On the Design of Generalized LDPC Codes with Component BCJR Decoding

被引:0
|
作者
Liu, Yanfang [1 ]
Olmos, Pablo M. [2 ,3 ]
Mitchell, David G. M. [1 ]
机构
[1] New Mexico State Univ, Klipsch Sch Elect & Comp Engn, Las Cruces, NM 88003 USA
[2] Univ Carlos III Madrid, Madrid, Spain
[3] Gregorio Maranon Hlth Res Inst, Madrid, Spain
来源
2020 IEEE GLOBAL COMMUNICATIONS CONFERENCE (GLOBECOM) | 2020年
基金
美国国家科学基金会; 欧洲研究理事会;
关键词
Generalized low-density parity-check codes; BCJR decoding; trellis of linear block codes; TRELLIS;
D O I
10.1109/GLOBECOM42002.2020.9322143
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Generalized low-density parity-check (GLDPC) codes, where the single parity-check (SPC) nodes are replaced by generalized constraint (GC) nodes, are known to offer a reduced gap to capacity when compared with conventional LDPC codes, while also maintaining linear growth of minimum distance. However, for certain classes of practical GLDPC codes, there remains a gap to capacity even when utilizing blockwise decoding algorithm at GC nodes. In this work, we propose to optimize the design of GLDPC codes where the GC nodes are decoded with a trellis-based bit-wise Bahl-Cocke-Jelinek-Raviv (BCJR) component decoding algorithm. We analyze the asymptotic threshold behavior of GLDPC codes and determine the optimal proportion of the GC nodes in the GLDPC Tanner graph. We show significant performance improvements compared to existing designs with the same order of decoding complexity.
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页数:6
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