Abstract
In this paper we propose a uniformly reweighted a posteriori probability (APP) decoder. The APP decoder is well-known to be suboptimal compared to the BP decoder. Here, we derive the APP decoder as an algorithm of approximate Bayesian inference on the LDPC code graph and introduce a correction parameter to overcome the suboptimaly of the APP decoder. We optimize numerically the correction parameter and show that it improves the BER performance of the APP decoder compared to its non-corrected version. In addition, the original APP decoder requires memory that is linear in the number of edges in the code graph. Here, we propose a memory efficient implementation of the algorithm that requires memory that is linear only in the codeword length.
| Original language | English (US) |
|---|---|
| Title of host publication | 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 1228-1232 |
| Number of pages | 5 |
| ISBN (Print) | 9781479980093 |
| DOIs | |
| State | Published - Jan 30 2014 |
| Event | 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 - Monticello, United States Duration: Sep 30 2014 → Oct 3 2014 |
Other
| Other | 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014 |
|---|---|
| Country | United States |
| City | Monticello |
| Period | 9/30/14 → 10/3/14 |
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ASJC Scopus subject areas
- Computer Networks and Communications
- Computer Science Applications
Cite this
Uniformly reweighted APP decoder for memory efficient decoding of LDPC Codes. / Ilic, Velimir; Dupraz, Elsa; Declercq, David; Vasic, Bane V.
2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014. Institute of Electrical and Electronics Engineers Inc., 2014. p. 1228-1232 7028595.Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Uniformly reweighted APP decoder for memory efficient decoding of LDPC Codes
AU - Ilic, Velimir
AU - Dupraz, Elsa
AU - Declercq, David
AU - Vasic, Bane V
PY - 2014/1/30
Y1 - 2014/1/30
N2 - In this paper we propose a uniformly reweighted a posteriori probability (APP) decoder. The APP decoder is well-known to be suboptimal compared to the BP decoder. Here, we derive the APP decoder as an algorithm of approximate Bayesian inference on the LDPC code graph and introduce a correction parameter to overcome the suboptimaly of the APP decoder. We optimize numerically the correction parameter and show that it improves the BER performance of the APP decoder compared to its non-corrected version. In addition, the original APP decoder requires memory that is linear in the number of edges in the code graph. Here, we propose a memory efficient implementation of the algorithm that requires memory that is linear only in the codeword length.
AB - In this paper we propose a uniformly reweighted a posteriori probability (APP) decoder. The APP decoder is well-known to be suboptimal compared to the BP decoder. Here, we derive the APP decoder as an algorithm of approximate Bayesian inference on the LDPC code graph and introduce a correction parameter to overcome the suboptimaly of the APP decoder. We optimize numerically the correction parameter and show that it improves the BER performance of the APP decoder compared to its non-corrected version. In addition, the original APP decoder requires memory that is linear in the number of edges in the code graph. Here, we propose a memory efficient implementation of the algorithm that requires memory that is linear only in the codeword length.
UR - http://www.scopus.com/inward/record.url?scp=84946685314&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=84946685314&partnerID=8YFLogxK
U2 - 10.1109/ALLERTON.2014.7028595
DO - 10.1109/ALLERTON.2014.7028595
M3 - Conference contribution
AN - SCOPUS:84946685314
SN - 9781479980093
SP - 1228
EP - 1232
BT - 2014 52nd Annual Allerton Conference on Communication, Control, and Computing, Allerton 2014
PB - Institute of Electrical and Electronics Engineers Inc.
ER -