Hi!
Please consider using "Guessing Random Additive Noise Decoding" (GRAND) when
decoding whatever digital modes.
-
Expect that all existing ECC-software can be replaced by this (universal)
ECC-software (or hardware if used); "Guessing Random Additive Noise Decoding"
(GRAND) - article mentioning:
September 14, 2021, New Chip [but also as software] Can Decode Any Type of Data
Sent Across a Network:
https://scitechdaily.com/new-chip-can-decode-any-type-of-data-sent-across-a-network/
<https://scitechdaily.com/new-chip-can-decode-any-type-of-data-sent-across-a-network/>
Citat: "...
Since the 1950s, most error-correcting codes and decoding algorithms have been
designed together. Each code had a structure that corresponded with a
particular, highly complex decoding algorithm, which often required the use of
dedicated hardware.
Researchers at MIT, Boston University, and Maynooth University in Ireland have
now created the first silicon chip that is able to decode any code, regardless
of its structure, with maximum accuracy, using a universal decoding algorithm
called Guessing Random Additive Noise Decoding (GRAND). By eliminating the need
for multiple, computationally complex decoders, GRAND enables increased
efficiency that could have applications in augmented and virtual reality,
gaming, 5G networks, and connected devices that rely on processing a high
volume of data with minimal delay.
...
One way to think of these codes is as redundant hashes (in this case, a series
of 1s and 0s) added to the end of the original data. The rules for the creation
of that hash are stored in a specific codebook.
As the encoded data travel over a network, they are affected by noise, or
energy that disrupts the signal, which is often generated by other electronic
devices. When that coded data and the noise that affected them arrive at their
destination, the decoding algorithm consults its codebook and uses the
structure of the hash to guess what the stored information is.
Instead, GRAND works by guessing the noise that affected the message, and uses
the noise pattern to deduce the original information. GRAND generates a series
of noise sequences in the order they are likely to occur, subtracts them from
the received data, and checks to see if the resulting codeword is in a codebook.
...
The GRAND chip uses a three-tiered structure, starting with the simplest
possible solutions in the first stage and working up to longer and more complex
noise patterns in the two subsequent stages. Each stage operates independently,
which increases the throughput of the system and saves power.
The device is also designed to switch seamlessly between two codebooks. It
contains two static random-access memory chips, one that can crack codewords,
while the other loads a new codebook and then switches to decoding without any
downtime.
The researchers tested the GRAND chip and found it could effectively decode any
moderate redundancy code up to 128 bits in length, with only about a
microsecond of latency.
Médard and her collaborators had previously demonstrated the success of the
algorithm, but this new work showcases the effectiveness and efficiency of
GRAND in hardware for the first time.
...
Since GRAND only uses codebooks for verification, the chip not only works with
legacy codes but could also be used with codes that haven’t even been
introduced yet.
…"
September 9 2021, A universal system for decoding any type of data sent across
a network.
New chip eliminates the need for specific decoding hardware, could boost
efficiency of gaming systems, 5G networks, the internet of things, and more:
https://news.mit.edu/2021/grand-decoding-data-0909
<https://news.mit.edu/2021/grand-decoding-data-0909>
https://www.granddecoder.mit.edu/ <https://www.granddecoder.mit.edu/>
Muriel Medard:
https://en.wikipedia.org/wiki/Muriel_M%C3%A9dard
<https://en.wikipedia.org/wiki/Muriel_M%C3%A9dard>
ECC incl. FEC:
https://en.wikipedia.org/wiki/Error_correction_code
<https://en.wikipedia.org/wiki/Error_correction_code>
-
1 time 19 min:
23. maj 2021, It’s All in the Noise: Universal Noise-Centric Decoding | IEEE
Montreal Keynote Event:
https://www.youtube.com/watch?v=QbPfylinEXU
<https://www.youtube.com/watch?v=QbPfylinEXU>
1 time video:
7. sep. 2020, Prof. Muriel Médard - Guessing Random Additive Noise Decoding
(GRAND):
https://www.youtube.com/watch?v=IWVQl_Bn4gE
<https://www.youtube.com/watch?v=IWVQl_Bn4gE>
FIU SCIS Distinguished Lecture Series: Guessing Random Additive Noise
Decoding(GRAND)- Muriel Medard:
https://www.youtube.com/watch?v=6iRCbu-Iozw
<https://www.youtube.com/watch?v=6iRCbu-Iozw>
23. okt. 2020, Muriel Medard: Guessing Random Additive Noise Decoding (GRAND)
(Keynote Address):
https://www.youtube.com/watch?v=WA1JmV7hhPw
<https://www.youtube.com/watch?v=WA1JmV7hhPw>
Reliable Communication over Noisy Channels by Guessing Random Additive Noise
Decoding (GRAND):
https://www.youtube.com/watch?v=U1QlmXqYN1A
<https://www.youtube.com/watch?v=U1QlmXqYN1A>
-
Articles:
23 Aug 2021, Guessing random additive noise decoding with symbol reliability
information (SRGRAND):
https://arxiv.org/abs/1902.03796 <https://arxiv.org/abs/1902.03796>
22 Mar 2019, Capacity-achieving Guessing Random Additive Noise Decoding (GRAND):
https://arxiv.org/abs/1802.07010 <https://arxiv.org/abs/1802.07010>
IEEE Transactions on Information Theory ( Volume: 65, Issue: 7, July 2019 pp.
4023-4040): "Capacity-Achieving Guessing Random Additive Noise Decoding”:
https://ieeexplore.ieee.org/document/8630851
<https://ieeexplore.ieee.org/document/8630851>
GRAND Duffy, Li & Medard, IEEE ISIT, 2018; IEEE Trans Inf Theory, 2019, An,
Medard, Duffy, preprint, 2020.
SRGRAND Duffy & Medard, IEEE ISIT, 2019; Duffy, Solomon, Konwar & Medard, CISS,
2020; Duffy, Medard & An, arXiv: 1902.03796;
https://arxiv.org/abs/1902.03796 <https://arxiv.org/abs/1902.03796>
ORBGRAND Duffy, arXiv:2001.00546, to appear ICASSP 2021;
https://arxiv.org/abs/2001.00546 <https://arxiv.org/abs/2001.00546>
SGRAND Solomon, Duffy & Medard, IEEE ICC, 2020.
--
best regards,
Glenn, OZ1HFT
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