On Unequal Error Protection of Convolutional Codes From an Algebraic Perspective

Wang, Chung-Hsuan; Chiu, Mao-Ching; Chao, Chi-chao

doi:10.1109/tit.2009.2034821

Cited by 9 publications

(4 citation statements)

References 37 publications

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“…Based on this fact, we chose to protect the bitstreams with UEP pre-code that possesses three SVC/MGS layers with 1:1:1 ratio among the bit rates and proper erasure protection. More precisely, we adopted as pre-code a three-layered UEP convolutional code [36] because it provides a code designer capability to cope with variations of the input stream size, although, it suffers from a minor sacrifice of the overall coding rate. In order to reduce the inflation rate of the composite code, we decided to raise the code rate of the pre-code through puncturing providing the maximum separation vector.…”

Section: Protecting Svc Multicastmentioning

confidence: 99%

Customizing short-length LT codes with evolution strategies for video streaming protection

Hornansky¹,

Zao²

2017

Multimed Tools Appl

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Designing short-length Luby Transform (SLLT) codes to best protect video streaming and multicasting over lossy communication remains largely an empirical exercise. In this paper, we present a systematic approach to customize the decoding performance of these codes so that the protected video bitstreams may have the best playback quality over a wide range of channel loss rates. Our approach begins with the proposal of a new SLLT decoding performance model based on three parameters: decoding overhead, symbol decoding failure rate and tail probability of symbol decoding failure rate. We then formulate the design of SLLT codes as a multi-objective optimization problem, specify the design objectives in terms of goal program, and search for the most suitable codes using an augmented weighted Tchebycheff method implemented with the Covariance Matrix Adaptation Evolution Strategy (CMA-ES). Two design examples are provided to illustrate the effectiveness of our approach: (1) an SLLT postcode of a short-length raptor code that provides erasure protection to H.264 AVC bitstreams, and (2) an SLLT post-code of a rateless UEP code that supports graceful degradation of H.264 SVC playback quality. Empirical results demonstrate that the proposed method is capable of producing SLLT codes with customized decoding performance, whereas, the customized codes enable the playback pictures to attain significantly higher PSNR values at different stages of the decoding process than the pictures recovered under the protection of conventionally optimized codes.

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Section: Protecting Svc Multicastmentioning

confidence: 99%

Customizing short-length LT codes with evolution strategies for video streaming protection

Hornansky¹,

Zao²

2017

Multimed Tools Appl

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“…As shown by [33], UEP coding theory for block codes [30], [31] can be extended to convolutional codes as well. In fact, UEP capabilities can be expected since we have a rate r = k/n convolutional code with k > 1 [33]- [35]. However, the inherent UEP properties of G(D) are closely related to the polynomials G x (D) [34], [35].…”

Section: Distributed Network/channel Codementioning

confidence: 99%

“…In fact, UEP capabilities can be expected since we have a rate r = k/n convolutional code with k > 1 [33]- [35]. However, the inherent UEP properties of G(D) are closely related to the polynomials G x (D) [34], [35]. It is important to note that the convolutional codes used at the sources should be chosen in order to avoid catastrophic convolutional codes seen at the relays [29].…”

Section: Distributed Network/channel Codementioning

confidence: 99%

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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“…It is realized by multiple coding schemes, so the structures of the encoder and decoder are more complicated. The latter was first proposed by Masnick in [12], it is often used to provide better protection to one subset of bits in a coding block and ensure that the bits of higher protection level have less error probability than the bits with lower protection level [10][11][12]. The bit-wise method constructs unequal distances for information bits in one coding block by algebraic means and assigns them with different error correcting capabilities in once coding process without changing the coding rate.…”

Section: A Unequal Error Protection Codesmentioning

confidence: 99%

Image Watermarking Scheme With Unequal Protection Capability Based on Error Correcting Codes

Qin¹,

Mao²,

Zhang³

2010

JMM

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We propose a novel image watermarking scheme capable of providing unequal protection levels to different regions. In the scheme, we firstly construct the unequal error protection (UEP) code by designing an unequal coding space using algebra means, then we divide the image into high protection region, low protection region and non-protection region, and use the UEP code to encode the bits generated by high and low protection regions simultaneously and form the watermark bits to embed in the non-protection region. On the receiver side, the extracted bits with UEP capability can restore the high protection region more correctly than the low protection region after the efficient decoding algorithm is applied.

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On Unequal Error Protection of Convolutional Codes From an Algebraic Perspective

Cited by 9 publications

References 37 publications

Customizing short-length LT codes with evolution strategies for video streaming protection

Customizing short-length LT codes with evolution strategies for video streaming protection

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

Image Watermarking Scheme With Unequal Protection Capability Based on Error Correcting Codes

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