Block code: Difference between revisions

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{{Short description|Family of error-correcting codes that encode data in blocks}}

{{More footnotes needed|date=February 2025}}

In [[coding theory]], '''block codes''' are a large and important family of [[Channel coding|error-correcting codes]] that encode data in blocks.

There is a vast number of examples for block codes, many of which have a wide range of practical applications. The abstract definition of block codes is conceptually useful because it allows coding theorists, [[mathematician]]s, and [[computer science|computer scientistsscientist]]s to study the limitations of ''all'' block codes in a unified way.

Such limitations often take the form of ''bounds'' that relate different parameters of the block code to each other, such as its rate and its ability to detect and correct errors.

Examples of block codes are [[Reed–Solomon code]]s, [[Hamming code]]s, [[Hadamard code]]s, [[Expander code]]s, [[Golay code (disambiguation)|Golay code]]s, [[Reed–Muller code]]s and [[Reed–MullerPolar code (coding theory)|Polar code]]s. These examples also belong to the class of [[linear code]]s, and hence they are called '''linear block codes'''. More particularly, these codes are known as algebraic block codes, or cyclic block codes, because they can be generated using booleanBoolean polynomials.

Algebraic block codes are typically [[Soft-decision decoder|hard-decoded]] using algebraic decoders.{{Technical statement|date=May 2015}}

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A large rate means that the amount of actual message per transmitted block is high. In this sense, the rate measures the transmission speed and the quantity <math>1-R</math> measures the overhead that occurs due to the encoding with the block code.

It is a simple [[information theory|information theoretical]] fact that the rate cannot exceed <math>1</math> since data cannot in general be losslessly compressed. Formally, this follows from the fact that the code <math>C</math> is an injective map.

=== {{anchor|Minimum distance}}The distance ''d'' ===

The '''distance''' or '''minimum distance''' {{mvar|d}} of a block code is the minimum number of positions in which any two distinct codewords differ, and the '''relative distance''' <math>\delta</math> is the fraction <math>d/n</math>.

Formally, for received words <math>c_1,c_2\in\Sigma^n</math>, let <math>\Delta(c_1,c_2)</math> denote the [[Hamming distance]] between <math>c_1</math> and <math>c_2</math>, that is, the number of positions in which <math>c_1</math> and <math>c_2</math> differ.

Then the minimum distance <math>d</math> of the code <math>C</math> is defined as

:<math>d := \min_{m_1,m_2\in\Sigma^k\atop m_1\neq m_2} \Delta[C(m_1),C(m_2)]</math>.

Since any code has to be [[injective]], any two codewords will disagree in at least one position, so the distance of any code is at least <math>1</math>. Besides, the '''distance''' equals the '''[[Hamming weight#Minimum weight|minimum weight]]''' for linear block codes because:{{cn|date=December 2024}}

:<math>\min_{m_1,m_2\in\Sigma^k\atop m_1\neq m_2} \Delta[C(m_1),C(m_2)] = \min_{m_1,m_2\in\Sigma^k\atop m_1\neq m_2} \Delta[\mathbf{0},C(m_2)-C(m_1)] = \min_{m\in\Sigma^k\atop m\neq\mathbf{0}} w[C(m)] = w_\min</math>.

A larger distance allows for more error correction and detection.

For example, if we only consider errors that may change symbols of the sent codeword but never erase or add them, then the number of errors is the number of positions in which the sent codeword and the received word differ.

A code with distance {{mvar|d}} allows the receiver to detect up to <math>d-1</math> transmission errors since changing <math>d-1</math> positions of a codeword can never accidentally yield another codeword. Furthermore, if no more than <math>(d-1)/2</math> transmission errors occur, the receiver can uniquely decode the received word to a codeword. This is because every received word has at most one codeword at distance <math>(d-1)/2</math>. If more than <math>(d-1)/2</math> transmission errors occur, the receiver cannot uniquely decode the received word in general as there might be several possible codewords. One way for the receiver to cope with this situation is to use [[list decoding]], in which the decoder outputs a list of all codewords in a certain radius.

=== Popular notation ===

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== Error detection and correction properties ==

A codeword <math>c \in \Sigma^n</math>could be considered as a point in the <math>n</math>-dimension space <math>\Sigma^n</math> and the code <math>\mathcal{C}</math> is the subset of <math>\Sigma^n</math>. A code <math>\mathcal{C}</math> has distance <math>d</math> means that <math>\forall c\in \mathcal{C}</math>, there is no other codeword in the ''[[Hamming ball'']] centered at <math>c</math> with radius <math>d-1</math>, which is defined as the collection of <math>n</math>-dimension words whose ''[[Hamming distance]]'' to <math>c</math> is no more than <math>d-1</math>. Similarly, <math> \mathcal{C}</math> with (minimum) distance <math>d</math> has the following properties:

* <math> \mathcal{C}</math> can detect <math>d-1</math> errors : Because a codeword <math>c</math> is the only codeword in the Hamming ball centered at itself with radius <math>d-1</math>, no error pattern of <math>d-1</math> or fewer errors could change one codeword to another. When the receiver detects that the received vector is not a codeword of <math> \mathcal{C}</math>, the errors are detected (but no guarantee to correct).

* <math> \mathcal{C}</math> can correct <math>\textstyle\left\lfloor {{d-1} \over 2}\right\rfloor</math> errors. Because a codeword <math>c</math> is the only codeword in the Hamming ball centered at itself with radius <math>d-1</math>, the two Hamming balls centered at two different codewords respectively with both radius <math>\textstyle\left \lfloor {{d-1} \over 2}\right \rfloor</math> do not overlap with each other. Therefore, if we consider the error correction as finding the codeword closest to the received word <math>y</math>, as long as the number of errors is no more than <math>\textstyle\left \lfloor {{d-1} \over 2}\right \rfloor</math>, there is only one codeword in the hamming ball centered at <math>y</math> with radius <math>\textstyle\left \lfloor {{d-1} \over 2}\right \rfloor</math>, therefore all errors could be corrected.

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{{reflist}}

{{refbegin}}

{{Refimprove|date=September 2008}}

* {{cite book | author=J.H. van Lint | authorlink=Jack van Lint | title=Introduction to Coding Theory | edition=2nd | publisher=Springer-Verlag | series=[[Graduate Texts in Mathematics|GTM]] | volume=86 | year=1992 | isbn=3-540-54894-7 | page=[https://archive.org/details/introductiontoco0000lint/page/31 31] | url=https://archive.org/details/introductiontoco0000lint/page/31 }}

* {{cite book | author=F.J. MacWilliams | authorlink=Jessie MacWilliams |author2=N.J.A. Sloane |authorlink2=Neil Sloane | title=The Theory of Error-Correcting Codes | url=https://archive.org/details/theoryoferrorcor0000macw | url-access=registration | publisher=North-Holland | year=1977 | isbn=0-444-85193-3 | page=[https://archive.org/details/theoryoferrorcor0000macw/page/35 35]}}

* {{cite book | author=W. Huffman |author2=V.Pless | authorlink2=Vera Pless | title= Fundamentals of error-correcting codes | url=https://archive.org/details/fundamentalsofer0000huff | url-access=registration | publisher=Cambridge University Press | year=2003 | isbn=978-0-521-78280-7}}

* {{cite book | author=S. Lin |author2=D. J. Jr. Costello | title= Error Control Coding: Fundamentals and Applications | publisher=Prentice-Hall | year=1983 | isbn=0-13-283796-X}}

{{refend}}

== External links ==