Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Log inSign up
Challenges
Datasets
Workspaces
Papers
Discussions
Leaderboard
Blog
Job Board
Q3AS

© 2026 Aqora Quantum S.A.S.

TermsPrivacyLegal Notice

IEEE Access

Successive Cancellation Priority Decoding of Polar Codes

Di Guan, Kai Niu, Chao Dong, Ping Zhang

Published Jan 1, 2019• 9 citations
Publisher

Abstract

The successive cancellation list (SCL) decoding of polar codes can achieve a performance close to that of maximum-likelihood decoding. Nevertheless, a large list size results in high-computational complexity. In this paper, a successive cancellation priority (SCP) decoding algorithm is proposed to reduce the time complexity. The SCP decoder performs a priority-first decoding, which is composed of a priority queue and a trellis. During the SCP decoding, the priority queue interacts with the trellis iteratively. Conceptually, the priority queue stores the priority information and guides the extension of the candidate path. The trellis calculates and stores the intermediate results. Since most of the unnecessary path extensions are avoided by using the priority queue, the time complexity of the SCP decoder is much lower than that of the standard SCL decoder. Then, a quantized priority queue is introduced to avoid the comparison operations in the path selection and to simplify the SCP decoder. Furthermore, we prove that the path extension of the SCP decoder is equivalent to the extension of the most reliable paths of the standard SCL decoder. Thus, the SCP decoder can achieve the same decoding performance as that of the standard SCL decoder.

DOI
10.1109/access.2019.2890838

Related papers

An Adaptive Successive Cancellation Priority Decoder with Iteratively-increased Searching Width for Polar Codes

Di Guan, Kai Niu

The successive cancellation list (SCL) decoding of polar codes can achieve a performance close to the maximum-likelihood (ML) decoding while large list size results in high computational complexity. To this end, successive cancellation priority (SCP) decoding is proposed to reduce the complexity of the SCL decoding with acceptable space complexity. In this paper, an adaptive SCP (ADSCP) decoder with iteratively increased searching width is proposed. Two priority queues are applied to store all the priority nodes during the decoding. When the correct decoding path cannot be obtained with the current searching width, the decoding continues with a larger searching width rather than be restarted. Furthermore, an early termination criterion is applied to quit the decoding when too many inefficient path extensions are performed based on a preset threshold. The early termination criterion can reduce the worst-case complexity of the decoder. Simulation results show that given the same searching width (list size), the proposed ADSCP decoder can achieve the same decoding performance as the conventional adaptive SCL (ADSCL) decoder while significantly reducing the complexity.

International Conference on Wireless Communications and Signal Processing (WCSP)•Nov 2, 2023•0 citations

Adaptive Successive Cancellation Priority Decoder for 5G Polar Codes

Wenqing Song, Yifei Shen, Yuxiang Fu +2 more

As two common successive cancellation (SC)-based decoding algorithms of polar codes, the SC list (SCL) and SC stack (SCS) decoder can achieve satisfactory error correction performance, especially with increased list size or stack depth. Nevertheless, a large list size or stack depth will lead to high computational complexities and hardware resources. To this end, successive cancellation priority (SCP) decoding with priority- first searching strategy and trellis-like storage is proposed to offer one solution. In this paper, an efficient SCP decoder is first proposed to verify its advantages over SCL and SCS decoders. Furthermore, an adaptive node-inserting scheme is proposed to reduce the number of bits insert into the priority queue. Numerical results have shown that for the polar code with transmission length 1024 and rate 1/2, the proposed adaptive SCP (ASCP) decoder can achieve significant time complexity reduction on average compared with the standard SCL decoder. The hardware architecture of SCP decoding is implemented using 65-nm CMOS technology and the results show better throughput compared with the SCS decoder.

IEEE International Symposium on Circuits and Systems proceedings•Apr 27, 2021•4 citations

A Low Complexity Successive Cancellation List Decoding Algorithm of Polar Codes

Jiansong Miao, Weijie Li, Xuejia Hu +1 more

Polar codes are the first provably capacity-achieving novel channel codes. Successive cancellation list (SCL) decoding algorithm has a performance close to maximum-likelihood decoding when code length is finite, though the complexity is high. To reduce the complexity of SCL, a partial path expansion with segmented check and pruning SCL (PPE-SCP-SCL) algorithm is proposed in this paper. Based on the successive decoding structure, if the decoding result of a bit is judged to be reliable enough, then a hard decision is made directly and no path expansion is necessary. Moreover, several parity-check points are introduced to perform segmented parity-check during the decoding process, and if the check fails, the current path is directly abandoned. The rationality of the operations is theoretically verified, and numerical simulations also verify that the proposed algorithm can significantly reduce the complexity of decoding with trivial loss of error performance.

IEEE/CIC International Conference on Communications in China (ICCC)•Aug 9, 2020•0 citations

Simplified Successive-Cancellation List decoding of polar codes

Seyyed Ali Hashemi, Carlo Condo, Warren J. Gross

The Successive-Cancellation List (SCL) decoding algorithm is one of the most promising approaches towards practical polar code decoding. It is able to provide a good trade-off between error-correction performance and complexity, tunable through the size of the list. In this paper, we show that in the conventional formulation of SCL, there are redundant calculations which do not need to be performed in the course of the algorithm. We simplify SCL by removing these redundant calculations and prove that the proposed simplified SCL and the conventional SCL algorithms are equivalent. The simplified SCL algorithm is valid for any code and can reduce the time-complexity of SCL without affecting the space complexity.

IEEE International Symposium on Information Theory (ISIT)•Jul 1, 2016•72 citations

Low-Complexity Successive Cancellation List Decoding of Polar Codes Based on Path Metric

Xiaodong Liu, Ce Sun, Wei Tang

Successive cancellation (SC) decoding algorithm and successive cancellation list (SCL) decoding algorithm are two common decoding methods for polar codes. The SC decoding algorithm has low complexity, but in its decoding process, the bits with small channel indices are used to assist the decoding of the bits with large channel indices. Therefore, the bit being decoded depends on the bits that have already been decoded which causes error propagation. On the basis of SC decoding, the SCL decoding algorithm overcomes the problem of error propagation by widening the path search width and retaining multiple paths at the same time in the decoding process. However, the complexity of SCL decoding is higher than that of SC decoding. Without changing the performance of the SCL decoding algorithm, we propose a low-complexity SCL decoding algorithm based on path metric (PM). After the last frozen bit is decoded, the path with the smallest PM is selected, and the subsequent nodes adopt SC decoding. Through this combination of SCL decoding and SC decoding, the complexity of the SCL decoding algorithm can be effectively reduced while the SCL decoding performance remains unchanged, especially in the case of high code rates.

IEEE International Conference on Communication Technology (ICCT)•Oct 13, 2021•3 citations

Large-Small Sorting for Successive Cancellation List Decoding of Polar Codes

Kyungpil Lee, In‐Cheol Park

The successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficult to apply the SCL decoding to the applications with limited processing time. To reduce the latency of the metric sorting, this paper proposes a new sorting method derived by analyzing path extension cases encountered in SCL decoding. The proposed method can avoid unnecessary sorting operations by adaptively determining the sorting size, and can be combined with other metric sorting methods. Simulation results show that the proposed method significantly reduces the decoding latency for various list sizes and code rates without degrading the error-correcting performance. The proposed method also becomes more effective as the code rate or the list size increases. Combined with the state-of-the-art sorting method, the proposed method reduces the average SCL decoding latency for a (1024, 512) polar code by 33.1% when the list size is 8.

IEEE Access•Jan 1, 2020•4 citations
The successive cancellation list (SCL) decoding of polar codes can achieve a performance close to that of maximum-likelihood decoding. Nevertheless, a large list size results in high-computational complexity. In this paper, a successive cancellation priority (SCP) decoding algorithm is proposed to reduce the time complexity. The SCP decoder performs a priority-first decoding, which is composed of a priority queue and a trellis. During the SCP decoding, the priority queue interacts with the trellis iteratively. Conceptually, the priority queue stores the priority information and guides the extension of the candidate path. The trellis calculates and stores the intermediate results. Since most of the unnecessary path extensions are avoided by using the priority queue, the time complexity of the SCP decoder is much lower than that of the standard SCL decoder. Then, a quantized priority queue is introduced to avoid the comparison operations in the path selection and to simplify the SCP decoder. Furthermore, we prove that the path extension of the SCP decoder is equivalent to the extension of the most reliable paths of the standard SCL decoder. Thus, the SCP decoder can achieve the same decoding performance as that of the standard SCL decoder.
The successive cancellation list (SCL) decoding of polar codes can achieve a performance close to the maximum-likelihood (ML) decoding while large list size results in high computational complexity. To this end, successive cancellation priority (SCP) decoding is proposed to reduce the complexity of the SCL decoding with acceptable space complexity. In this paper, an adaptive SCP (ADSCP) decoder with iteratively increased searching width is proposed. Two priority queues are applied to store all the priority nodes during the decoding. When the correct decoding path cannot be obtained with the current searching width, the decoding continues with a larger searching width rather than be restarted. Furthermore, an early termination criterion is applied to quit the decoding when too many inefficient path extensions are performed based on a preset threshold. The early termination criterion can reduce the worst-case complexity of the decoder. Simulation results show that given the same searching width (list size), the proposed ADSCP decoder can achieve the same decoding performance as the conventional adaptive SCL (ADSCL) decoder while significantly reducing the complexity.
As two common successive cancellation (SC)-based decoding algorithms of polar codes, the SC list (SCL) and SC stack (SCS) decoder can achieve satisfactory error correction performance, especially with increased list size or stack depth. Nevertheless, a large list size or stack depth will lead to high computational complexities and hardware resources. To this end, successive cancellation priority (SCP) decoding with priority- first searching strategy and trellis-like storage is proposed to offer one solution. In this paper, an efficient SCP decoder is first proposed to verify its advantages over SCL and SCS decoders. Furthermore, an adaptive node-inserting scheme is proposed to reduce the number of bits insert into the priority queue. Numerical results have shown that for the polar code with transmission length 1024 and rate 1/2, the proposed adaptive SCP (ASCP) decoder can achieve significant time complexity reduction on average compared with the standard SCL decoder. The hardware architecture of SCP decoding is implemented using 65-nm CMOS technology and the results show better throughput compared with the SCS decoder.
Polar codes are the first provably capacity-achieving novel channel codes. Successive cancellation list (SCL) decoding algorithm has a performance close to maximum-likelihood decoding when code length is finite, though the complexity is high. To reduce the complexity of SCL, a partial path expansion with segmented check and pruning SCL (PPE-SCP-SCL) algorithm is proposed in this paper. Based on the successive decoding structure, if the decoding result of a bit is judged to be reliable enough, then a hard decision is made directly and no path expansion is necessary. Moreover, several parity-check points are introduced to perform segmented parity-check during the decoding process, and if the check fails, the current path is directly abandoned. The rationality of the operations is theoretically verified, and numerical simulations also verify that the proposed algorithm can significantly reduce the complexity of decoding with trivial loss of error performance.
The Successive-Cancellation List (SCL) decoding algorithm is one of the most promising approaches towards practical polar code decoding. It is able to provide a good trade-off between error-correction performance and complexity, tunable through the size of the list. In this paper, we show that in the conventional formulation of SCL, there are redundant calculations which do not need to be performed in the course of the algorithm. We simplify SCL by removing these redundant calculations and prove that the proposed simplified SCL and the conventional SCL algorithms are equivalent. The simplified SCL algorithm is valid for any code and can reduce the time-complexity of SCL without affecting the space complexity.
Successive cancellation (SC) decoding algorithm and successive cancellation list (SCL) decoding algorithm are two common decoding methods for polar codes. The SC decoding algorithm has low complexity, but in its decoding process, the bits with small channel indices are used to assist the decoding of the bits with large channel indices. Therefore, the bit being decoded depends on the bits that have already been decoded which causes error propagation. On the basis of SC decoding, the SCL decoding algorithm overcomes the problem of error propagation by widening the path search width and retaining multiple paths at the same time in the decoding process. However, the complexity of SCL decoding is higher than that of SC decoding. Without changing the performance of the SCL decoding algorithm, we propose a low-complexity SCL decoding algorithm based on path metric (PM). After the last frozen bit is decoded, the path with the smallest PM is selected, and the subsequent nodes adopt SC decoding. Through this combination of SCL decoding and SC decoding, the complexity of the SCL decoding algorithm can be effectively reduced while the SCL decoding performance remains unchanged, especially in the case of high code rates.
The successive cancellation list (SCL) decoding is used to achieve good error-correcting performance for practical finite-length polar codes. However, the metric sorting that is repeatedly performed in SCL decoding increases the overall decoding latency as the list size increases, making it difficult to apply the SCL decoding to the applications with limited processing time. To reduce the latency of the metric sorting, this paper proposes a new sorting method derived by analyzing path extension cases encountered in SCL decoding. The proposed method can avoid unnecessary sorting operations by adaptively determining the sorting size, and can be combined with other metric sorting methods. Simulation results show that the proposed method significantly reduces the decoding latency for various list sizes and code rates without degrading the error-correcting performance. The proposed method also becomes more effective as the code rate or the list size increases. Combined with the state-of-the-art sorting method, the proposed method reduces the average SCL decoding latency for a (1024, 512) polar code by 33.1% when the list size is 8.