Convolutional code: Difference between revisions

Revision as of 04:56, 29 July 2021

Revision as of 23:00, 2 August 2021

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{{see also|Viterbi algorithm}}

[[File:Convolutional codes PSK QAM LLR.svg|thumb|right|300px| Bit error ratio curves for convolutional codes with different options of digital modulations ([[Phase-shift keying|QPSK, 8-PSK]], [[Quadrature amplitude modulation|16-QAM, 64-QAM]]) and [[Likelihood_function#Log-likelihood|LLR]] Algorithms.<ref>[https://www.mathworks.com/help/comm/examples/llr-vs-hard-decision-demodulation.html LLR vs. Hard Decision Demodulation (MathWorks)]</ref><ref>[https://www.mathworks.com/help/comm/ug/estimate-ber-for-hard-and-soft-decision-viterbi-decoding.html Estimate BER for Hard and Soft Decision Viterbi Decoding (MathWorks)]</ref>. (Exact<ref>[https://www.mathworks.com/help/comm/ug/digital-modulation.html#brc6yjx Digital modulation: Exact LLR Algorithm (MathWorks)]</ref> and Approximate<ref>[https://www.mathworks.com/help/comm/ug/digital-modulation.html#brc6ymu Digital modulation: Approximate LLR Algorithm (MathWorks)]</ref>) over additive white Gaussian noise channel.]]

Several [[algorithm]]s exist for decoding convolutional codes. For relatively small values of ''k'', the [[Viterbi algorithm]] is universally used as it provides [[maximum likelihood]] performance and is highly parallelizable. Viterbi decoders are thus easy to implement in [[VLSI]] hardware and in software on CPUs with [[SIMD]] instruction sets.