Are there any LDPC implementations out there that aren't patent encumbered?
73-KY9K/Brian
On Mar 6, 2013 10:05 AM, "Rick Muething" <[email protected]> wrote:
> Daniel,
>
> RS and similar block codes are fairly efficient and have some nice
> properties especially when mixed (layered) with other types of FEC. E.g.
> Viterbi (convolutional) type decoders work well with random errors. But
> these type codes perform poorly in burst error situations. Sometimes if
> the timing permits bursts can be reduced by interleaving but there are
> limits especially when you don’t want to delay the signal much in time as
> in the case of digital voice. In such cases adding a block code “outside”
> the convolutional codes can be effectively in many systems.
>
> Reed Solomon adds two “parity” characters for each carrier correction
> desired. ( a character can be any number of bits from 2 on up although
> often is done with 8 bit characters) E.g. if I were sending 8 bit
> characters and I wanted to correct up to 8 character errors I would have to
> add 16 8 bit “parity” characters to my data and these could correct up to
> 8 character errors in the entire block of data (data + Parity). The amount
> of Parity you need is a function of the channel and the error rates. So
> the “efficiency” of a RS type code is a function of how many errors you
> wish to be able to correct. For example if I were sending a block of 100
> data characters and wished to correct up to 8 erroneous characters I would
> need to add 16 total parity characters so my overall efficiency would be
> 100/116 or about 86% which is reasonable. As the number of corrected
> characters desired increases the efficiency of course goes down but the
> robustness increases. Correcting up to 32 characters would require 64
> characters of Parity so the efficiency would be 100/164 or about 61%. The
> beauty of RS and other similar block codes is they are tolerant of block
> errors. It corrects by character whether there is one bit in error or 8
> bits in error of the character. So it compliments the convolutional code
> nicely by correcting bursts that the convolutional code can’t correct.
>
> This is why layering two types of FEC is effective and why for example
> NASA often uses layered block coding on top of convolutional coding in very
> weak signal transmission.
>
> In the end the amount and selection of FEC is a function of the channel
> and the type and number and type of errors expected. But in general adding
> the correct type and level of FEC can usually provide a net improvement
> over uncoded systems in terms of net BER. This is usually expressed as
> equivalent dB improvement. (the amount of improvement you would get by
> increasing the S/N by the same number of dB.
>
> In digital Voice we have another issue in that unlike in binary message
> transmission some level of uncorrected errors may be acceptable (resulting
> in some speech artifact which may not severely impact intelligibility).
>
> I have experimented with this a lot in the development of WINMOR and often
> optimization is the result of iterating different promising FEC coding and
> evaluating them over specific (some times standardized CCIR) channels using
> a HF channel simulator. Prediction with theory alone is possible on White
> Gaussian Noise channels but we seldom see these channels in HF propagation.
>
> 73,
>
> Rick Muething, KN6KB
>
>
>
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Symantec Endpoint Protection 12 positioned as A LEADER in The Forrester
Wave(TM): Endpoint Security, Q1 2013 and "remains a good choice" in the
endpoint security space. For insight on selecting the right partner to
tackle endpoint security challenges, access the full report.
http://p.sf.net/sfu/symantec-dev2dev
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