Joint network-channel code design for real wireless relay networks

Pang, Kun; Lin, Zihuai; Li, Yonghui; Vucetic, Branka

doi:10.1109/istc.2010.5613834

Cited by 11 publications

(2 citation statements)

References 10 publications

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“…We consider rate-1/2 convolutional codes on the source-torelay links and rate-1 convolutional codes on the relay-todestination links. In (24), R 1 and R 2 use D-NC-F and DF, respectively, while in (25), R 1 and R 2 both use D-NC-F. The results are obtained for K = 1000 information bits.…”

Section: Simulation Resultsmentioning

confidence: 98%

Joint Network/Channel Decoding for Heterogeneous Multi-Source/Multi-Relay Cooperative Networks

Poulliat¹,

Renzo²

2011

Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools

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In this paper, we study joint network/channel decoding for multi-source multi-relay heterogeneous wireless networks. When convolutional and network codes are used at the physical and network layers, respectively, we show that error correction and diversity properties of the whole network can be characterized by an equivalent and distributed convolutional network/channel code. In particular, it is shown that, by properly choosing the network code, the equivalent code can show Unequal Error Protection (UEP) properties, which might be useful for heterogeneous wireless networks in which each source might ask for a different quality-ofservice requirement or error probability. Using this representation, we show that Maximum-Likelihood (ML) joint network/channel decoding can be performed by using the trellis representation of the distributed convolutional network/channel code. Furthermore, to deal with decoding errors at the relays, a ML-optimum receiver which exploits side information on the source-to-relay links is proposed.

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Section: Simulation Resultsmentioning

confidence: 98%

Joint Network/Channel Decoding for Heterogeneous Multi-Source/Multi-Relay Cooperative Networks

Poulliat¹,

Renzo²

2011

Proceedings of the 5th International ICST Conference on Performance Evaluation Methodologies and Tools

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“…Since any transmission link, be it wire or wireless, is bound to undergo distorsion and noise corruption, the capacity of codes [2] to correct a part of the resulting errors is necessary for a correct communication. In view of its efficiency, the principle of channel coding has been used beyond the context of robustness in signal transmission, as for instance in cooperative networks [3], [4] and in secrecy coding (see [5] and references therein) to name a few.…”

Section: Introductionmentioning

confidence: 99%

A robust signal quantization system based on error correcting codes

Jili

Mahé

Mboup

2017

2017 25th European Signal Processing Conference (EUSIPCO)

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Abstract-In this paper we propose a robust representation of a digital signal based on error correction codes. For each frame of the signal (N successive samples) a binary decomposition, as a (successive power 2) weighted sum of binary vectors, is first considered. Then, each binary vector is projected into the set of codewords of a corresponding block code.The codes are designed so that their correction powers increases inversely to the weight of the binary vectors since the binary vectors with high weight are less sensitive to disturbance. The corresponding representation (decoding) thus appears as a form of signal quantization that can provide an interesting protection against noise and/or channel distorsion. Some applications showing the utility of the proposed representation are given.

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Design of Distributed Network-Channel Codes for Wireless Sensor Networks

Pang

Lin

et al. 2011

2011 IEEE International Conference on Communications (ICC)

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Joint network-channel code design for real wireless relay networks

Cited by 11 publications

References 10 publications

Joint Network/Channel Decoding for Heterogeneous Multi-Source/Multi-Relay Cooperative Networks

Joint Network/Channel Decoding for Heterogeneous Multi-Source/Multi-Relay Cooperative Networks

A robust signal quantization system based on error correcting codes

Design of Distributed Network-Channel Codes for Wireless Sensor Networks

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