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Motivation
This interactive website provides a new perspective on channel coding and the code families
used in telecommunication standards.
Toolboxes
Sionna™ and
AFF3CT are open source libraries that provide fast simulators and helpful
tools for physical layer research and channel coding.
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Bit-error-rate (BER) performance
For reliable communication over a channel (e.g. a target bit error rate of $10^{-4}$) a certain minimal SNR is required
depending on the type of channel code, the decoding algorithm, the codewordlength N and the coderate R.
The figure on the right shows the BER curve for the selected parameters.
Decoding Complexity
It is not always possible to state a general decoding complexity for a given code family since different methods for decoding may be possible.
However, we compare codes under the assumption of a given decoding algorithm implementation. The complexities are calculated as stated below.
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Beach plots and island plots
A novel type of plot is introduced in order to view different codes from a new perspective.
For a given channel coding setup the gap between the SNR defined by the channel capacity and the required SNR for different combinations of R and N is displayed.
This can be helpful to view strengths and weaknesses of state of the art channel coding methods
and simplifies comparison.
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Benchmark your own codes
You can upload your own data ( example.csv, minimum three points) and plot the evaluation.
Hovering over points will show details and update the BER plot.
Interpolation may be used to compare the codes even when the rate or length do not exactly match.
How to cite
@misc{cocomba,
author = {Bezner, Paul and Geiselhart, Marvin},
title = {{CoComBA: A Code Comparison and Benchmarking Assistant}},
howpublished = "\url{https://cocomba.inue.uni-stuttgart.de/}",
year = {2023}
}
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