Standards/convolutional
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= Coder = | = Coder = | ||
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+ | == Non-recursive encoder == | ||
The following picture shows a (2, 1, 3) convolutional encoder | The following picture shows a (2, 1, 3) convolutional encoder | ||
− | with generator polynomials G<sub>1</sub> = 111 and G<sub>2</sub> = 101 : | + | with generator polynomials G<sub>1</sub> = 111 and G<sub>2</sub> = 101 : |
[[File:Convolutional encoder 2-1-3.svg|center|Convolutional encoder (2,1,3)]] | [[File:Convolutional encoder 2-1-3.svg|center|Convolutional encoder (2,1,3)]] | ||
+ | |||
+ | The graph of the convolutional encoder is presented in the following picture : | ||
+ | |||
+ | [[File:Convolutional encoder 2-1-3 graph.svg |center|Convolutional encoder (2,1,3) graph]] | ||
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+ | |||
+ | == Punctured encoder == | ||
= Decoders = | = Decoders = | ||
+ | |||
+ | [[Category:Standards]] [[Category:Codes]] |
Latest revision as of 16:10, 21 July 2016
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Convolutional codes are used in communication systems for error correction. They allow to have a very low Bit Error Rate (BER) and are preferably used in the case of noisy channels.
These codes are often implemented in concatenation with a hard-decision code, such as Reed Solomon.
Definitions
A convolutional code is specified by:
-
n
: number of output bits -
k
: number of input bits -
m
: number of registers -
Gi
: then
generator polynomials
Coder
Non-recursive encoder
The following picture shows a (2, 1, 3) convolutional encoder with generator polynomials G1 = 111 and G2 = 101 :
The graph of the convolutional encoder is presented in the following picture :