Bit-Flip Algorithm for Successive Cancellation List Decoder of Polar Codes

Cheng, Fengyi; Liu, Aijun; Zhang, Yingxian; Ren, Jian

doi:10.1109/access.2019.2914691

Cited by 32 publications

(71 citation statements)

References 18 publications

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“…Similar to the output design of WP-LSTM with the path metrics taken as inputs, we also simulate for the performance of LSTM without preprocessing (NP) named as NP-LSTM. The proposed design is compared with the prior work [13], and the simulation results are shown in Fig. 4.…”

Section: Simulation Resultsmentioning

confidence: 99%

“…In this paper, we present the novel LSTM-assisted CA-SCLF decoder. The bit-flipping order can be learned from the LSTM network, and it can improve the performance and the latency compared to the conventional algorithms [13]. Also, we utilize the domain knowledge to reduce the complexity and memory requirements so that the hardware can be more friendly.…”

Section: Resultsmentioning

confidence: 99%

“…Finally, Section 5 concludes our work. Overview of (a) the conventional CA-SCLF design [13], and (b) the proposed low-complexity LSTM-assisted CA-SCLF.…”

Section: Introductionmentioning

confidence: 99%

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Low-Complexity LSTM-Assisted Bit-Flipping Algorithm For Successive Cancellation List Polar Decoder

Chen

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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Polar codes have attracted much attention in the past decade due to their capacity-achieving performance. The higher decoding capacity is required for 5G and beyond 5G (B5G). Although the cyclic redundancy check (CRC)assisted successive cancellation list bit-flipping (CA-SCLF) decoders have been developed to obtain a better performance, the solution to error bit correction (bitflipping) problem is still imperfect and hard to design. In this work, we leverage the expert knowledge in communication systems and adopt deep learning (DL) technique to obtain the better solution. A low-complexity long short-term memory network (LSTM)-assisted CA-SCLF decoder is proposed to further improve the performance of conventional CA-SCLF and avoid complexity and memory overhead. Our test results show that we can effectively improve the BLER performance by 0.11dB compared to prior work and reduce the complexity and memory overhead by over 30% of the network.

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Section: Simulation Resultsmentioning

confidence: 99%

Section: Resultsmentioning

confidence: 99%

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Low-Complexity LSTM-Assisted Bit-Flipping Algorithm For Successive Cancellation List Polar Decoder

Chen

2020

ICASSP 2020 - 2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)

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“…The authors in [22] combined the bit flipping with the high-performance SCL decoding such that a performance gain was achieved at a cost of increased complexity. Another SCL-based flipping (SCLFlip) decoding algorithm was also proposed in [23]. With a superior bit-flip criterion, the SCLFlip decoder in [23] could not only outperform existing SCLFlip decoders but also achieve a better performance than SCL decoder while maintaining a similar complexity.…”

Section: Introductionmentioning

confidence: 99%

BER Evaluation Based SCFlip Algorithm for Polar Codes Decoding

2020

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Successive cancellation (SC) decoding of polar codes may bring about error propagation that needs to be mitigated. In this paper, we present a new SC Flipping (SCFlip) decoder, named bit error rate (BER) evaluation based SCFlip (BER-SCFlip), which can accurately target the first error bit and correct it with a high probability. Thus, a high error correction capability and a low decoding complexity can be achieved. First, we propose a new criterion to find out the most suspicious error bit. Those non-frozen bits that have higher decoding BERs derived from log-likelihood-ratios (LLRs) after SC decoding than the corresponding expected ones estimated via Gaussian Approximation (GA), are collected into the flip-bits set. These candidate bits will be flipped one by one according to their SC decoding orderings in extra decoding attempts until the decoded codeword passes cyclic redundancy check (CRC) or a predetermined maximum number of extra attempts is reached. We then propose an extended version of BER-SCFlip, named BER-SCFlip-ω with the capability to correct up to ω error bits in each extra decoding attempt. By combining our criterion for the flip-bits selection with that of Dynamic SCFlip (D-SCFlip), the proposed BER-SCFlip-ω significantly reduces decoding complexity and latency while maintaining the superior error-correction performance close to that of D-SCFlip-ω. The simulation results show that the proposed schemes are competitive among existing SCFlip algorithms and could achieve the error-correction performance approaching that of CRC-aided SCL decoding under list size L = 16 while maintaining low complexity. INDEX TERMS Polar codes, SC decoding, SCFlip decoding, Gaussian approximation.

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“…However, using multiple CRC codes increases memory and time complexity, which can be reduced by optimizing CRC positions in combination with a modified decoding operation. Cheng et al proposed the bit-flip algorithm for the CA-SCL algorithm, which can improve the decoding performance of polar codes compared to CRC-aided decoding of polar codes [ 7 ]. Although the SCL decoding algorithm has excellent decoding performance by adding CRC, its memory complexity and time complexity increase with the increase of

.…”

Section: Introductionmentioning

confidence: 99%

Improved Adaptive Successive Cancellation List Decoding of Polar Codes

Wang

et al. 2019

Entropy

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Although the adaptive successive cancellation list (AD-SCL) algorithm and the segmented-CRC adaptive successive cancellation list (SCAD-SCL) algorithm based on the cyclic redundancy check (CRC) can greatly reduce the computational complexity of the successive cancellation list (SCL) algorithm, these two algorithms discard the previous decoding result and re-decode by increasing L, where L is the size of list. When CRC fails, these two algorithms waste useful information from the previous decoding. In this paper, a simplified adaptive successive cancellation list (SAD-SCL) is proposed. Before the re-decoding of updating value L each time, SAD-SCL uses the existing log likelihood ratio (LLR) information to locate the range of burst error bits, and then re-decoding starts at the incorrect bit with the smallest index in this range. Moreover, when the segmented information sequence cannot get the correct result of decoding, the SAD-SCL algorithm uses SC decoding to complete the decoding of the subsequent segmentation information sequence. Furthermore, its decoding performance is almost the same as that of the subsequent segmentation information sequence using the AD-SCL algorithm. The simulation results show that the SAD-SCL algorithm has lower computational complexity than AD-SCL and SCAD-SCL with negligible loss of performance.

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Bit-Flip Algorithm for Successive Cancellation List Decoder of Polar Codes

Cited by 32 publications

References 18 publications

Low-Complexity LSTM-Assisted Bit-Flipping Algorithm For Successive Cancellation List Polar Decoder

Low-Complexity LSTM-Assisted Bit-Flipping Algorithm For Successive Cancellation List Polar Decoder

BER Evaluation Based SCFlip Algorithm for Polar Codes Decoding

Improved Adaptive Successive Cancellation List Decoding of Polar Codes

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