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Technical Program

Paper Detail

Paper IDD2-S2-T2.1
Paper Title Generalized Spatially Coupled Parallel Concatenated Convolutional Codes With Partial Repetition
Authors Min Qiu, Xiaowei Wu, Jinhong Yuan, University of New South Wales, Australia; Alexandre Graell i Amat, Chalmers University of Technology, Sweden
Session D2-S2-T2: Spatial Coupling & Protograph Codes
Chaired Session: Tuesday, 13 July, 22:20 - 22:40
Engagement Session: Tuesday, 13 July, 22:40 - 23:00
Abstract We introduce generalized spatially coupled parallel concatenated convolutional 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.