文档介绍：Choice of Encoder Class
The answer to the first question depends on the application. For example, many applications require that the encoder be systematic so that the data are readily observable in the code stream. As another example, parallel turbo codes (Chapter 7) require that the constituent convolutional codes be of the recursive type,and usually systematic. For many applications the encoder class matters very little,particularly applications in which the convolutional code is not a constituentcode of a turbo(-like) code. As seen in Example and as we shall see in the discussion below of the third question, the choice of encoder class can affect the encoder memory μ.
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Catastrophic Encoders
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Minimal Encoders
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Design of Convolutional Codes
Regarding the fourth question listed in Section , for reasons affecting decoder complexity, typical values of n and k are very small: k =1, 2, 3 and n = 2, 3, 4. Typical code rates are 1/2, 1/3, 1/4, 2/3, and 3/4, with 1/2 by far the most common rate.
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Alternative Convolutional Code Representations
Under this section, we consider alternative representations of convolutional codes that are useful for many other aspects of convolutional codes, such as
decoding, code design, and analysis.
Convolutional Codes as Semi-Infinite Linear Codes
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