D. MacKay's Gallager code resources
Questions about
David MacKay's Sparse graph code resources are answered here.
Contents:
Other useful sites
All David MacKay's papers can be found here,
and his textbook on information theory is here: Information Theory, Probability and Neural Networks | Canada mirror
Matrices `A', `Cn', and `G' are respectively
the parity check matrix (in list format),
the right hand square bit of A,
and the generator matrix for the code.
Format for raw results
The following format is used in SOME of the raw results
files, in particular, the Tanner Product code
results.
Column Heading Meaning
============================================================
1 ebno Literal value of Eb/No
2 (dB) Eb/No expressed in decibels
3 distance A crude measure of how far we are from the shannon limit
4 C The capacity of the present channel
5 R The Rate of the code (assumed value)
6 x s.n.r. of Gaussian channel.
(The input to the channel is +/- x, and the added noise
has standard deviation 1.)
7 errors Total number of blocks decoded erroneously
8 trials Number of blocks simulated
9 undet Number of UNDETECTED errors
10 blep Point estimate of block error probability
11 point Alternate point estimate of block error probability
12 upper Error bar
13 lower Error bar
14 bitsw Number of bits received in error ("bits wrong")
15 undet Number of bit errors in the "undetected" community.
16 bitep:point Bit error rate
17 upper Error bar
18 lower Error bar
19 maxloops Number of loops of sum-product at which algorithm halts
and declares detected error
20 mean_lps Mean number of loops needed to get valid decoding
21 K K
22 N N
23-27 loop05:25:50:75:95 The 5th, 25th, 50th, 75th, 95th percentiles of the number of
loops needed to get valid decoding.
The work of the inference group is supported by
an award from IBM Zurich research laboratory, and by
the Gatsby charitable foundation.