Distributed Joint Source and Channel Coding with Low-Density Parity-Check Codes

Low-density parity-check (LDPC) codes with the parity-based approach for distributed joint source channel coding (DJSCC) with decoder side information is described in this letter. The parity-based approach is theoretical limit achievable. Different edge degree distributions are used for source varia...

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Veröffentlicht in:IEEE communications letters Jg. 17; H. 12; S. 2336 - 2339
1. Verfasser: Cen, Feng
Format: Journal Article
Sprache:Englisch
Veröffentlicht: New York, NY IEEE 01.12.2013
Institute of Electrical and Electronics Engineers
Schlagworte:
Applied sciences
Channel coding
Coding, codes
Correlation
Decoding
density evolution
Distributed joint source-channel coding
distributed source coding
Exact sciences and technology
Information, signal and communications theory
Joints
low-density parity-check codes
nonuniform sources
Parity check codes
Signal and communications theory
Source coding
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Transmission and modulation (techniques and equipments)
Performance evaluation
Source coding
Distributed source signal
density evolution
Transmission channel
Decoding
Joint source channel coding
Memoryless channel
Simulation
distributed source coding
Distributed joint source-channel coding
Error correcting code
Parity check codes
low-density parity-check codes
nonuniform sources
ISSN:1089-7798
Online-Zugang:Volltext
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Beschreibung
Zusammenfassung:Low-density parity-check (LDPC) codes with the parity-based approach for distributed joint source channel coding (DJSCC) with decoder side information is described in this letter. The parity-based approach is theoretical limit achievable. Different edge degree distributions are used for source variable nodes and parity variable nodes. Particularly, the codeword-averaged density evolution (CADE) is presented for asymmetrically correlated nonuniform sources over the asymmetric memoryless transmission channel. Extensive simulations show that the splitting of variable nodes can improve the coding efficiency of suboptimal codes and lower the error floor.
ISSN:1089-7798
DOI:10.1109/LCOMM.2013.101613.131616