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I am currently taking an online course on probabilistic graphical models. In the section on belief propagation (BP), specifically loopy BP, reference was made to Robert Mc Eliece's 1988 paper Turbo Decoding as an Instance of Pearl’s “Belief Propagation” Algorithm and turbo decoding.

As I understand it, the key breakthrough with turbo decoding is that one can obtain greater channel throughput by operating closer to the theoretical limit of attainability as given by Shannon's theorem. This increased throughput is achieved at the cost of greater computational complexity in the decoder.

Further I understand that turbo decoding has become widespread and virtually ubiquitous in modern communication channels.

Is my understanding correct?

Also is this currently an active field with development of new decoding algorithms or has it stabilized?

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It seems like a better fit somewhere like the Computer-Science Theory Stack-exchange – Connor Wolf Apr 5 '12 at 6:55
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Gee, I thought channel coding and in particular the Shannon–Hartley theorem were integral to EE? en.wikipedia.org/wiki/Shannon%E2%80%93Hartley_theorem – JonnyBoats Apr 5 '12 at 10:57
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@FakeName Communication schemes are very much on-topic here, they are even specifically listed in the FAQ. – Kellenjb Apr 5 '12 at 13:29
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I think it belongs here more than anywhere else as strictly speaking it is communication engineer which is generally part of electrical/electronics .... – smashtastic Apr 5 '12 at 14:09
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I'd consider this on topic here, but in terms of who's around to answer the question, dsp.stackexchange.com might be at least as productive. – The Photon Apr 5 '12 at 15:34
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It has been a long time since I studied turbo codes and at the time novel decoding algorithms was a key area of development. Most of the improvements are evolutionary rather revolutionary.

your statement about them being used to optimise channel throughput and obtain rates closer to the Shannon limit is correct and the decoding side is computationally intensive.

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