Maodong Li

Cross-layer optimization for SVC video delivery over the IEEE 802.11e wireless networks

The Scalable Video Coding (SVC) standard extends the H.264/AVC with scalability support and is effective to adapt bitrate to the time-varying wireless channel bandwidth. In this paper, we propose a cross-layer optimization scheme, which includes packet prioritization and QoS mapping, for the delivery of SVC over the IEEE 802.11e wireless networks. The proposed structure enables interaction among different network layers, providing differentiated services for video packets. Our cross-layer optimization performs with the following information: (i) SVC packet prioritization at the application layer, (ii) service differentiation at the MAC layer, and (iii) interface queue (IFQ) occupation status at the link layer. We formulate the QoS mapping problem as a joint optimization of access category (AC) assignment and IFQ control. A novel and efficient solution is proposed to reduce the computational complexity of the joint optimization problem. Simulation results show that the proposed approach achieves notable improvement when compared to conventional methods.

Scalable Resource Allocation for SVC Video Streaming Over Multiuser MIMO-OFDM Networks

In this paper, we propose a scalable resource allocation framework for streaming scalable videos over multiuser multiple-input multiple-output orthogonal frequency-division multiplexing (MIMO-OFDM) networks. We exploit the utilities of scalable videos produced by the scalable extension of H.264/AVC (SVC) and investigate the multidimensional diversities of the multiuser MIMO-OFDM wireless networks. First, we study the rate-utility relationship of SVC via a packet prioritization scheme. Based on the rate-utility analysis, a scalable resource-allocation framework is proposed to achieve differentiated service objectives for different scalable video layers. To provide users with fair opportunities to acquire basic viewing experience, a fair scheme is designed to guarantee that each user is entitled to a MAXMIN fairness to have their base layer video packets received. After all users have their base layer packets successfully scheduled, resources are distributed to exploit the network efficiency. The two schemes are integrated into a unified bit loading and power allocation solution to enhance the practicability of the scalable framework. Experiment results confirms that the proposed scheme handles fairness and efficiency better at different scenarios than the conventional schemes.

Perception-Aware Multiple Scalable Video Streaming Over WLANs

In this letter, we consider how to efficiently transmit multiple video programs over IEEE 802.11e WLANs using scalable video coding technique. Scalable video offers flexibilities and functionalities for video adaptation according to the time-varying wireless channel conditions. We examine the perceptible quality impact of scalable video packets and maximize the minimum perceptible video utility of each scalable video stream. The quality of service is optimized by QoS mapping such that scalable video packets with higher impact on perceptible quality are better protected by the enhanced distributed channel access mechanism (EDCA). Using a MAXMIN strategy, we achieve fair distribution of videos to end users based on the spatial, temporal, and quality scalabilities offered by scalable video coding. Our simulation results show the efficacy and performance of the proposed approach.

A MAXMIN resource allocation approach for scalable video delivery over multiuser MIMO-OFDM systems

In this paper, we propose a novel approach for scalable video delivery over multiuser Multiple Input Multiple Output-Orthogonal Frequency Division Multiplexing (MIMO-OFDM) systems with MAXMIN fairness ensured. Scalable Video Coding (SVC) is efficient for rate adaptation and unequal protection in wireless networks where heterogeneous mobile clients have different hardware specifications and time-varying channel conditions. Using the scalability characteristics of SVC, we propose a general approach to ensure fairness for multiple scalable video downlink from a multiple-antenna base station. The fairness is achieved by packet priority analysis referring to layer dependency from application layer and a MAXMIN resource allocation at the physical layer. Based on packet priorities, time-frequency resource, power and modulation schemes are adaptively selected for transmission. This scheme significantly improves the overall system performance and guarantee fairness among users, as demonstrated by experimental comparisons with conventional radio resource allocation schemes.

On quality of experience of scalable video adaptation

Abstract In this paper, we study the quality of experience (QoE) issues in scalable video coding (SVC) for its adaptation in video communications. A QoE assessment database is developed according to SVC scalabilities. Based on the subjective evaluation results, we derive the optimal scalability adaptation track for the individual video and further summarize common scalability adaptation tracks for videos according to their spatial information (SI) and temporal information (TI). Based on the summarized adaptation tracks, we conclude some general guidelines for the effective SVC video adaptation. A rate-QoE model for SVC adaptation is derived accordingly. Experimental results show that the proposed QoE-aware scalability adaptation scheme significantly outperforms the conventional adaptation schemes in terms of QoE. Moreover, the proposed QoE model reflects the rate and QoE relationship in SVC adaptation and thus, provides a useful methodology to estimate video QoE which is important for QoE-aware scalable video streaming.

Set-to-set gait recognition across varying views and walking conditions

This paper examines the multiview gait recognition problem in which human gait sequences are collected from several different views simultaneously. Motivated by the fact that set-based feature representation can handle certain intra-subject variations, we propose a new Multiview Subspace Representation (MSR) method for gait recognition across varying views and walking conditions. It takes samples collected from different views of the same subject as a feature set and uses a subspace to represent such information. Then, the similarity of two subjects is measured by the distance between two subspaces and a simple yet effective Weighted Subspace Distance (WSD) algorithm is applied to calculate the similarity. There are two notable advantages of our proposed method: 1) we need not know the exact view of the test gait sequence in advance, and 2) some extent of intra-subject variations can be effectively handled. Experimental results on two benchmark multi-view gait databases are presented to demonstrate the effectiveness of the proposed method.

Efficient packet scheduling for scalable video delivery to mobile clients

Scalable Video Coding (SVC) provides an efficient solution for video adaptation to satisfy different requirements from heterogeneous mobile clients due to their display sizes and channel conditions. Based on the encoding structure and dependency relationship, SVC packets are entitled with different priorities in presenting quality of video sequences. In this paper, a functional model is derived to calculate packet priority index for multiple scalable video streaming to heterogeneous mobile clients. SVC packet layer ID information is utilized for packet prioritization which provides a fast and efficient implementation in packet scheduling. The accuracy and efficacy of the model are validated by comparisons with the maximum performance achieved from the distortion based prioritization. The generality is considered under different coding structures and the utility is convinced through comparisons with conventional streaming schemes in which different resolution videos are transmitted through IEEE 802.11e wireless networks.

QoE analysis for scalable video adaptation

Quality of Experience (QoE) serves as a key service goal in video applications. In this paper, we study the QoE issue in scalable video adaptation by constructing a subjective video quality assessment database based on the full scalability of SVC. We derive the optimal scalability adaptation track for individual video and further summarize common scalability adaptation tracks for grouped videos. The common track provides useful guidelines on how to adapt scalable video based on their content characteristics. A rate-QoE model is proposed accordingly for the SVC adaptation. Experimental analyses show that the novel QoE-aware scalability adaptation scheme significantly outperforms the existing ones.

Joint power allocation and bit loading for enhanced SVC video downlink transmissions over SDMA/OFDMA networks

We address in this paper the utility maximization of scalable video transmission under limited radio resource in a multi-user, multi-antenna downlink. The proposed utility maximization framework comprises two parts: a utility analysis of scalable video based on approximated rate-distortion function and a resource allocation scheme by joint power allocation and bit loading. Scalable video packets are entitled with differentiated priority due to the inherent dependency relationship in a layer-based encoding scheme. First, we analyze the rate-utility of scalable video by packet prioritization, which plays a key role in video utility maximization under a fixed rate constraint. Then to cater for diverse rate-utility character and time-varying network condition for multiple scalable video downlink over SDMA/OFDMA system, a joint power allocation and bit loading scheme is proposed to increase the overall video utility under limited radio resource. The resource allocation is accomplished by three important procedures, user grouping, bit loading and power adaptation. The performance of the proposed scheme is validated by comparing with conventional radio resource allocation schemes.

Joint packet prioritization and QoS mapping for SVC over wlans

The emerging H.264/AVC extension, SVC encoding standard facilitates the truncation of bitstreams at certain points to fit in with wireless network variations. In this paper, we propose a joint packet prioritization and QoS mapping strategy based on priority analysis of SVC packets and the exploration of the service differentiations among IEEE 802.11e EDCA access categories. The proposed scheme enables the interaction among different layers, providing differentiated services for scalable video packets. The cross-layer optimization is performed based on SVC packet information at application layer, differentiated access categories at MAC layer and interface queue (IFQ) control at link layer. Based on these cross-layer information, the proposed joint packet prioritization and QoS mapping strategy minimizes the packet loss impact of visual quality. The proposed approach shows significant performance improvement when compared to conventional schemes for SVC streaming over 802.11e wireless networks.