Abstract

It is well known that some harmful objects in the Tanner graph of low-density parity-check (LDPC) codes have a negative impact on their error correction performance under iterative message-passing decoding. Depending on the channel and the decoding algorithm, these harmful objects are different in nature and can be stopping sets, trapping sets, absorbing sets, or pseudocodewords. Differently from LDPC block codes, the design of spatially coupled LDPC codes must take into account the semi-infinite nature of the code, while still reducing the number of harmful objects as much as possible. We propose a general procedure, based on edge spreading, enabling the design of good quasi-cyclic spatially coupled LDPC (QC-SC-LDPC) codes. These codes are derived from quasi-cyclic LDPC (QC-LDPC) block codes and contain a considerably reduced number of harmful objects with respect to the original QC-LDPC block codes. We use an efficient way of enumerating harmful objects in QC-SC-LDPCCs to obtain a fast algorithm that spans the search space of potential candidates to select those minimizing the multiplicity of the target harmful objects. We validate the effectiveness of our method via numerical simulations, showing that the newly designed codes achieve better error rate performance than codes presented in previous literature.

Details

Title
Optimizing quasi-cyclic spatially coupled LDPC codes by eliminating harmful objects
Author
Battaglioni, Massimo 1   VIAFID ORCID Logo  ; Chiaraluce, Franco 1 ; Baldi, Marco 1 ; Pacenti, Michele 2 ; Mitchell, David G. M. 3 

 Università Politecnica delle Marche and CNIT, Dipartimento di Ingegneria dell’Informazione, Ancona, Italy (GRID:grid.7010.6) (ISNI:0000 0001 1017 3210) 
 University of Arizona, Department of Electrical and Computer Engineering, Tucson, USA (GRID:grid.134563.6) (ISNI:0000 0001 2168 186X) 
 New Mexico State University, Klipsch School of Electrical and Computer Engineering, Las Cruces, USA (GRID:grid.24805.3b) (ISNI:0000 0001 0687 2182) 
Pages
67
Publication year
2023
Publication date
Dec 2023
Publisher
Springer Nature B.V.
ISSN
16871472
e-ISSN
16871499
Source type
Scholarly Journal
Language of publication
English
ProQuest document ID
2841697292
Copyright
© The Author(s) 2023. This work is published under http://creativecommons.org/licenses/by/4.0/ (the “License”). Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License.