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To compress or not to compress?

Authors: G. Buch; F. Burkert; J. Hagenauer; B. Kukla;

To compress or not to compress?

Abstract

For practical communications which transmit finite blocks of source data over noisy channels, we question the common practice to compress (C) the source and then to add redundancy for error control. Rather we exploit the redundancy of the non-compressed source (NC) at the channel decoder by source-controlled channel-decoding. For a simple binary Markov source and a Rayleigh fading channel we simulated in a fair comparison the 2 systems (C and NC) using an ARQ/FEC scheme with rate-compatible punctured convolutional (RCPC) codes, Lempel-Ziv compression and a modified Viterbi decoder. We indicate parameter regions where it is better not to compress.

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
25
Average
Top 10%
Top 10%
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