# Why Convolutional codes is easy to factor/handle the uncertainty of a bit being a 0 or a 1 into the decoding?

Here is an excerpt from Andrew S. Tanenbaum, Computer Networks, 5th edition, Chapter 3 (The data link layer), Page 208:

[Convolutional codes have been popular in practice because it is easy to factor the uncertainty of a bit being a 0 or a 1 into the decoding.]

Why is it easy to use convolutional codes to factor the uncertainty of a bit?

Is it because the convolutional code circuit is designed in such way as to handle uncertainty properly? I couldn't really find the exact answer. I think the answer has something related to the fact that a convolutional code is not a linear code but I couldn't really understand exactly why a convolutional code is special to handle uncertainty.

• I'm not sure how to explain the answer easily without introducing new concepts. I suggest you study the decoding algorithm for convolutional codes, and understand how that works before asking about these details.
– D.W.
Commented May 25, 2020 at 3:04

An important idea with convolutional codes is that the output sequences of bits (of the convolutional coder) consists of sequences of bits that are correlated with one another, i.e., not independent. Hence, in the receiver side, you know that, given what the convolutional coder is, the sequence of bits can only be some sequences, out of the big set of possibilities. Imagine a big space (say, it may be easier to imagine in 2 or 3 dimensions, then just imagine it gets extended to more dimensions), that has many points in it with integer coordinates, e.g., (1,0,1,1,0), but only only a few of these are allowed possibilities. So you look for the maximum likelihood sequence, which you could think of as the allowed point with the highest probability of having been the input to the convolutional coder.