Phuc Chau

Hierarchical random linear network coding for multicast scalable video streaming

Network coding (NC) has been exploited to minimize delay, energy per bit and to maximize throughput over lossy networks. However, applying network coding for scalable video transmission over packet-lossy networks is still an active research topic because of the challenge in trading off between rank deficiency problem and scalability of the video bitstream. Scalable video coding promises providing flexible broadcasting to heterogeneous user equipments, but the rank deficiency problem in NC limits the scalable capability in video streaming since the time of waiting for full rank causes long delay. In this paper, we exploit the combination of hierarchical and random linear network coding for solving the above issue. The hierarchical network coding provides unequal erasure protection for scalable layers and addresses the process of decoding layer by layer according to importance. Otherwise, random linear network coding provides error-correcting capability and makes the scheme resilient to packet loss. Our proposed network coding scheme benefits from these two schemes for multicast scalable video streaming. The simulation results and performance analysis are provided to evaluate the efficiency in terms of averaged decoding probability and peak signal-to-noise ratio. The proposed scheme achieves same performance of random linear network coding in good channel and approximately hierarchical network coding scheme in bad channel.

Efficient data uploading based on network coding in LTE-Advanced heterogeneous networks

LTE-Advanced heterogeneous networks enable a uniform broadband experience to users flexibly anywhere in the network by using a mix of large and small cells — i.e., macro, pico, femto and relay stations. In this paper, we propose a novel network coding-based for mobile content uploading, where multiple user equipments upload their own content toward the eNodeB in LTE-Advanced relay networks. Network coding has been considered as a promising solution in next generation networks because of the significant improvement in the transmission rate and reliability. The network coding enables an intermediate node having the capability of encoding incoming packets rather than simply forwarding. However, the advantages come at the cost of high computational, storage costs and coding vector overhead. The two former drawbacks can be solved easily by the fast development of current smart users and relay with high capability on computation and storage. The last issue of coding vector overhead still remains as many packets are encoded together using a linear combination since each packet needs to carry a large size of the header to store the information of the coding vector. We propose random overlapped chunked code for enhancing the transmission rate and reliability under the constraint of coding vector overhead. Furthermore, the encoding and decoding processes can be operated with low complexity. The complete transmission consists of two phases: users upload the content to the relay; the relay performs the proposed random overlapped chunked code of different coming streams from users and forwards the network-coded packets to the eNodeB. For performance evaluation, we run various simulations along with analysis to show that our proposal outperforms current schemes in terms of decoding probability.

Two cooperative multicast schemes of scalable video in relay-based cellular networks

This study investigates the cooperative multicast of scalable video over dedicated relay-based cellular networks. Different layers in a scalable video tend to have different transmission quality requirements, and legacy cellular network has limitations in providing homogeneous service quality within its coverage area. The authors propose two realistic cooperative transmission schemes with a capacity performance analysis for scalable video over dedicated relay-based cellular networks. The proposed transmission schemes with multiple antennas at an evolved node B and the dedicated relay utilise the combinations of beamforming and space-time coding in order to enhance the multicast performance of scalable video. The proposed schemes ensure that the received base layer (BL) of scalable video guarantees the minimum video quality to all user terminals throughout the cell coverage with given outage probability, while the terminals inside the relay coverage can achieve better video quality by receiving both the BL and additional enhancement layer data according to the received channel condition. The antennas configuration and the video type determine which multicast scheme to choose.

A comparison of transmission schemes for scalable video over MIMO relay networks

This paper investigates a comparison of transmission schemes for the scalable video over multiple-input multiple-output relay networks. We consider three time-division multiple-access cooperative schemes by using embedded space time codes with various degrees of broadcasting and receiving collision. In this paper, we assume that base station and relay station are equipped two antennas and mobile stations have only one antenna. The relay station operates decode-and-forward mode for cooperative transmission. The base station broadcasts scalable video bit stream by encoding embedded space time codes with the assistance of relay. Upon the amount of received information of each cooperative scheme, Mobile stations get the corresponding efficient decoding. With the help of relayed information, base layer retrieves better protection for ensuring the basic quality of scalable video. Visual quality is refined by enhancement layers carried in transmitted signal. We investigate the diversity performance of various schemes in term of bit error rate. Scalable video performance is also provided for comparing and evaluating the effectiveness of scalable video transmission schemes. Based on the need of users, its possible to select the suitable scheme for trading off between the protection of base and enhancement layers.

Efficient scalable video multicast based on network-coded communication

In order to increase the efficiency of mobile video transmission in a 5G network, this paper investigates a cooperative multicast of scalable video using network coding with adaptive modulation and coding over dedicated relay-based cellular networks. Different scalable video layers prefer different protection degrees, and user equipments (UEs) in different locations experience different packet loss rates in wireless networks. Guaranteeing that all UEs experience a certain level of video quality is one of the biggest challenges in scalable video multicast. Using the number of satisfied UEs as a metric, the proposed efficient scalable video multicast based on network-coded cooperation (SVM-NC) scheme, combined with adaptive modulation and coding, enhances the attainable system performance under strict time and bandwidth resource constraints for guaranteed smooth playback. Various simulations were performed for performance evaluation. The proposed scheme ensures that the expected percentage of satisfied UEs approximately achieves the maximum number of UEs in a multicast group by using network-coded cooperation over dedicated relay-based cellular networks. In addition, the peak signal-to-noise ratio metric is asymptotic to the maximum performance of high-resolution video quality offered by service providers.

Distributed Systematic Network Coding for Reliable Content Uploading in Wireless Multimedia Sensor Networks

Recently, the wireless sensor network paradigm is shifting toward research aimed at enabling the robust delivery of multimedia content. A challenge is to deliver multimedia content with predefined levels of Quality of Service (QoS) under resource constraints such as bandwidth, energy, and delay. In this paper, we propose a distributed systematic network coding (DSNC) scheme for reliable multimedia content uploading over wireless multimedia sensor networks, in which a large number of multimedia sensor nodes upload their own content to a sink through a cluster head node. The design objective is to increase the reliability and bandwidth-efficient utilization in uploading with low decoding complexity. The proposed scheme consists of two phases: in the first phase, each sensor node distributedly encodes the content into systematic network coding packets and transmits them to the cluster head; then in the second phase, the cluster head encodes all successfully decoded incoming packets from multiple sensor nodes into innovative systematic network coding packets and transmits them to the sink. A bandwidth-efficient and channel-aware error control algorithm is proposed to enhance the bandwidth-efficient utilization by dynamically determining the optimal number of innovative coded packets. For performance analysis and evaluation, we firstly derive the closed-form equations of decoding probability to validate the effectiveness of the proposed uploading scheme. Furthermore, we perform various simulations along with a discussion in terms of three performance metrics: decoding probability, redundancy, and image quality measurement. The analytical and experimental results demonstrate that the performance of our proposed DSNC outperforms the existing uploading schemes.

APRA: Affinity Propagation-Based Resource Allocation Scheme in M2M for System Capacity Maximization

Abstract In this paper, we propose an enhanced affinity propagation (AP)-based resource allocation scheme (APRA) to overcome major issues in machine-to-machine (M2M), such as delay, complexity, throughput, and system capacity. There would be rapid increase of added devices, such as cellular and machine-type devices. It would be difficult for Evolved Node B (eNB) to control all of them. Considering this problem, we propose an AP-based group formation method in which machines make groups with other similar type of machines. After making groups, group members in each group can communicate directly with each other by getting a channel from eNB via their group head. A resource allocation method is proposed for different groups that can use the same channel at the same time. Considering energy constraints, we also propose different methods to rotate the role of a group head among group members, through the modification of AP or the application of Markov chain model. As expected, the group head will drain energy at a higher rate than the group members. Thus, the rotation of the group head will increase the overall performance. Simulation results show that the proposed method can minimize both data delivery delay and operation complexity while increasing the throughput, system capacity, and energy efficiency through the rotation of the group head.

Scalable video multicast using inter-layered superposition and network-coded cooperation over MIMO relay systems

Abstract The adoption of scalable video coding (SVC) for video multicast services is a promising solution for providing efficient streaming under channel heterogeneity, since SVC can support quality scalability with high coding efficiency. The scalability allows receivers to experience video quality according to their channel conditions. Nevertheless, the scalable video layers are inter-dependent; if a layer of the scalable video is lost, all subsequent layers that depend on the lost layer are downloaded but not rendered, which leads to a low video quality and bandwidth inefficiency. Consequently, unequal error protection among scalable video layers needs to be addressed in a bandwidth-efficient manner. This paper proposes a scalable video multicast scheme over relay-based cellular networks, consisting of two main components: inter-layered superposition in the first phase and digital network coding in the second phase. In this joint design, the proposed inter-layered superposition coding provides incremental service quality according to average channel conditions, as well as unequal error protection under channel heterogeneity. Furthermore, the network-coded cooperation, implemented by mixing all decoded signals at the relay, improves bandwidth efficiency by reducing the number of transmissions in the second phase. The proposed scheme aims to increase the number of users experiencing a maximal number of rendered video layers as well as bandwidth efficiency. We also derive the relevant channel capacities of scalable layers for performance analysis. Numerical results, consisting of a cumulative distribution function of channel capacity, achievable video data rate, and video quality measurement, confirm that our design objective can be achieved for video multicast over multiple-input and multiple-output relay-based cellular networks.

An efficient resource allocation scheme for scalable video multicast in LTE-advanced networks

We address the challenge of optimizing the radio resource allocation for scalable video multicast over LTE-Advanced. The advantage of multicast service is to utilize the available bandwidth efficiently in delivering the same content to multiple receivers. However, the instantaneous channel condition of each receiver in the multicast group varies independently. To guarantee all receivers experiencing similar performance becomes more challenging. Hence, we need an advanced radio resource management to guarantee the least quality of service levels. In this paper, we propose a novel heuristic strategy which aims to jointly optimize the frequency selectivity, adaptive modulation and coding, and random linear network coding scheme performed at Medium Access Layer. The key aspect is that our proposal enhances the reliability of video services by exploiting random linear network coding in LTE-Advanced. Moreover, the available bandwidth is utilized efficiently by taking the advantage from the frequency selectivity in subgroup formation. We do various simulations for performance evaluation. The results show that our proposed resource allocation outperforms the existing studies regarding resource load, spectral efficiency, recovery probability and the attainable video quality (i.e., peak signal-to-noise ratio).

Content-aware RaptorQ

With a low complexity and high successful probability, RaptorQ code is considered as an efficient solution for media transmission. However, RaptorQ code is optimal for the purpose of single layer transmission. Therefore, RaptorQ code is not suitable for dependent media transmission, where the successful decoding of the least important layer depends on the successful of the more important layer, especially in Scalable video coding (SVC). In this paper, we propose an unequal error protection scheme to protect layers video in SVC using RaptorQ code named content-aware RaptorQ. Specifically, the layers are encoded based on a window selection probability so that the least important media layers is utilized to protect data of more important media layers. The simulation results demonstrate that the successful decoding probability of the proposed method is improved by 105%, relative to that of RaptorQ.