17,810 research outputs found
Dependency-aware unequal erasure protection codes
Classical unequal erasure protection schemes split data to be protected into classes which are encoded independently. The unequal protection scheme presented in this paper is based on an erasure code which encodes all the data together according to the existing dependencies. A simple algorithm generates dynamically the generator matrix of the erasure code according to the packets streams structure, i.e., the dependencies between the packets, and the rate of the code. This proposed erasure code was applied to a packetized MPEG4 stream transmitted over a packet erasure channel and compared with other classical protection schemes in terms of PSNR and MOS. It is shown that the proposed code allows keeping a high video quality-level in a larger packet loss rate range than the other protection schemes
Cross-layer optimization of unequal protected layered video over hierarchical modulation
Abstract-unequal protection mechanisms have been proposed at several layers in order to improve the reliability of multimedia contents, especially for video data. The paper aims at implementing a multi-layer unequal protection scheme, which is based on a Physical-Transport-Application cross-layer design. Hierarchical modulation, in the physical layer, has been demonstrated to increase the overall user capacity of a wireless communications. On the other hand, unequal erasure protection codes at the transport layer turned out to be an efficient method to protect video data generated by the application layer by exploiting their intrinsic properties. In this paper, the two techniques are jointly optimized in order to enable recovering lost data in case the protection is performed separately. We show that the cross-layer design proposed herein outperforms the performance of hierarchical modulation and unequal erasure codes taken independently
Object-Based Unequal Error Protection
This thesis presents a comparison of two methods for Object-Based Unequal Error Protection. The two methods, Combined Unequal Error Protection and Individual Unequal Error Protection, add Forward Error Correcting Codes to embeddedly coded objects of an image. This is done so that each byte within an object is protected according to its importance, has object-level of error protection proportional to the object\u27s importance to the reconstructed quality, and has random access at the receiver. It is found that random access to the objects is obtained at a cost in terms of quality
Quality of Experience and Adaptation Techniques for Multimedia Communications
The widespread use of multimedia services on the World Wide Web and the advances
in end-user portable devices have recently increased the user demands for better quality.
Moreover, providing these services seamlessly and ubiquitously on wireless networks and
with user mobility poses hard challenges. To meet these challenges and fulfill the end-user
requirements, suitable strategies need to be adopted at both application level and network
level. At the application level rate and quality have to be adapted to time-varying bandwidth
limitations, whereas on the network side a mechanism for efficient use of the network
resources has to be implemented, to provide a better end-user Quality of Experience (QoE)
through better Quality of Service (QoS). The work in this thesis addresses these issues by
first investigating multi-stream rate adaptation techniques for Scalable Video Coding (SVC)
applications aimed at a fair provision of QoE to end-users. Rate Distortion (R-D) models
for real-time and non real-time video streaming have been proposed and a rate adaptation
technique is also developed to minimize with fairness the distortion of multiple videos
with difference complexities. To provide resiliency against errors, the effect of Unequal
Error protection (UXP) based on Reed Solomon (RS) encoding with erasure correction has
been also included in the proposed R-D modelling. Moreover, to improve the support of
QoE at the network level for multimedia applications sensitive to delays, jitters and packet
drops, a technique to prioritise different traffic flows using specific QoS classes within an
intermediate DiffServ network integrated with a WiMAX access system is investigated.
Simulations were performed to test the network under different congestion scenarios
Mcmc- Based Optimization And Application
In the thesis, we study the theory of Markov Chain Monte Carlo (MCMC) and its application in statistical optimization. The MCMC method is a class of evolutionary algorithms for generating samples from given probability distributions. In the thesis, we first focus on the methods of slice sampling and simulated annealing. While slice sampling has a merit to generate samples based on the underlying distribution with adjustable step size, simulated annealing can facilitate samples to jump out of local optima and converge quickly to the global optimum. With this MCMC method, we then solve two practical optimization problems. The first problem is image transmission over varying channels. Existing work in media transmission generally assumes that channel condition is stationary. However, communication channels are often varying with time in practice. Adaptive design needs frequent feedback for channel updates, which is often impractical due to the complexity and delay. In this application, we design an unequal error protection scheme for image transmission over noisy varying channels based on MCMC. First, the problem cost function is mapped into a multi-variable probability distribution. Then, with the “detailed balance , MCMC is used to generate samples from the mapped stationary distribution so that the optimal solution is the one that gives the lowest data distortion. We also show that the final rate allocation designed with this method works better than a conventional design that considers the mean value of the channel. In the second application, we consider a terminal-location-planning problem for intermodal transportation systems. With a given number of potential locations, it needs to find the most appropriate number of terminals and their locations to provide the economically most efficient operation when multiple service pairs exist simultaneously. The problem also has an inherent issue that for a particular planning, the optimal route paths must be determined for the co-existing service pairs. To solve this NP-hard problem, we design a MCMC-based two-layer method. The lower-layer is an optimal routing design for all service pairs given a particular planning that considers both efficiency and fairness. The upper-layer is finding the optimal planning based on MCMC with the stationary distribution that is mapped from the cost function. The effectiveness of this method is demonstrated through computer simulations and comparison with one state-of-the-art method. The work of this thesis has shown that a MCMC-method, consisting of both slice sampling and simulated annealing, can be successfully applied to solving practical optimization problems. Particularly, the method has advantages in dealing with high-dimensional problems with large searching spaces
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