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Skew Convolutional Codes

Sidorenko, Vladimir; Li, Wenhui; Günlü, Onur; Kramer, Gerhard

A new class of convolutional codes, called skew convolutional codes, that extends the class of classical fixed convolutional codes, is proposed. Skew convolutional codes can be represented as periodic time-varying convolutional codes but have a description as compact as fixed convolutional codes. Designs of generator and parity check matrices, encoders, and code trellises for skew convolutional codes and their duals are shown. For memoryless channels, one can apply Viterbi or BCJR decoding algorithms, or a dualized BCJR algorithm, to decode skew convolutional codes.
Published in: Entropy, 10.3390/e22121364, MDPI