Unequal Error Protection Random Linear Coding Strategies for Erasure Channels

Vukobratović, Dejan; Stankovic, Vladimir

doi:10.1109/tcomm.2012.030712.100454

Cited by 55 publications

(93 citation statements)

References 24 publications

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“…In our technique, we use an implementation of random linear network coding referred to as expanding window network coding (EWNC) [28,32]. The key idea of EWNC is to increase the size of the coding window (i.e., the set of packets in the generation that may appear in combination vectors) for each new packet.…”

Section: Proposed Methodsmentioning

confidence: 99%

“…The coding coefficients, needed to reconstruct the original packets, are typically sent along the combinations as headers [22][23][24][25], unless more advanced reconstruction schemes are implemented at the receiver side [26,27]. Used as an alternative to traditional routing, NC has proved beneficial to real-time streaming applications, both in terms of maximization of the throughput and in terms of reduction of the effects of losses [28][29][30][31][32][33].…”

Section: Introductionmentioning

confidence: 99%

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Rate-distortion-optimized multi-view streaming in wireless environment using network coding

Greco¹,

Nemoianu

Cagnazzo

et al. 2016

EURASIP J. Adv. Signal Process.

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Multi-view video streaming is an emerging video paradigm that enables new interactive services, such as 3D video, free viewpoint television, and immersive teleconferencing. Because of the high bandwidth cost they come with, multi-view streaming applications can greatly benefit from the use of network coding, in particular in transmission scenarios such as wireless network, where the channels have limited capacity and are affected by losses. In this paper, we address the topic of cooperative streaming of multi-view video content, wherein users who recently acquired the content can contribute parts of it to their neighbors by providing linear combinations of the video packets. We propose a novel method for selection and network encoding of the transmitted frames based on the users' preferences for the different views and the rate-distortion properties of the stream. Using network coding enables the users to retrieve the content in a faster and more reliable manner and without the need for coordination among the senders. Our experimental results prove that our preference-based approach provides a high-quality decoding even when the uplink capacity of each node is only a small fraction of the rate of the stream.

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Section: Proposed Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Rate-distortion-optimized multi-view streaming in wireless environment using network coding

Greco¹,

Nemoianu

Cagnazzo

et al. 2016

EURASIP J. Adv. Signal Process.

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“…Fountain codes such as random linear network codes (RLNC) [13][14][15][16][17][18], raptor codes [19], and LT codes [20][21][22] have been studied extensively for efficient data delivery in wireless networks. These codes offer significant performance gains compared to conventional channel codes since channel protection is not pre-determined [21][22][23][24][25].…”

Section: Introductionmentioning

confidence: 99%

“…The works in [13,17,18,33] designed expanding window-based RLNC strategies for scalable video transmission such that coded packets are formed across different numbers of video layers. In particular, the authors in [17] used a probabilistic approach for selecting coding windows and included the packets in the lower video layers into all coded packets to obtain high decoding probabilities for the lower layers. Moreover, the authors in [18] considered a scalable video transmission with a hard deadline and used a deterministic approach for selecting coding windows over all transmissions before the deadline.…”

Section: Introductionmentioning

confidence: 99%

“…Moreover, the authors in [18] considered a scalable video transmission with a hard deadline and used a deterministic approach for selecting coding windows over all transmissions before the deadline. Another work in [33] continued the work in [17] and addressed the problem of jointly determining the coding strategy and the scheduling decisions when receivers obtain layered video data from multiple servers. Moreover, a resource-allocation framework for network-coded scalable video multicast services was proposed in [13] that minimizes the number of broadcast packets on each downlink channel while providing service guarantees to a predetermined fraction of receivers.…”

Section: Introductionmentioning

confidence: 99%

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Instantly decodable network coding for real-time scalable video broadcast over wireless networks

Karim

Sadeghi

Sorour

et al. 2016

EURASIP J. Adv. Signal Process.

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In this paper, we study real-time scalable video broadcast over wireless networks using instantly decodable network coding (IDNC). Such real-time scalable videos have hard deadline and impose a decoding order on the video layers. We first derive the upper bound on the probability that the individual completion times of all receivers meet the deadline. Using this probability, we design two prioritized IDNC algorithms, namely the expanding window IDNC (EW-IDNC) algorithm and the non-overlapping window IDNC (NOW-IDNC) algorithm. These algorithms provide a high level of protection to the most important video layer, namely the base layer, before considering additional video layers, namely the enhancement layers, in coding decisions. Moreover, in these algorithms, we select an appropriate packet combination over a given number of video layers so that these video layers are decoded by the maximum number of receivers before the deadline. We formulate this packet selection problem as a two-stage maximal clique selection problem over an IDNC graph. Simulation results over a real scalable video sequence show that our proposed EW-IDNC and NOW-IDNC algorithms improve the received video quality compared to the existing IDNC algorithms.

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