There are two main algorithms, successive cancellation (SC) algorithm and brief propagation (BP) algorithm, for decoding polar code. The SC algorithm has better error-correcting performance and the BP algorithm has low latency. The hybrid BP-SC decoding combines these two decoding algorithms and achieves improvements. Furthermore, the successive cancellation flip (SCF) algorithm improves the error-correcting performance for the SC algorithm, but it has higher computation complexity and latency. Based on the hybrid BP-SC decoding, we proposed a hybrid BP-SC/SCF decoding for polar codes in this paper to further improve the error-correcting performance. The result shows our approach outperforms to frame error rates (FER) of the SC decoding and BP decoding at least 0.5-dB and outperforms hybrid BP-SC decoding by 0.2-dB to 0.4-dB. Compared with the SCF decoding, the hybrid BPSC/SCF decoding has a small degradation of FER in a highquality channel but it significantly reduces the average computation complexity.
There are two main algorithms, successive cancellation (SC) algorithm and brief propagation (BP) algorithm, for decoding polar code. The SC algorithm has better error-correcting performance and the BP algorithm has low latency. The hybrid BP-SC decoding combines these two decoding algorithms and achieves improvements. Furthermore, the successive cancellation flip (SCF) algorithm improves the error-correcting performance for the SC algorithm, but it has higher computation complexity and latency. Based on the hybrid BP-SC decoding, we proposed a hybrid BP-SC/SCF decoding for polar codes in this paper to further improve the error-correcting performance. The result shows our approach outperforms to frame error rates (FER) of the SC decoding and BP decoding at least 0.5-dB and outperforms hybrid BP-SC decoding by 0.2-dB to 0.4-dB. Compared with the SCF decoding, the hybrid BPSC/SCF decoding has a small degradation of FER in a highquality channel but it significantly reduces the average computation complexity.
By adopting successive cancellation list decoding (SCL), polar codes demonstrate competitive error correction performance over LDPC and Turbo codes. However, SCL decoding suffers from high computational complexity and long decoding latency, especially when the list size is very large. Successive cancellation flip (SCF), as another decoding algorithm that can achieve high error correction performance, has a complexity that is close to that of successive cancellation (SC) decoding. With the observation that SCL and SCF decoding are similar at giving more chances to inspect possible codewords simultaneously or sequentially, a novel hybrid decoder is proposed in this paper, which essentially combines the ideas of SCF and SCL decoders. Moreover, in order to compensate for the degradation of performance caused by the reduction of path splitting and further reduce the decoding latency, the convolutional polar codes are adopted with a designed bit-flipping set. Simulation results demonstrate that the proposed decoder achieves the reduction of decoding latency while attaining better performance than conventional CRC-aided SCL decoder.
Polar code has lower coding and decoding requirements, linear complexity, and superior channel performance, so it is proven to be close to the Shannon limit for 5G communication. Successive cancellation (SC) is a polar code decoding method, but its performance has a lot of room for optimization, and flip methodology is one of its basic optimizations. Successive Cancellation Flip (SCF) has a good error correction capability. But due to the repetition of the SC decoder during computation, it has a very long latency. Moreover, SCF output is a hard decision, so it is not capable of soft input and soft output decoder. To allow SCF to be used in more decoding environments, the Hybrid SCF/SCAN proposed in this paper can freely select soft output and hard output, and the proposed architecture can reduce the problem of repeatedly computing SC decode.
Bit flipping was first used to improve the decoding performance of successive cancellation (SC) decoder. Since SC decoding process is serial, so the first bit that goes wrong in the decoding process will cause several subsequent bits to go wrong, which will suffer from higher decoding delay than belief propagation (BP) parallel decoding. In order to meet the performance of 5G low latency and high reliability, BP decoding algorithm have received a lot of attention. However, at medium and high signal-to-noise ratios (SNR), BP decoding does not perform as well as the SC list (SCL) decoding algorithm. Hence, BP decoding algorithm borrows bit-flip strategies from SC bit flip (SCF) decoder to improve the performance. The performance of BP bit flip (BPF) decoding depends on whether the construction of the flip set is correct, so this letter proposes a flip set construction approach based on the standard deviation of the log-likelihood ratio (LLR) and the reliability weight of polarized channels, which is comparable to the existing BPF decoding, the improved algorithm can identify the error-prone bits more efficiently and improve the decoding performance.
Since the inherent serial nature of successive cancellation list (SCL) decoding results in a long latency, belief propagation (BP) decoding for polar codes has drawn attention for high-throughput applications. However, its error correction performance is inferior to that of SCL decoding. Therefore, the bit-flipping strategy has been recently applied to BP decoding, which can approach the SCL decoding performance through multiple additional decoding attempts. The original BP flip (BPF) decoding suffers from an inaccurate identification of erroneous bits by a fixed flip set (FS), which has been improved by the generalized BPF (GBPF) decoding. In this article, the GBPF decoding is extended to support multiple bits being flipped in one decoding attempt. In addition, for two types of decoding errors: detected errors and undetected errors, we propose two novel methods to more effectively identify erroneous bits. For detected errors, the concept of loop sets is defined and a loopbased identification method is introduced based on the study of error patterns of BP decoding. On the other hand, a method to generate a more accurate fixed FS is proposed for undetected errors, which considers the bit error distribution under BP decoding. Combining the two methods, the GBPF with merged sets (GBPF-MS) decoding can achieve the SCL-8 performance and outperforms the state-of-the-art BPF, BP list, and SC flip (SCF) decoding, for polar codes with length 1024 and information rate 1/2. Implemented by 40nm CMOS technology, the proposed GBPF-MS decoder with ten flips exhibits an average throughput of 4.19 Gbps at 2.5 dB, which is 1.6× and 1.72× faster than the state-of-the-art SCL-4 and SCF decoders, respectively.
In this paper, we propose a low complexity hybrid ordered statistics decoding (OSD) successive cancellation (SC) decoding algorithm for the polar codes. By replacing smaller size SC decoder with OSD decoder, we can improve the error correcting performance of the SC algorithm. The size of the OSD decoder can be changed to control the trade-off between the decoding complexity and the error correcting performance of the proposed algorithm. We also provide a method to further simplify the proposed algorithm. Simulation results show that the proposed algorithm offers about 0.3 dB gain comparing to the SC at target bit error rate (BER) 10-5with code length N = 1024, 512,256 and code rate R = 1 /3. The impact of the OSD size is also simulated and analyzed.
Polar Codes achieve average error correction performance at finite code lengths, when decoded using Successive Cancellation (SC) decoding. Successive Cancellation Flip (SC-Flip) based decoders provide a viable low complexity substitute of the high performing high complexity Successive Cancellation List (SCL) decoders, providing a considerable improvement in the performance. A novel approach to identify and flip multiple erroneous bits in each decoding attempt has been aimed in this paper. Moreover, a faster version of the proposed decoder is also presented, which provides better performance throughout the entire decoding range. The performance of the proposed decoders have been evaluated with respect to frame error correction rate along with average normalized complexity and then compared with some of the existing works for validating the outperformance.