Joint source/channel coding and MAP decoding of arithmetic codes

In this paper, a novel maximum a posteriori (MAP) estimation approach is employed for error correction of arithmetic codes with a forbidden symbol. The system is founded on the principle of joint source channel coding, which allows one to unify the arithmetic decoding and error correction tasks into...

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Vydané v:IEEE transactions on communications Ročník 53; číslo 6; s. 1007 - 1016
Hlavní autori: Grangetto, M., Cosman, P., Olmo, G.
Médium: Journal Article
Jazyk:English
Vydavateľské údaje: New York, NY IEEE 01.06.2005
Institute of Electrical and Electronics Engineers
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Predmet:
Additive white noise
Applied sciences
Arithmetic
Arithmetic coding
Channel coding
Channels
Coding
Coding, codes
Convolutional codes
Decoding
Detection, estimation, filtering, equalization, prediction
Error analysis
Error correction
Error correction & detection
Error correction codes
Exact sciences and technology
Forward error correction
Image communication
Image transmission
Information, signal and communications theory
joint source/channel coding (JSCC)
maximum
Signal and communications theory
Signal, noise
Studies
Symbols
Systems, networks and services of telecommunications
Telecommunications
Telecommunications and information theory
Testing
Transmission and modulation (techniques and equipments)
Performance evaluation
maximum a posteriori (MAP) estimation
Source coding
Convolutional code
joint source/channel coding (JSCC)
Decoding
Packet error rate
Channel coding
Joint source channel coding
Flexibility
AWGN channels
Image quality
A posteriori estimation
Arithmetic code
Forward error correction
Error correction
Image transmission
Arithmetic coding
ISSN:0090-6778, 1558-0857
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Popis
Shrnutí:In this paper, a novel maximum a posteriori (MAP) estimation approach is employed for error correction of arithmetic codes with a forbidden symbol. The system is founded on the principle of joint source channel coding, which allows one to unify the arithmetic decoding and error correction tasks into a single process, with superior performance compared to traditional separated techniques. The proposed system improves the performance in terms of error correction with respect to a separated source and channel coding approach based on convolutional codes, with the additional great advantage of allowing complete flexibility in adjusting the coding rate. The proposed MAP decoder is tested in the case of image transmission across the additive white Gaussian noise channel and compared against standard forward error correction techniques in terms of performance and complexity. Both hard and soft decoding are taken into account, and excellent results in terms of packet error rate and decoded image quality are obtained.
Bibliografia:ObjectType-Article-2
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ISSN:0090-6778
1558-0857
DOI:10.1109/TCOMM.2005.849690