Coarsely Quantized Layered Decoding Using the Information Bottleneck Method

Publikationstyp
Conference Paper
Date Issued
2021-06
Sprache
English
Author(s)
Mohr, Philipp  orcid-logo
Bauch, Gerhard  
Yu, Fan  
Li, Mo  
Institut
Nachrichtentechnik E-8  
TORE-URI
http://hdl.handle.net/11420/10437
Citation
IEEE International Conference on Communications (ICC 2021)
Contribution to Conference
IEEE International Conference on Communications, ICC 2021  
Publisher DOI
10.1109/ICC42927.2021.9500593
Scopus ID
2-s2.0-85115706449
In recent years coarsely quantized LDPC decoding using a flooding schedule has been extensively studied. However, there exist few works addressing coarse quantization for a layered schedule, which enables improved convergence speed of the message passing algorithm. The layered schedule can especially be beneficial for high throughput applications like fiber optical systems. This paper presents innovative layered decoding approaches, where the information bottleneck method is used for the design of different coarsely quantized decoder architectures. The varieties of investigated node implementations include lookup tables, computational domain techniques as well as reduced complexity approximations. All structures are designed offline using a layered discrete density evolution method. The performance of multiple node architectures is investigated in terms of evolution of mutual information in the design phase and in terms of error rates. We focus in this paper on regular quasi-cyclic codes. Our simulations running on GPUs also allow insights into the error floor behavior.