enhance the performance of multimedia transmission over long-term evolution (LTE) networks. LTE represents a promising framework for the next-generation broadband multimedia services because of its significantly increased data rate over 3G cellular networks. However, the current LTE scheduling scheme has largely been designed for general data traffic without adequate consideration of multimedia characteristics. Moreover, the hard handoff (HO) procedure adopted in LTE will further degrade the multimedia services when the mobile user moves from one cell to another. Even with increased data rate, current LTE systems still cannot deliver the expected quality of service (QoS) to the mobile users under various mobility scenarios, especially when the hard HO is evoked. Aiming at overcoming these major challenges, we develop in this paper a QoS-driven smart downlink scheduling scheme for enhanced multimedia transmission over LTE networks. The proposed design shall take the following QoS metrics into consideration: 1) the delay constraint of voice-over-Internet protocol flow; 2) the packet deadline of video flow; and 3) the service degradation induced by the hard HO procedure. We achieve the design objectives by creating three QoS-driven operational control modules: 1) a transmission delay control module to ensure the on-time arrival of various types of multimedia data; 2) an HO control module to warrant continuous multimedia services when the user moves across a cell boundary; and 3) a resource allocation module to strategically map the requested flows to best fit radio resource blocks. The simulation results confirm the performance gain of the proposed scheme. [ABSTRACT FROM AUTHOR]

In the existing cooperative cognitive radio, primary users are generally assumed to be more than capable of supporting their target throughput, thereby the rate enhancement or the cooperation from secondary users actually has less attraction to primary users. Instead, they might be more interested in the benefits in other format. This paper presents a new cooperative cognitive radio framework, where primary users are willing to cooperatively relay data for secondary users with their under-utilized resource to earn the revenue. An auction model with multiple auctioneers, multiple bidders and hybrid divisible/indivisible commodities is proposed to solve channel bands and cooperative transmit power competitions among secondary users. For maximizing the utility, secondary users can select receiving primary user’s assistance (i.e., work in cooperative transmission mode) and purchase both spectrum and power from the primary user, or select direct transmission mode and just buy spectrum from the primary user. Then, the convergence of the proposed auction scheme to a Walrasian equilibrium is mathematically proved. Finally, the performance of the proposed scheme is verified by the simulation results. [ABSTRACT FROM PUBLISHER]

This research addresses the problem of robust linear video transmission over the Rayleigh fading channel, where only statistical channel state information (CSI) is available to the sender. We observe that discarding low-priority (LP) data and saving the channel uses for high-priority (HP) data can significantly improve the quality of the received video. We formulate an optimization problem that aims to minimize the total squared error of a multi-variant Gaussian random vector under the given bandwidth and power resources. To tame the complexity of this NP-hard problem, we analyze two sub-problems, namely power allocation and bandwidth allocation, and propose an iterative algorithm to approximate the solution. Subsequently, we propose a one-pass two-step fast algorithm that further reduces both algorithmic and computational complexity. A linear video transmission system is implemented based on the proposed algorithm. Simulations show that our system significantly outperforms SoftCast, and the PSNR gain at 5th percentile of 1000 test runs is between 4.0 dB and 7.5 dB under varying noise levels. [ABSTRACT FROM PUBLISHER]

In this paper, we consider power allocation in multiband cognitive radio (CR) networks, where multiple secondary users (SUs) transmit via a common relay and compete for the transmit power of the relay. We employ a hybrid overlay/underlay spectrum sharing scheme, allowing the SU to adapt its way of accessing the licensed spectrum to the status of the primary user (PU). If the PU is detected to be idle at the selected channel, the SU works in an overlay mode; else, it works in spectrum underlay. In addition, an auction-based power-allocation scheme is proposed to solve power competition of multiple SUs. For the SU working in spectrum overlay, the relay allocates the power in proportion to its payment without additional constraints; for the SU in spectrum underlay, its own transmit power and that of the relay are upper bounded for the quality of service (QoS) of the PU. Then, the convergence of the proposed auction algorithm and the outage probability of secondary transmissions is theoretically analyzed. Finally, the performance of the proposed scheme is verified by the simulation results. [ABSTRACT FROM PUBLISHER]

With the exponential growth of video-based services, the development of video transmission systems, and the advancement of consumer video technologies, it is becoming increasingly important to improve visual applications in order to meet the quality expectations of end users. While monitoring and controlling QoS parameters of the video transmission system is important for achieving high video quality, it is more crucial to evaluate video quality directly from the users? perspective, which is known as quality of experience (QoE), or user-level quality of service (QoS). QoE-based video quality assessment is difficult because user experience is subjective, and hence hard to quantify and measure. [ABSTRACT FROM AUTHOR]