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Everything about Convolutional code

Type of error-correcting code using convolution

In telecommunication, a convolutional code is a type of error-correcting code that generates parity symbols via the sliding application of a boolean polynomial function to a data stream. The sliding application represents the 'convolution' of the encoder over the data, which gives rise to the term 'convolutional coding'. The sliding nature of the convolutional codes facilitates trellis decoding using a time-invariant trellis. Time invariant trellis decoding allows convolutional codes to be maximum-likelihood soft-decision decoded with reasonable complexity. Wikipedia →

🧭 Start here: a 6-step reading path

  1. Read the overview: Convolutional codeA 5-minute orientation
  2. Skim a recent paper: Very high resolution canopy height maps from RGB imagery using self-supervised vision transformer and convolutional decoder trained on aerial lidarInfluential work since 2022
  3. Pick up a classic book: Turbo coding for satellite and wireless communicationsThe most-reprinted book on the subject
  4. Read the landmark paper: SegNet: A Deep Convolutional Encoder-Decoder Architecture for Image SegmentationCited 16,741 times
  5. Go sideways: Viterbi decoderA closely related topic
  6. Go sideways: Turbo codeA closely related topic

📖 Definitions

No dictionary entry for this exact phrase.

🗂️ The subject at a glance

  1. History
  2. Where convolutional codes are used
  3. Convolutional encoding
  4. Recursive and non-recursive codes
  5. Impulse response, transfer function, and constraint length
  6. Trellis diagram
  7. Free distance and error distribution
  8. Decoding convolutional codes
  9. Popular convolutional codes
  10. Punctured convolutional codes
  11. Turbo codes: replacing convolutional codes

🏆 Landmark papers (most cited)

🆕 Influential since 2022

📚 Books worth reading

Ranked by number of editions on Open Library, a rough measure of how lasting a book is.

🔗 Related topics