What is recorded here?
Berrou, Glavieux and Thitimajshima combine interleaved recursive convolutional encoders with iterative soft-information decoding and report close-to-channel-limit error performance under a specified long-block Gaussian-channel simulation. A noisy message can be encoded twice, with the second encoder seeing its bits in a different order. Two decoders then exchange information about uncertain bits. Each tries to pass new evidence rather than simply repeating the same received information. This paper shows striking simulation performance for a carefully chosen code, channel, long interleaver and iteration schedule. The exchange is approximate: more iterations can worsen results at low signal levels, and long blocks require memory and delay. The result opens a powerful coding route without proving every such decoder reaches channel capacity.
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Scientific scope
Exact 1993 ICC conference paper 1064-1070/PDF 1-7 all original technical/annex/reference text read. Parallel recursive convolutional codes, interleaving and iterative extrinsic soft information use discrete Gaussian memoryless/binary-channel assumptions and approximate weak correlation/Gaussian feedback. Reported Monte Carlo uses rate 1/2, componentrate 2/3, constraintlength 5/16 states,65536-bit 256 x 256 interleaver,128 blocks and iterations up to 18. Close-to-limit headline is specific reported performance, not universal capacity/global convergence or hardware-efficiency proof. Low-SNR BER can worsen with iteration; weighting/interleaver choices and storage/delay matter. No exact headline Eb/N0 value or independently certified formula transcription is supplied here. Crossref date is null;1993 established by source copyright/conference identity. No independent certification.
Read the original work
- Berrou, Glavieux and Thitimajshima: iterative turbo error-correcting codes; exact original contribution text
- IEEE-deposited exact turbo-code conference identity
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People and systems
Claude Berrou; Alain Glavieux; Punya Thitimajshima
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English catalogue narrative
Berrou, Glavieux and Thitimajshima: iterative turbo error-correcting codes
Berrou, Glavieux and Thitimajshima combine interleaved recursive convolutional encoders with iterative soft-information decoding and report close-to-channel-limit error performance under a specified long-block Gaussian-channel simulation.
A noisy message can be encoded twice, with the second encoder seeing its bits in a different order. Two decoders then exchange information about uncertain bits. Each tries to pass new evidence rather than simply repeating the same received information. This paper shows striking simulation performance for a carefully chosen code, channel, long interleaver and iteration schedule. The exchange is approximate: more iterations can worsen results at low signal levels, and long blocks require memory and delay. The result opens a powerful coding route without proving every such decoder reaches channel capacity.
Scientific scope
Exact 1993 ICC conference paper 1064-1070/PDF 1-7 all original technical/annex/reference text read. Parallel recursive convolutional codes, interleaving and iterative extrinsic soft information use discrete Gaussian memoryless/binary-channel assumptions and approximate weak correlation/Gaussian feedback. Reported Monte Carlo uses rate 1/2, componentrate 2/3, constraintlength 5/16 states,65536-bit 256 x 256 interleaver,128 blocks and iterations up to 18. Close-to-limit headline is specific reported performance, not universal capacity/global convergence or hardware-efficiency proof. Low-SNR BER can worsen with iteration; weighting/interleaver choices and storage/delay matter. No exact headline Eb/N0 value or independently certified formula transcription is supplied here. Crossref date is null;1993 established by source copyright/conference identity. No independent certification.
People and systems
Claude Berrou; Alain Glavieux; Punya Thitimajshima