> Now I'm wondering why I didn't get any segmentation faults.
You should be able to reproduce this by loading the alist file from the
reference site
http://www.inference.phy.cam.ac.uk/mackay/codes/alist.html (that example may
not be a good LDPC example, but should at minimum cause a fault in unfixed
alist.cc)
The next question (tl;dr) about LDPC may not be an actual bug, but I don't have
enough
knowledge of this topic to know for sure. All I know about the error correcting
codes has been learned through experimentation and trial and error...
One of the error correcting codes used in P25 has a 4x8 generator matrix and
I've
been able successfully to get numpy to generate code words that match what we've
seen over the air from analysis of actual P25 TDMA traffic. When I tried to
generate
the set of all possible code words using LDPC it produced a very interesting
result
(see below). It appears that the codewords that gr-ldpc generates really are
the same
as the ones used in P25, however the generated parity bits appear before the
user
data bits, instead of as in P25 where the parity bits are appended after the
original
data bits.
data P25 gr-ldpc
word codeword codeword
==== ======== ========
0 00000000 00000000
1 00010111 11010001
2 00101110 01110010
3 00111001 10100011
4 01001011 10110100
5 01011100 01100101
6 01100101 11000110
7 01110010 00010111
8 10001101 11101000
9 10011010 00111001
10 10100011 10011010
11 10110100 01001011
12 11000110 01011100
13 11010001 10001101
14 11101000 00101110
15 11111111 11111111
The "problem" is that if we receive say, P25 codeword 01011100 we want it to
decode
to 5 (0101) whereas if gr-ldpc is called upon to decode 01011100 its answer is
12 .
In this small example we could clean up afterwords by adding a lookup table
(4 bits in, 4 bits out) to map the result back to the proper value, but it's
not clear
that would be generalizable.
I've pasted the python code below that's used to generate the second column in
the
table above - the example shown is for dataword='0101' (5)
>>> import numpy as np
>>>
>>> g = np.array(np.mat('1 0 0 0 1 1 0 1; 0 1 0 0 1 0 1 1; 0 0 1 0 1 1 1 0; 0 0
>>> 0 1 0 1 1 1'))
>>>
>>> codeword = np.dot([0,1,0,1], g) % 2
>>>
>>> print codeword
[0 1 0 1 1 1 0 0]
>>>
The question (_if_ I understand things correctly) seems to be : how reasonable
/ unreasonable is it for users of the
library to be picky about the exact ordering of the parity bits in the
generated codewords?
Thx again Manu
Best
Max
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