Generalized Spatially Coupled Parallel Concatenated Convolutional Codes with Partial Repetition
Paper i proceeding, 2021

We introduce generalized spatially coupled parallel concatenated codes (GSC-PCCs), a class of spatially coupled turbo-like codes obtained by coupling parallel concatenated codes (PCCs) with a fraction of information bits repeated before the PCC encoding. GSC-PCCs can be seen as a generalization of the original spatially coupled parallel concatenated convolutional codes (SC-PCCs) proposed by Moloudi et al. [1]. To characterize the asymptotic performance of GSC-PCCs, we derive the corresponding density evolution equations and compute their decoding thresholds. We show that the proposed codes have some nice properties such as threshold saturation and that their decoding thresholds improve with the repetition factor q. Most notably, our analysis suggests that the proposed codes asymptotically approach the capacity as q tends to infinity with any given constituent convolutional code.


Min Qiu

University of New South Wales (UNSW)

Xiaowei Wu

University of New South Wales (UNSW)

Jinhong Yuan

University of New South Wales (UNSW)

Alexandre Graell I Amat

Chalmers, Elektroteknik, Kommunikations- och antennsystem, Kommunikationssystem

IEEE International Symposium on Information Theory - Proceedings

21578095 (ISSN)

Vol. 2021-July 581-586

2021 IEEE International Symposium on Information Theory, ISIT 2021
Virtual, Melbourne, Australia,



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