Multi-CRC Polar Codes and M-SCFlip-Based Decoding

Guo, Rui; Chen, Kangni; Liu, Huaping

doi:10.1109/access.2019.2927391

Cited by 7 publications

(4 citation statements)

References 19 publications

(19 reference statements)

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“…A threshold SCFlip (TSCF) decoding algorithm was proposed to improve the BLER performance of the SC decoder [21]. A multi-CRC polar codes construction algorithm was introduced to correct an error in time and slow down the error propagation [22]. A simplified dynamic SCFlip polar decoding was proposed in [23], which replaced the logarithmic and exponential calculation of [20] with simple approximation.…”

Section: Introductionmentioning

confidence: 99%

Parity-Check-CRC Concatenated Polar Codes SSCFlip Decoder

et al. 2022

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Successive cancellation flip decoding requires a large number of extra successive cancellation decoding attempts at low signal-to-noise ratios (SNRs), resulting in high decoding complexity. In addition, it has a long decoding latency. Although modifications have been proposed in successive cancellation flip decoding, these still have high computational complexity at low SNRs due to a huge number of additional successive cancellation decoding attempts. It is desirable to detect the unsuccessful successive cancellation decoding process at an early stage in the additional successive cancellation flip attempts and stop it that can reduce the decoding complexity. This paper combines the parity-check-CRC concatenated polar codes with the low-latency simplified successive cancellation decoding and proposes a parity-check-CRC concatenated polar codes simplified successive cancellation flip (PC-CRC-SSCFlip) decoder. It further employs the parity-check vector to identify the unsuccessful simplified successive cancellation flip decoding at an early stage and terminates so that it can minimize the decoding complexity on average. Additionally, this work proposes an error-prone flipping list by incorporating the empirically observed indices based on channel-induced error distribution along with the first bit of each Rate-1 node. The proposed technique can identify more than one error-prone bit through a flipping list and correct them. In addition, the parity-check vector further narrows down the search space for the identification of erroneous decisions. Simulation results show that 60% of unsuccessful additional successive cancellation decoding attempts terminate early rather than decode the whole codeword. The proposed PC-CRC-SSCFlip decoder has approximately 0.7 dB and 0.3 dB gains over successive cancellation and successive cancellation flip decoders, respectively, at a fixed block error rate (BLER) = 10−3. Additionally, it reduces the average computational complexity and decoding latency of the successive cancellation flip decoder at low-to-medium SNRs while approaching successive cancellation decoding complexity at medium-to-high SNRs.

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Section: Introductionmentioning

confidence: 99%

Parity-Check-CRC Concatenated Polar Codes SSCFlip Decoder

et al. 2022

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“…Another improved method is to use the segmentation method to divide the whole codeword into several segments, and CRC code is added after each segment to verify whether the segment is correct [15]. This method has two advantages: (1) The CGE bits only need to be selected in the erroneous segments, which narrows the search space; (2) If the CGE bits cannot be found after several flipping attempts, there is no need to continue the decoding process and the decoding delay can be reduced [16,17].…”

Section: Introductionmentioning

confidence: 99%

A latency‐reduced SC flip decoding algorithm for polar codes

2022

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The successive cancellation flip (SC Flip) decoding algorithm was recently suggested for decoding polar codes, which could improve the performance of the frame error rate (FER). The performance of the SC Flip (SCF) decoding algorithm is strong, and its computational complexity tends to be the same as that of the SC decoder at medium to high signal-tonoise ratios (SNRs). However, the decoding latency of the SCF decoding algorithm is large. In this paper, a new method for detecting whether or not the flipped bit is correct is proposed. The proposed method makes a decision according to the changing log likelihood ratio (LLR) value caused by the flipped bit to ensure that the decoding process can be terminated in advance and the decoding latency is reduced. The simulation results show that the proposed Latency-Reduced SCF decoding algorithm can decrease computational complexity and decoding latency, while also achieving similar decoding performance compared to its counterpart.

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“…SC-flip identifies the first incorrectly estimated bit that occurs during SC decoding and flips it to restrict the error propagation in the next SC decoding attempt. Several supplements of SC-flip with the average computational complexity close to the standard SC decoder in the moderate to high SNR regime have been proposed [9][10][11][12][13][14][15]. However, they still rely on the SC decoding mechanism, which results in high decoding latency and low throughput due to the sequential processing nature.…”

Section: Introductionmentioning

confidence: 99%

A Novel Flip-List-Enabled Belief Propagation Decoder for Polar Codes

et al. 2021

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Due to the design principle of parallel processing, belief propagation (BP) decoding is attractive, and it provides good error-correction performance compared with successive cancellation (SC) decoding. However, its error-correction performance is still inferior to that of successive cancellation list (SCL) decoding. Consequently, this paper proposes a novel flip-list- (FL)-enabled belief propagation (BP) method to improve the error-correction performance of BP decoding for polar codes with low computational complexity. The proposed technique identifies the vulnerable channel log-likelihood ratio (LLR) that deteriorates the BP decoding result. The FL is utilized to efficiently identify the erroneous channel LLRs and correct them for the next BP decoding attempt. The preprocessed channel LLR through FL improves the error-correction performance with minimal flipping attempts and reduces the computational complexity. The proposed technique was compared with the state-of-the-art BP, i.e., BP bit-flip (BP-BF), generalized BP-flip (GBPF), cyclic redundancy check (CRC)-aided (CA-SCL) decoding, and ordered statistic decoding (OSD), algorithms. Simulation results showed that the FL-BP had an excellent block error rate (BLER) performance gain up to 0.7dB compared with BP, BP-BF, and GBPF decoder. Besides, the computational complexity was reduced considerably in the high signal-to-noise ratio (SNR) regime compared with the BP-BF and GBPF decoding methods.

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Multi-CRC Polar Codes and M-SCFlip-Based Decoding

Cited by 7 publications

References 19 publications

Parity-Check-CRC Concatenated Polar Codes SSCFlip Decoder

Parity-Check-CRC Concatenated Polar Codes SSCFlip Decoder

A latency‐reduced SC flip decoding algorithm for polar codes

A Novel Flip-List-Enabled Belief Propagation Decoder for Polar Codes

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