TY - GEN
T1 - Optimally quantized offset min-sum algorithm for flexible ldpc decoder
AU - Oh, Daesun
AU - Parhi, Keshab K.
PY - 2008
Y1 - 2008
N2 - 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.
AB - 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.
UR - http://www.scopus.com/inward/record.url?scp=70349659467&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=70349659467&partnerID=8YFLogxK
U2 - 10.1109/ACSSC.2008.5074756
DO - 10.1109/ACSSC.2008.5074756
M3 - Conference contribution
AN - SCOPUS:70349659467
SN - 9781424429417
T3 - Conference Record - Asilomar Conference on Signals, Systems and Computers
SP - 1886
EP - 1891
BT - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
T2 - 2008 42nd Asilomar Conference on Signals, Systems and Computers, ASILOMAR 2008
Y2 - 26 October 2008 through 29 October 2008
ER -