  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.
