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In [[coding theory]], '''concatenated codes''' form a class of [[error-correcting code]]s that are derived by combining an '''inner code''' and an '''outer code'''. They were conceived in 1966 by [[Dave Forney]] as a solution to the problem of finding a code that has both exponentially decreasing error probability with increasing block length and [[polynomial-time]] decoding [[Computational complexity theory|complexity]].<ref name="Forney">
{{cite journal
|author=
|author-link=Dave Forney
|title=Concatenated codes
|publisher=MIT Press
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[[Noisy-channel coding theorem|Shannon's channel coding theorem]] shows that over many common channels there exist channel coding schemes that are able to transmit data reliably at all rates <math>R</math> less than a certain threshold <math>C</math>, called the [[channel capacity]] of the given channel. In fact, the probability of decoding error can be made to decrease exponentially as the block length <math>N</math> of the coding scheme goes to infinity. However, the complexity of a naive optimum decoding scheme that simply computes the likelihood of every possible transmitted codeword increases exponentially with <math>N</math>, so such an optimum decoder rapidly becomes infeasible.
In his [https://web.archive.org/web/20121012080412/http://mitpress.mit.edu/catalog/item/default.asp?tid=5813&ttype=2 doctoral thesis], [[Dave Forney]] showed that concatenated codes could be used to achieve exponentially decreasing error probabilities at all data rates less than capacity, with decoding complexity that increases only polynomially with the code block length.
==Description==
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Let ''C''<sub>''out''</sub> be a [''N'', ''K'', ''D''] code over an alphabet ''B'' with |''B''| = |''A''|<sup>''k''</sup> symbols:
:<math>C_{out}: B^K \rightarrow B^N</math>
The inner code ''C''<sub>''in''</sub> takes one of |''A''|<sup>''k''</sup> = |''B''| possible inputs, encodes into an ''n''-tuple over ''A'', transmits, and decodes into one of |''B''| possible outputs. We regard this as a (super) channel which can transmit one symbol from the alphabet ''B''. We use this channel ''N'' times to transmit each of the ''N'' symbols in a codeword of ''C''<sub>''out''</sub>. The ''concatenation'' of ''C''<sub>''out''</sub> (as outer code) with ''C''<sub>''in''</sub> (as inner code), denoted ''C''<sub>''out''</sub>
:<math>C_{out} \circ C_{in}: A^{kK} \rightarrow A^{nN}</math>
It maps each input message ''m'' = (''m''<sub>1</sub>, ''m''<sub>2</sub>, ..., ''m''<sub>K</sub>) to a codeword (''C''<sub>''in''</sub>(''m''<nowiki>'</nowiki><sub>1</sub>), ''C''<sub>''in''</sub>(''m''<nowiki>'</nowiki><sub>2</sub>), ..., ''C''<sub>''in''</sub>(''m''<nowiki>'</nowiki><sub>N</sub>)),
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==Properties==
'''1.''' The distance of the concatenated code ''C''<sub>''out''</sub>
''Proof:''
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:<math>\Delta(C_{in}(C_{out}(m^1)), C_{in}(C_{out}(m^2))) \ge dD.</math>
'''2.''' If ''C''<sub>''out''</sub> and ''C''<sub>''in''</sub> are [[linear block code]]s, then ''C''<sub>''out''</sub>
This property can be easily shown based on the idea of defining a [[generator matrix]] for the concatenated code in terms of the generator matrices of ''C''<sub>''out''</sub> and ''C''<sub>''in''</sub>.
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==Decoding concatenated codes==
A natural concept for a decoding algorithm for concatenated codes is to
In detail, let the input to the decoder be the vector ''y'' = (''y''<sub>1</sub>, ..., ''y''<sub>''N''</sub>) ∈ (''A''<sup>''n''</sup>)<sup>''N''</sup>. Then the decoding algorithm is a two-step process:
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|last=Forney
|title=Generalized Minimum Distance Decoding
|journal=IEEE Transactions on Information Theory
|volume=12
|issue=2
|pages=
|date=April 1966
|doi=10.1109/TIT.1966.1053873
}}</ref>
It uses [[erasure code|erasure]] information from the inner code to improve performance of the outer code, and was the first example of an algorithm using [[soft-decision decoding]].<ref>{{cite journal
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|last2=Costello
|title=Generalized Minimum Distance Decoding for ''Q''ary Output Channels
|journal=IEEE Transactions on Information Theory
|volume=26
|issue=2
|pages=
|date=March 1980
|doi=10.1109/TIT.1980.1056148
}}</ref><ref>{{cite journal
|first1=Yingquan
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|last2=Hadjicostis
|title=Soft-Decision Decoding of Linear Block Codes Using Preprocessing and Diversification
|journal=IEEE Transactions on Information Theory
|volume=53
|issue=1
|pages=
|date=January 2007
|doi=10.1109/tit.2006.887478
|s2cid=8338433
}}</ref>
==Applications==
Although a simple concatenation scheme was implemented already for the 1971 [[Mariner 8|Mariner]] Mars orbiter mission,<ref name="McEliece"/> concatenated codes were starting to be regularly used for [[Deep Space Network|deep space]] communication with the [[Voyager program]], which launched
Typically, the inner code is not a block code but a [[
{{cite journal
|author=J. P. Odenwalder
|title=Optimal decoding of convolutional codes
|publisher=[[U.C.L.A.]], Systems Science Dept.
|year=1970
}}
</ref>
For the outer code, a longer hard-decision block code, frequently a [[Reed
{{cite journal
|author1=
|author-link=Robert |author2=Laif Swanson
|title=Reed–Solomon Codes and the Exploration of the Solar System
|publisher=JPL
|date=20
}}
</ref>
The larger symbol size makes the outer code more robust to [[error burst
The combination of an inner Viterbi convolutional code with an outer [[Reed–Solomon code]] (known as an RSV code) was first used
In a
A simple concatenation scheme is also used on the
== Turbo codes: A parallel concatenation approach ==
The description above is given for what is now called a serially concatenated code. [[Turbo code]]s, as described first in 1993, implemented a parallel concatenation of two convolutional codes, with an interleaver between the two codes and an iterative decoder that
However, a key aspect of turbo codes is their iterated decoding approach. Iterated decoding is now also applied to serial concatenations in order to achieve higher coding gains, such as within serially concatenated convolutional codes (SCCCs). An early form of iterated decoding was
==See also==
*[[Gilbert–Varshamov bound]]
*[[Justesen code]]
*[[Singleton bound]]
*[[
== References ==
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== Further reading ==
* {{cite book |
* {{cite book | author=F.J. MacWilliams | authorlink=Jessie MacWilliams |
== External links ==
* {{scholarpedia|title=Concatenated codes|urlname=Concatenated_codes|curator=[[Dave Forney]]}}
* [https://web.archive.org/web/20110606191907/http://www.cse.buffalo.edu/~atri/courses/coding-theory/fall07.html University at Buffalo Lecture Notes on Coding Theory – Dr. Atri Rudra]
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