Optimally quantized offset min-sum algorithm for flexible ldpc decoder

Daesun Oh, Keshab K. Parhi

Research output: Chapter in Book/Report/Conference proceedingConference contribution

11 Scopus citations

Abstract

In this paper, we analyze the performance of quantized offset min-sum (MS) decoding algorithm and propose an optimally quantized offset MS algorithm for a flexible low-density paritycheck (LDPC) decoder. It is known that the offset MS decoding algorithm is implemented with simplified hardware complexity and achieves good decoding performance. However, the finite precision effects in decoding LDPC codes result in performance different from floating point. The performance degradation is caused by different dynamic ranges of input data at high signal-to-noise ratio (SNR). The proposed offset MS algorithm uses the received data directly instead of loglikelihood ratio (LLR) data as the intrinsic information. It can achieve better performance than the conventional one since its offset factor is more effective at a wide range of SNR and the intrinsic information is quantized more robustly since it is independent of channel information. Also, it is possible for the proposed scheme to use a same quantization scheme for a flexible LDPC decoder, which can decode several kinds of LDPC codes. Simulation results show that our optimally quantized offset MS algorithms with 5-bits for (1728, 864) and (1728, 1296) irregular LDPC codes achieve better performance compared with the conventional offset MS algorithms with 6-bits quantization scheme.

Original languageEnglish (US)
Title of host publication2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Pages1886-1891
Number of pages6
DOIs
StatePublished - 2008
Event2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008 - Pacific Grove, CA, United States
Duration: Oct 26 2008Oct 29 2008

Publication series

NameConference Record - Asilomar Conference on Signals, Systems and Computers
ISSN (Print)1058-6393

Other

Other2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Country/TerritoryUnited States
CityPacific Grove, CA
Period10/26/0810/29/08

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