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Journal of Xidian University

Dynamic extended mim-sum decoding algorithm for Q-ary LDPC codes

Xuepeng Wang

Published Jan 1, 2012• 0 citations
OpenAlex

Abstract

Decoded with the extended min-sum(EMS) algorithm,q-ary LDPC codes suffer great performance degradation compared with that decoded with the q-ary sum-product algorithm(QSPA) in case the length nm of message vectors is too small.To solve this problem,a dynamic EMS(D-EMS) algorithm is proposed in this paper.First,we examined the distribution of likelihood values among GF(q) symbols in the message vectors,and concluded that the likelihood values would concentrate to a small portion of symbols as the iteration number increases.Therefore,the D-EMS algorithm first set the length of message vectors to nm1,then truncate it to nm2 after certain decoding iterations,thus the decoding computational complexity can be efficiently reduced.Meanwhile,in order to reduce the complexity of real comparisons in the decoder,the proposed algorithm employs the bubble check(BC) algorithm during the check node elementary steps.Complexity analysis and simulation results indicate that,under appropriate parameter configurations,while efficiently reducing the decoding complexity of the EMS algorithm,the D-EMS algorithm performs nearly as well as the corresponding EMS algorithm over both AWGN and Rayleigh fading channels,and thus can be efficiently applied to practical communication systems based on q-ary LDPC codes.

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Decoded with the extended min-sum(EMS) algorithm,q-ary LDPC codes suffer great performance degradation compared with that decoded with the q-ary sum-product algorithm(QSPA) in case the length nm of message vectors is too small.To solve this problem,a dynamic EMS(D-EMS) algorithm is proposed in this paper.First,we examined the distribution of likelihood values among GF(q) symbols in the message vectors,and concluded that the likelihood values would concentrate to a small portion of symbols as the iteration number increases.Therefore,the D-EMS algorithm first set the length of message vectors to nm1,then truncate it to nm2 after certain decoding iterations,thus the decoding computational complexity can be efficiently reduced.Meanwhile,in order to reduce the complexity of real comparisons in the decoder,the proposed algorithm employs the bubble check(BC) algorithm during the check node elementary steps.Complexity analysis and simulation results indicate that,under appropriate parameter configurations,while efficiently reducing the decoding complexity of the EMS algorithm,the D-EMS algorithm performs nearly as well as the corresponding EMS algorithm over both AWGN and Rayleigh fading channels,and thus can be efficiently applied to practical communication systems based on q-ary LDPC codes.
The extended min-sum (EMS) algorithm is adopted for non-binary low density parity check (NB-LDPC) codes. The high complexity of EMS algorithm is a hot topic in recent years. Aiming at the problem, a low-complexity EMS algorithm based on NB-LDPC codes is proposed. Dynamic bubble-check (DBC) algorithm in elementary check node (ECN) steps is adopted to reduce the complexity of check node. Furthermore, the proposed algorithm dynamically truncates the length of the message vector by the number of decoding iterations. Taking the length of message vector truncated again as half of the original one as an example, the simulation results and complexity are analyzed. Analysis shows that, compared to the EMS algorithm, computational complexity of comparisons and real additions of check node of the proposed algorithm have reduced by about 70% and 25% respectively. Meantime, the decoding performance of the proposed algorithm approach that of EMS algorithm and the loss is only near 0.08 dB when the bit error rate (BER) is 10−3and the Galois fieldGF(q)(q=16)GF(q)(q=16)GF(q)(q=16).
To reduce the high decoding complexity of q-ary LDPC codes, a joint-demodulation and extended min-sum (JD-EMS) decoding algorithm is presented in this paper. By utilizing the squares of the distances between signal and constellation points over constellation graph as the decoder input soft messages, the proposed algorithm not only facilitates the computations of the decoder initial messages, but also avoids the performance loss due to conversions between probabilities and log-likelihoodratios. The elementary check node (ECN) processing is also improved in JD-EMS algorithm, thus the number of real additions can be reduced. Moreover, we also give an upper bound of the number of comparison candidates in the sorter at each ECN step. Simulation results indicate that, while significantly reducing the number of real additions at check nodes, JD-EMS algorithm performs as well as EMS algorithm on both AWGN and Rayleigh fading channels.
A simplified algorithm for check node processing of extended min-sum (EMS) q-ary LDPC decoders is presented in this letter. Compared with the bubble check algorithm, the so-called dynamic bubble-check (DBC) algorithm aims to further reduce the computational complexity for the elementary check node (ECN) processing. By introducing two flag vectors in ECN processing, The DBC algorithm can use the minimum number of comparisons at each step. Simulation results show that, DBC algorithm uses significantly fewer comparison operations than the bubble check algorithm, and presents no performance loss compared with standard EMS algorithm on AWGN channels.
The extended min-sum algorithm (EMS) for decoding non-binary low density parity check (NB-LDPC) codes reduces the decoding complexity by truncating the message vector by retaining only the most reliable symbols. However, the EMS algorithm does not consider that the noise of the received codeword is gradually reduced as the iteration count goes up. In this paper, we propose a low-complexity adaptive EMS algorithm, called threshold-based EMS (TB-EMS). The TB-EMS algorithm has a simple adaptive rule to calculate the new message vector length compared to the A-EMS. The proposed algorithm selects one of two message vector lengths. Experimental results show that the proposed algorithm reduces the decoding complexity with minimal performance degradation compared with the EMS algorithm. Further, the decoding performance of the TB-EMS is better than A-EMS.
This letter is concerned with low-complexity decoding algorithms for nonbinary low-density parity-check (NB-LDPC) codes. A new truncation rule based on an adaptive threshold μ is proposed for the extended min-sum (EMS) algorithm. The threshold μ is determined by the mean of the message vector. Therefore, it can be matched to channel observation and decoding iteration. The resulting algorithm is referred to as μ-EMS algorithm. Simulation results show that the μ-EMS algorithm performs almost as well as the Q-ary sum-product algorithm (QSPA). Simulation results also show that the μ-EMS algorithm is simpler than the other X-EMS algorithms for NB-LDPC over high order finite fields.
The extended min-sum (EMS) algorithm for decoding low-density parity-check codes over the finite field with q elements significantly reduces decoding complexity by truncating each message of length q into a message of effective length nm. The number of effectively dominant components in each truncated message may gradually decrease with the number of decoding iterations. Based on this observation, we propose a novel adaptive EMS algorithm, called a two-length EMS (TL-EMS) algorithm. It chooses one of two candidate values as the effective message length nmfor each message by reflecting the concept called message separation. Numerical results show that it can significantly reduce the computational complexity with little performance degradation.