Early Stopping Criteria for Energy-Efficient Low-Latency Belief-Propagation Polar Code Decoders

Yuan, Bo; Parhi, Keshab K.

doi:10.1109/tsp.2014.2366712

Cited by 191 publications

(184 citation statements)

References 25 publications

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“…We can see that the proposed decoder with M BP = 50 performs significantly better than the SC decoder and the original BP decoder. Particularly, for C 2 , at FER = 10 −4 , the performance gains for the proposed decoder with M BP = 50 is about 1.2 dB when compared to the original BP decoder with M BP = 60 and the improved BP decoders proposed in [11] and [15]. And also, compared to the SC list (SCL) decoder with the list size L = 32, the polar codes using the proposed decoder can obtain almost 0.7 dB performance gains.…”

Section: Simulation Resultsmentioning

confidence: 96%

“…However, if the value of β is 7.5, the average number of BP iterations for C 1 is about 63 at the same SNR. Therefore, as in [15], to make a tradeoff between the FER performance and decoding complexity, we choose β = 0.5 when SNR <3.5 dB and β = 7.5 when SNR ≥ 3.5 dB for C 1 . For C 2 and C 3 , Fig.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…6) which is mainly due to the overshooting of the update scheduling such that the decoder tends to a wrong codeword, quickly. Figure 7 shows the average number of total BP iterations ( = C AP C BP ) per frame for C 2 using the original BP decoder, BP decoder with G-matrix-based early stopping scheme [15], BP decoder with the freezing of connected sub-factor-graphs (CSFGs) [19], and the proposed decoder. From simulations, we can see that as SNR increases, the average number of BP iterations for the proposed decoder decreases faster than other decoders.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…However, according to the analysis in [15] and simulation results, the BP decoder does not provide a good error-correction performance if we only usex H T = 0 as the stopping criterion for polar codes. Hence, we consider the following simple but efficient stopping criterion for the proposed decoder based on the criterion described in [15], which also can reduce the number of matrix adaption.…”

Section: Early Terminationmentioning

confidence: 99%

“…The above criterion is based on the stopping criterion described in [15], though it is proposed for BP decoder with factor graph representation of generator matrix. To illustrate the validity of this criterion, the proposed decoder only withx H T = 0 as the stopping criterion is used to decode the (256, 128) polar code at SNR = 2.5 dB.…”

Section: Early Terminationmentioning

confidence: 99%

See 4 more Smart Citations

Enhanced belief propagation decoding of polar codes by adapting the parity-check matrix

Jiao

et al. 2017

J Wireless Com Network

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Though the performance of belief propagation (BP) decoder for polar codes is comparable with the successive cancellation (SC) decoder, it has significant performance gap when compared with the improved SC decoders, such as SC list (SCL) decoding. In this paper, we propose an improved BP decoding for polar codes with good performance by adapting their parity-check matrices. The decoding process is iterative and consists of two parts. Firstly, the parity-check matrix of polar codes is adjusted such that one of its submatrices corresponding to less reliable bits is in a sparse nature. Secondly, the BP decoding is applied to the adjusted parity-check matrix. Simulation results show that the proposed decoder, when accompanied with the early termination scheme, provides significant performance gains over the original polar BP decoder under a relatively low decoding complexity and even competes with the cyclic redundancy check (CRC)-aided SCL (CRC-SCL) decoder only by increasing a tolerate complexity.

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Section: Simulation Resultsmentioning

confidence: 96%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Simulation Resultsmentioning

confidence: 99%

Section: Early Terminationmentioning

confidence: 99%

Section: Early Terminationmentioning

confidence: 99%

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Enhanced belief propagation decoding of polar codes by adapting the parity-check matrix

Jiao

et al. 2017

J Wireless Com Network

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Error‐rate analysis of polar code designs using genetic algorithm for additive white Gaussian noise channel

Sinha,

Bhaumik

2023

Int J Communication

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SummaryA novel scheme for designing polar codes with specific decoding schemes in the additive white Gaussian noise channel is presented in this paper. The code construction strategy is built on the genetic algorithm (GA) where successive evolution of populations (or group of information sets) leads toward fittest candidate to attain finest error‐rates. In this work, it is shown that better error‐rates can be attained by both successive cancelation list decoding using GA with no cyclic redundancy check (CRC) and belief propagation decoding using GA with no CRC and no list, compared to existing polar decoding schemes. Our proposed polar code design scheme using GA has the ability to attain a target block error rates with the least possible SNR and using no additional CRC by exploiting least belief propagation iterations or lesser successive cancelation list list size with no self‐alterations in the decoding algorithm.

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Termination for Belief Propagation Decoding of Polar Codes in Fading Channels

Zhang

Yan

2019

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Early Stopping Criteria for Energy-Efficient Low-Latency Belief-Propagation Polar Code Decoders

Cited by 191 publications

References 25 publications

Enhanced belief propagation decoding of polar codes by adapting the parity-check matrix

Enhanced belief propagation decoding of polar codes by adapting the parity-check matrix

Error‐rate analysis of polar code designs using genetic algorithm for additive white Gaussian noise channel

Termination for Belief Propagation Decoding of Polar Codes in Fading Channels

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