2020 IEEE International Symposium
on Information Theory
21-26 June 2020 • Los Angeles, California, USA
| Paper ID | C.8.4 | ||
| Paper Title | Generalized LDPC Codes with Convolutional Code Constraints | ||
| Authors | Muhammad Umar Farooq, Lund University, Sweden; Saeedeh Moloudi, Ericsson, Sweden; Michael Lentmaier, Lund University, Sweden | ||
| Session | C.8: Spatially Coupled Codes | ||
| Presentation | Lecture | ||
| Track | Coding for Communications | ||
| Manuscript | Click here to download the manuscript | ||
| Virtual Presentation | Click here to watch in the Virtual Symposium | ||
| Abstract | Braided convolutional codes (BCCs) are a class of spatially coupled turbo-like codes that can be described by a (2,3)-regular compact graph. In this paper, we introduce a family of (dv, dc)-regular GLDPC codes with convolutional code constraints (CC-GLDPC codes), which form an extension of classical BCCs to arbitrary regular graphs. In order to characterize the performance in the waterfall and error floor regions, we perform an analysis of the density evolution thresholds as well as the finite-length ensemble weight enumerators and minimum distances of the ensembles. In particular, we consider various ensembles of overall rate R= 1/3 and R= 1/2 and study the trade-off between variable node degree and strength of the component codes. We also compare the results to corresponding classical LDPC codes with equal degrees and rates. It is observed that for the considered LDPC codes with variable node degree dv>2, we can find a CC-GLDPC code with smaller dv that offers similar or better performance in terms of BP and MAP thresholds at the expense of a negligible loss in the minimum distance. | ||
Plan Ahead
2021 IEEE International Symposium on Information Theory
11-16 July 2021 | Melbourne, Victoria, Australia
