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 International Symposium on Circuits and Systems proceedings

Adaptive Successive Cancellation Priority Decoder for 5G Polar Codes

Wenqing Song, Yifei Shen, Yuxiang Fu, Chuan Zhang, Li Li

Published Apr 27, 2021• 4 citations
Publisher

Abstract

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.

DOI
10.1109/iscas51556.2021.9401175

Related papers

Successive Cancellation Priority Decoding of Polar Codes

Di Guan, Kai Niu, Chao Dong +1 more

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.

IEEE Access•Jan 1, 2019•9 citations

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

Efficient Successive Cancellation Stack Decoder for Polar Codes

Wenqing Song, Huayi Zhou, Kai Niu +4 more

As an improved version of successive cancellation (SC) polar decoder, an SC stack (SCS) decoder has been proposed for performance improvement. However, the existing SCS polar decoder suffers a lot from high time complexity at low signal-to-noise ratio (SNR) region and space complexity compared with the SC decoder. To this end, two improved decoders are proposed to reduce time and space complexity in both low and high SNR regions. The first one is the segmented cyclic redundancy check (CRC)-aided SCS (SCA-SCS) decoder, which is based on segmented parity checkers. The second one is the adaptive SCS (ASCS) decoder, which has the flexibility of stack depth and searching width. Furthermore, a channel condition estimator is proposed to select appropriate decision criteria for different SNR scenarios. Results have shown that for the polar code of length 1024 and rate 1/2, two improved SCS decoders can perform better than the traditional SCS decoder. The proposed SCA-SCS decoder and the ASCS decoder can achieve 10.8% and 11.42% time complexity reduction and 31.68% and 60.85% space complexity reduction on average over binary-input additive white Gaussian noise channels (BI-AWGNCs), respectively. Efficient parallel hardware architecture of the SCS polar decoder is first proposed and implemented with 90- and 65-nm technologies. Results have verified its advantages over the state of the art (SOA).

IEEE Transactions on Very Large Scale Integration (VLSI) Systems•Jul 15, 2019•19 citations

Fast Sequence Repetition Node-Based Successive Cancellation List Decoding for Polar Codes

Yifei Shen, Yuqing Ren, Andreas Toftegaard Kristensen +4 more

Compared with the bit-wise successive cancellation list (SCL) decoding of polar codes, the node-based Fast SCL decoding significantly reduces the decoding latency by identifying special constituent codes and decoding these in parallel. To further reduce the latency of current Fast SCL decoders, we first propose a fast sequence repetition (SR) node-based SCL (Fast SR-SCL) decoding algorithm, which only involves one type of node in the SCL decoding tree. Furthermore, we employ the adaptive path splitting (APS) strategy to terminate the path splitting in the SR node early, without degrading the error-correcting performance. Numerical results show that for 5G uplink codes with a length of 1024 and rates of 1/4, 1/2, and 3/4, our decoder can deliver the same decoding performance while reducing the average latency by 34.5%, 38.0%, and 39.6% compared with the state-of-the-art Fast SCL decoder for a list size L = 8.

International Conference on Communications•May 16, 2022•9 citations

A Sequence Repetition Node-Based Successive Cancellation List Decoder for 5G Polar Codes: Algorithm and Implementation

Yuqing Ren, Andreas Toftegaard Kristensen, Yifei Shen +3 more

Due to the low-latency and high-reliability requirements of 5G, low-complexity node-based successive cancellation list (SCL) decoding has received considerable attention for use in 5G communications systems. By identifying special constituent codes in the decoding tree and immediately decoding these, node-based SCL decoding provides a significant reduction in decoding latency compared to conventional SCL decoding. However, while there exists many types of nodes, the current node-based SCL decoders are limited by the lack of a more generalized node that can efficiently decode a larger number of different constituent codes to further reduce the decoding time. In this paper, we extend a recent generalized node, the sequence repetition (SR) node, to SCL decoding, and describe the first implementation of an SR-List decoder. By merging certain SR-List decoding operations and applying various optimizations for 5G New Radio (NR) polar codes, our optimized SR-List decoding algorithm increases the throughput by almost$\bm {2\times }$compared to a similar state-of-the-art node-based SCL decoder. We also present our hardware implementation of the optimized SR-List decoding algorithm which supports all 5G NR polar codes. Synthesis results show that our SR-List decoder can achieve a$2.94 \,\mathrm{Gbps}$throughput and$6.70 \,\mathrm{Gbps}\mathrm{m}^{-1}\,\mathrm{m}^{2}\,$area efficiency for$\bm {L=8}$.

arXiv:2205.08857•IEEE Transactions on Signal Processing•Jan 1, 2022•53 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
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.
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 an improved version of successive cancellation (SC) polar decoder, an SC stack (SCS) decoder has been proposed for performance improvement. However, the existing SCS polar decoder suffers a lot from high time complexity at low signal-to-noise ratio (SNR) region and space complexity compared with the SC decoder. To this end, two improved decoders are proposed to reduce time and space complexity in both low and high SNR regions. The first one is the segmented cyclic redundancy check (CRC)-aided SCS (SCA-SCS) decoder, which is based on segmented parity checkers. The second one is the adaptive SCS (ASCS) decoder, which has the flexibility of stack depth and searching width. Furthermore, a channel condition estimator is proposed to select appropriate decision criteria for different SNR scenarios. Results have shown that for the polar code of length 1024 and rate 1/2, two improved SCS decoders can perform better than the traditional SCS decoder. The proposed SCA-SCS decoder and the ASCS decoder can achieve 10.8% and 11.42% time complexity reduction and 31.68% and 60.85% space complexity reduction on average over binary-input additive white Gaussian noise channels (BI-AWGNCs), respectively. Efficient parallel hardware architecture of the SCS polar decoder is first proposed and implemented with 90- and 65-nm technologies. Results have verified its advantages over the state of the art (SOA).
Compared with the bit-wise successive cancellation list (SCL) decoding of polar codes, the node-based Fast SCL decoding significantly reduces the decoding latency by identifying special constituent codes and decoding these in parallel. To further reduce the latency of current Fast SCL decoders, we first propose a fast sequence repetition (SR) node-based SCL (Fast SR-SCL) decoding algorithm, which only involves one type of node in the SCL decoding tree. Furthermore, we employ the adaptive path splitting (APS) strategy to terminate the path splitting in the SR node early, without degrading the error-correcting performance. Numerical results show that for 5G uplink codes with a length of 1024 and rates of 1/4, 1/2, and 3/4, our decoder can deliver the same decoding performance while reducing the average latency by 34.5%, 38.0%, and 39.6% compared with the state-of-the-art Fast SCL decoder for a list size L = 8.
Due to the low-latency and high-reliability requirements of 5G, low-complexity node-based successive cancellation list (SCL) decoding has received considerable attention for use in 5G communications systems. By identifying special constituent codes in the decoding tree and immediately decoding these, node-based SCL decoding provides a significant reduction in decoding latency compared to conventional SCL decoding. However, while there exists many types of nodes, the current node-based SCL decoders are limited by the lack of a more generalized node that can efficiently decode a larger number of different constituent codes to further reduce the decoding time. In this paper, we extend a recent generalized node, the sequence repetition (SR) node, to SCL decoding, and describe the first implementation of an SR-List decoder. By merging certain SR-List decoding operations and applying various optimizations for 5G New Radio (NR) polar codes, our optimized SR-List decoding algorithm increases the throughput by almost2×\bm {2\times }2×compared to a similar state-of-the-art node-based SCL decoder. We also present our hardware implementation of the optimized SR-List decoding algorithm which supports all 5G NR polar codes. Synthesis results show that our SR-List decoder can achieve a2.94 Gbps2.94 \,\mathrm{Gbps}2.94Gbpsthroughput and6.70 Gbpsm−1 m2 6.70 \,\mathrm{Gbps}\mathrm{m}^{-1}\,\mathrm{m}^{2}\,6.70Gbpsm−1m2area efficiency forL=8\bm {L=8}L=8.
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.