Symmetric Distributed Joint Source-Channel Coding Using Raptor Codes
Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient coding strategy is one of the crucial issues for applications. In this paper, a symmetric Distributed Joint Source-Channel Coding (DJSCC) sche...
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| Published in: | 2010 International Conference on Networking Architecture and Storage pp. 317 - 321 |
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| Main Authors: | , , , |
| Format: | Conference Proceeding |
| Language: | English |
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IEEE
01.07.2010
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| ISBN: | 9781424481330, 1424481333 |
| Online Access: | Get full text |
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| Abstract | Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient coding strategy is one of the crucial issues for applications. In this paper, a symmetric Distributed Joint Source-Channel Coding (DJSCC) scheme is proposed by using Raptor codes for the independent channels case. The channel noise and the correlation of sources are considered simultaneously within one set of encoder and decoder. The symmetric structure of the proposed approach leads to more flexible and balanced rate allocation, and the rateless property of Raptor codes also guarantees tractable code rates and error correction. At last, the simulation results demonstrate that our scheme outperforms the existing LDPC-based scheme at low SNR. |
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| AbstractList | Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient coding strategy is one of the crucial issues for applications. In this paper, a symmetric Distributed Joint Source-Channel Coding (DJSCC) scheme is proposed by using Raptor codes for the independent channels case. The channel noise and the correlation of sources are considered simultaneously within one set of encoder and decoder. The symmetric structure of the proposed approach leads to more flexible and balanced rate allocation, and the rateless property of Raptor codes also guarantees tractable code rates and error correction. At last, the simulation results demonstrate that our scheme outperforms the existing LDPC-based scheme at low SNR. |
| Author | Wenbo Zhang Lin Zhang Xuqi Zhu Bin Li |
| Author_xml | – sequence: 1 surname: Xuqi Zhu fullname: Xuqi Zhu email: safiml@gmail.com organization: Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China – sequence: 2 surname: Wenbo Zhang fullname: Wenbo Zhang email: zhanglin@bupt.edu.cn organization: Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China – sequence: 3 surname: Bin Li fullname: Bin Li organization: Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China – sequence: 4 surname: Lin Zhang fullname: Lin Zhang organization: Key Lab. of Universal Wireless Commun., Beijing Univ. of Posts & Telecommun., Beijing, China |
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| Snippet | Distributed compression of correlated sources has been discussed much in wireless sensor networks, while the error-resilient implementation of this efficient... |
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| SubjectTerms | AWGN channels Channel coding Decoding distributed joint source channel coding independent channels Joints low SNR Parity check codes Raptor code Signal to noise ratio |
| Title | Symmetric Distributed Joint Source-Channel Coding Using Raptor Codes |
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