On the Delay and Throughput Gains of Coding in Unreliable Networks

Eryılmaz, Atilla; Ozdaglar, Asuman; Médard, Muriel; Ahmed, Ebad

doi:10.1109/tit.2008.2006454

Cited by 139 publications

(149 citation statements)

References 14 publications

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“…Hence, RLNC is able to offer the smallest block completion time among all NC techniques. It has also been shown in [6,36,37] that the block completion time of RLNC scales as O(ln(N)) when K is a constant. Consequently, the throughput of RLNC vanishes with increasing number of receivers N. To prevent zero throughput, it has been proved in [38] that K should scale faster than ln(N).…”

Section: Property 1 Removing Any Vertex From the S-idnc Graph Does Nmentioning

confidence: 96%

“…The advent of network coding (NC) [2] starts a new era for high-throughput network coded wireless communications [3][4][5][6][7][8][9][10][11][12][13][14][15][16][17]. By linearly adding all data packets *Correspondence: ming.yu@anu.edu.au Research School of Engineering, Australian National University, Canberra, Australia together with randomly chosen coefficients from a sufficiently large finite field, random linear network coding (RLNC) can almost surely achieve the minimum block completion time [9][10][11]18], which is defined as the number of transmissions it takes to complete the broadcast.…”

Section: Introductionmentioning

confidence: 99%

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Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast

Sadeghi

Aboutorab

2015

EURASIP J. Adv. Signal Process.

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We consider broadcasting a block of packets to multiple wireless receivers under random packet erasures using instantly decodable network coding (IDNC). The sender first broadcasts each packet uncoded once, then generates coded packets according to receivers' feedback about their missing packets. We focus on strict IDNC (S-IDNC), where each coded packet includes at most one missing packet of every receiver. But, we will also study its relation with generalized IDNC (G-IDNC), where this condition is relaxed. We characterize two fundamental performance limits of S-IDNC: (1) the number of transmissions to complete the broadcast, which measures throughput and (2) average packet decoding delay, which measures how fast each packet is decoded at each receiver on average. We derive a closed-form expression for the expected minimum number of transmissions in terms of the number of packets and receivers and the erasure probability. We prove that it is NP-hard to minimize the average packet decoding delay of S-IDNC. We also prove that the graph models of S-and G-IDNC share the same chromatic number. Next, we design efficient S-IDNC transmission schemes and coding algorithms with full/intermittent receiver feedback. We present simulation results to corroborate the developed theory and compare our schemes with existing ones.

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Section: Property 1 Removing Any Vertex From the S-idnc Graph Does Nmentioning

confidence: 96%

Section: Introductionmentioning

confidence: 99%

Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast

Sadeghi

Aboutorab

2015

EURASIP J. Adv. Signal Process.

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“…[17], [19], [22]) and cross-layer designs that exploit coding [18]. In our case, it is the interference that creates the code, similarly to [21].…”

Section: Related Workmentioning

confidence: 99%

SigSag: Iterative Detection Through Soft Message-Passing

Tehrani

Dimakis

Neely

2011

IEEE J. Sel. Top. Signal Process.

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Abstract-The multiple-access framework of ZigZag decoding (Gollakota and Katabi 2008) is a useful technique for combating interference via multiple repeated transmissions, and is known to be compatible with distributed random access protocols. However, in the presence of noise this type of decoding can magnify errors, particularly when packet sizes are large. We show that ZigZag decoding can be seen as an instance of belief propagation in the high-SNR limit. Building on this observation, we present a simple soft-decoding version, called SigSag, that improves performance. We show that for two users, collisions result in a cycle-free factor graph that can be optimally decoded via belief propagation. For collisions between more than two users, we show that if a simple bit-permutation is used then the graph is locally tree-like with high probability, and hence belief propagation is near-optimal. Further, we introduce the joint channel-collision decoding which decodes the collided packets while the packets are coded by an LDPC code. Through simulations we show that our scheme performs better than coordinated collision-free time division multiple access (TDMA) and the ZigZag decoder. Furthermore, we investigate the performance of the joint channelcollision decoder in different scenarios and show that it performs better than TDMA and ZigZag decoder accompanied by sumproduct decoding.

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“…These results show that the completion time grows with the number of files which is consistent with the fact that files need to be retransmitted when erasures occur and delay other file transfers. The green dotted line is based on a heuristic where erasures are known a-priori allowing to compensate for them [2].…”

Section: A Downloadsmentioning

confidence: 99%

Video-Centric Network Coding Strategies for 4G Wireless Networks: An Overview

Montpetit¹,

Médard²

2010

2010 7th IEEE Consumer Communications and Networking Conference

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Abstract-The impact of Internet content and IP based television on networks is growing. Video is now ubiquitous in the home and on the street. It demands new approaches to video transmission to meet the growing traffic volume. This paper presents a novel strategy for network coding in video transmission. It uses a variety of coding approaches and adds feedback and device discovery to tailor the coding to the receiver ecosystems and can achieve better overall performance than the non coded versions.

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On the Delay and Throughput Gains of Coding in Unreliable Networks

Cited by 139 publications

References 14 publications

Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast

Performance characterization and transmission schemes for instantly decodable network coding in wireless broadcast

SigSag: Iterative Detection Through Soft Message-Passing

Video-Centric Network Coding Strategies for 4G Wireless Networks: An Overview

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