5 research outputs found

    Multimedia streaming over wireless channels

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    The improvements in mobile communication systems have accelerated the development of new multimedia streaming techniques to increase the quality of streaming data over time varying wireless channels. In order to increase multimedia quality, error control schemes are indispensable due to time-varying and erroneous nature of the channel. However, relatively low channel capacity of wireless channels, and dependency structure in multimedia limit the eectiveness of existing error control schemes and require more sophisticated techniques to provide quality improvement on the streaming data. In this thesis, we propose sender driven multimedia streaming algorithms that incorporate error control schemes of FEC, ARQ, and packet scheduling by considering media and channel parameters such as packet importance, packet dependencies, decoding deadlines, channel state information, and channel capacity. Initially, we have proposed a multi-rate distortion optimization framework so as to jointly optimize FEC rate and packet selection by minimizing end-to-end distortion to satisfy a specified Quality of Service under channel capacity constraint. Minimization of end-to-end distortion causes computational complexity in the rate distortion optimization framework due to dependency in encoded multimedia. Therefore, we propose multimedia streaming algorithms that select packet and FEC rate with reduced computational complexity and high quality as compared with multi-rate distortion optimization framework. Additionally, protocol stack of a UMTS cellular network system with W-CDMA air interface is presented in order to clarify the relation between proposed multimedia streaming algorithms and UMTS system that is used in simulations. Finally, proposed algorithms are simulated and results demonstrate that proposed algorithms improve multimedia quality significantly as compared to existing methods

    Packetized Media Streaming with Comprehensive Exploitation of Feedback Information

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    This paper addresses the problem of streaming packetized media over a lossy packet network, with sender-driven (re)transmission using acknowledgement feedback. The different transmission scenarios associated to a group of interdependent media data units are abstracted in terms of a finite alphabet of policies, for each single data unit. A rate-distortion optimized markovian framework is proposed, which supports the use of comprehensive feedback information. Contrarily to previous works in rate-distortion optimized streaming, whose transmission policies definitions do not take into account the feedback expected for other data units, our framework considers all the acknowledgment packets in defining the streaming policy of a single data unit. More specifically, the notion of master and slave data unit is introduced, to define dependent streaming policies between media packets; the policy adopted to transmit a slave data unit becomes dependent on the acknowledgments received about its masters. One of the main contributions of our work is to propose a methodology that limits the space of dependent policies for the RD optimized streaming strategy. A number of rules are formulated to select a set of relevant master/slave relationships, defined as the dependencies that are likely to bring RD performance gain in the streaming system. These rules provide a limited complexity solution to the rate-distortion optimized streaming problem, with comprehensive use of feedback information. Based on extensive simulations, we conclude that (i) the proposed set of relevant dependent policies achieves close to optimal performance, while being computationally tractable, and (ii) the benefit of dependent policies is driven by the relative sizes and importance of interdependent data units. Our simulations demonstrate that dependent streaming policies can perform significantly better than independent streaming strategies, especially for cases where some media data units bring a relatively large gain in distortion, in comparison with other data units they depend on for correct decoding. We observe however that the benefit becomes marginal when the gain in distortion per unit of rate decreases along the media decoding dependency path. Since such a trend characterizes most conventional scalable coders, the implementation of dependent policies can reasonably be ruled out in these specific cases

    On the complexity of rate-distortion optimal streaming of packetized media

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    We consider the problem of rate-distortion optimal streaming of packetized media with sender-driven transmission over a single-QoS network using feedback and retransmissions. For a single data unit, we prove that the problem is NP-hard and provide efficient branch and bound algorithms that are in practice much faster than the best known solution. For a group of interdependent data units, we show how to compute optimal solutions with branch and bound algorithms. The branch and bound algorithms for a group of data units are slower than the current state of the art, the heuristic sensitivity adaptation algorithm, but provide a significantly better rate-distortion performance in many real-world situations.SCOPUS: cp.pProceedings - DCC 2004 Data Compression Conference; Snowbird, UT. United States; 23 March 2004 through 25 March 2004.info:eu-repo/semantics/publishe

    On the Complexity of Rate-Distortion Optimal Streaming of Packetized Media

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    We consider the problem of optimal rate-distortion streaming of packetized multimedia data in the context of sender-driven transmission over a single-QoS network using feedback and retransmissions. For a single data unit, we prove that the problem is NP-hard and provide efficient branch and bound algorithms that are much faster than the previously best solution based on dynamic programming. For a group of data units, we show how to compute optimal solutions with branch and bound algorithms. The branch and bound algorithms for a group of data units are much slower than the current state of the art, a heuristic technique known as sensitivity adaptation. However, in many real-world situations, they provide a significantly better rate-distortion performance
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