The utilization of 5G and beyond wireless communication systems in autonomous driving and remote healthcare has necessitated the development of channel codes with high reliability and low latency. The multi-bit successive cancellation list (MSCL) parallel decoding of polar codes has shown great potential in the decrease of decoding latency while maintaining a high level of reliability, in comparison to the conventional successive cancellation list (SCL) decoding. However, the complexity of decoding path sorting increases exponentially with the increase of parallelism, which poses significant limitations to the improvement of parallelism. To address this issue, this paper proposes a critical set aided multi-bit successive cancellation list (CS-MSCL) decoding algorithm. Critical sets are introduced to the MSCL decoding, which prunes less reliable candidate paths to guarantee high decoding performance. Meanwhile, dynamic configuration is allowed according to the application scenario to make a good balance in decoding latency, error correction performance, and algorithmic complexity. Simulation results demonstrate that the algorithmic complexity decreased by 1099.04% compared to MSCL decoding for (1024, 512) polar codes when the degree of parallelism is 8 and the list size is 16.
The utilization of 5G and beyond wireless communication systems in autonomous driving and remote healthcare has necessitated the development of channel codes with high reliability and low latency. The multi-bit successive cancellation list (MSCL) parallel decoding of polar codes has shown great potential in the decrease of decoding latency while maintaining a high level of reliability, in comparison to the conventional successive cancellation list (SCL) decoding. However, the complexity of decoding path sorting increases exponentially with the increase of parallelism, which poses significant limitations to the improvement of parallelism. To address this issue, this paper proposes a critical set aided multi-bit successive cancellation list (CS-MSCL) decoding algorithm. Critical sets are introduced to the MSCL decoding, which prunes less reliable candidate paths to guarantee high decoding performance. Meanwhile, dynamic configuration is allowed according to the application scenario to make a good balance in decoding latency, error correction performance, and algorithmic complexity. Simulation results demonstrate that the algorithmic complexity decreased by 1099.04% compared to MSCL decoding for (1024, 512) polar codes when the degree of parallelism is 8 and the list size is 16.
Polar codes have garnered significant attention since they were proposed due to their capacity-achieving properties and their low-complexity decoding process, and they were selected as the coding scheme for the control channel in 5G mobile communication technology. A successive cancellation list (SCL) decoder, aided by a cyclic redundancy check (CRC), performs the competitive error correcting performance for polar codes compared to other sophisticated codes. The SCL-Flip decoding algorithm is proposed to enhance the error correction performance of the SCL. However, the SCL-Flip is hampered by a high decoding complexity due to the necessary selection and sorting process of path metrics (PMs). Additionally, it requires a large number of iterations to achieve a good error correction performance. In this paper, we propose the error segment bit-flip (ES-SCL-Flip) decoding algorithm, a simplified bit-flip approach for the SCL decoder based on analyzing the distributions of the first error bit. Firstly, we construct an index set with a high probability of the first erroneous bit. Second, a bit-flip criterion is introduced to prevent the costly operation of the PM selection and sorting without compromising the error correction performance. Finally, a search strategy is employed that utilizes segmented error indication to target and rectify the initial error segment sequentially. The simulation results demonstrate that the ES-SCL-Flip decoder provides an improved error correction performance with only a minimal increase in decoding complexity compared to the conventional CRC-aided SCL decoder. This algorithm attains a commendable equilibrium between the error correction performance and decoding complexity.
Successive cancellation list (SCL) decoding enables polar codes and their generalizations to deliver satisfactory performance in finite-length scenarios but it comes with high latency and complexity. To reduce latency, a partitioned SCL (PSCL) decoding algorithm, implemented over a PSCL decoding tree, can be utilized. In this work, we aim to lower down the complexity of the PSCL decoding, resulting in an efficient decoding algorithm with low latency and complexity for polar-like codes. To achieve this, we define two metrics at each level of the PSCL decoding tree. One is for evaluating the reliability of a path and the other is for estimating the probability of the correct path being included in a list of paths. Then, we propose a double-threshold strategy in the PSCL decoding process where unreliable valid paths are pruned based on the first metric, and then a list of surviving paths is selected based on the second metric. Simulation results demonstrate that when polar/CRC-polar/PAC codes are decoded using the proposed low-complexity PSCL decoder, both the sorting complexity and the computational complexity are reduced and significantly decrease as the signal-to-noise ratio (SNR) increases.
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 codes are the first capacity-achieving error-correction code which has attracted much research attention. Among many decoding methods, successive cancellation list decoding (SCLD) is considered as a representative decoding method that can achieve a good error-correcting performance. However, the long latency of SCLD is a significant matter that hinders practical applications, which is mainly caused by two features of the SCLD process: tree traversal and path-splitting. To alleviate the main reasons, a new multi-bit SCLD algorithm is proposed in this paper to decode several bits simultaneously without conducting any tree traversal and path-splitting when a node in the decoding tree holds a specific condition. In addition, a path ignoring (PI) technique is proposed to mitigate the condition of the multi-bit SCLD, which results in an additional reduction of latency. The proposed multi-bit decoding method and the PI technique play a significant role in reducing the number of path-splitting cases, by 96% compared to the conventional SCLD method. Simulation results show that compared to the conventional SCLD with list sizes 8 and 16, the proposed multi-bit decoding associated with the PI technique reduces the overall decoding cycles by 77% and 79%, respectively, with almost no degradation of error-correcting performance.
Polar codes, as the coding scheme for the control channel in fifth-generation mobile communication technology (5G), have attracted widespread attention since their proposal. As a mainstream decoding algorithm for polar codes, the successive cancellation list (SCL) decoder usually improves the error correction performance by increasing the list size, but this method suffers from the problems of high decoding complexity. To address this problem, this paper proposes a layered-search bit-flipping (LS-SCLF) decoding algorithm based on SCL decoding. Firstly, a new flip-bit metric is proposed, which derives a formula to approximate the probability of an error occurring in an information bit. This formula introduces a perturbation parameter to improve the calculation accuracy. Secondly, a compromise scheme for determining the perturbation parameter is proposed. The scheme uses Monte Carlo simulation to determine an optimized parameter for the precise positioning of the first erroneous decoded bit under different decoding conditions. Finally, a layered search strategy is adopted to sequentially search the erroneous decoded bits from the low order to high order, which can correct up to multiple bits at the same time. Simulation results show that the proposed algorithm achieves improved error correction performance with a slight increase in decoding complexity compared to the generalized SCL-Flip (GSCLF) decoding algorithm. This algorithm also achieves a good balance between the error correction performance and decoding complexity.
When the code length is finite, the successive cancellation list (SCL) decoding of polar codes shows as good error-correction performance as low-density parity-check codes and turbo codes and it will be used in high-speed communications. However, since the hardware complexity of the SCL increases linearly as the size of the list increases, it is difficult to use the high-complexity SCL decoding for devices with limited resource such as IoT devices. The successive cancellation flip (SCF) decoding algorithm has been proposed to solve the problem of high hardware complexity and to enhance the error-correction performance of successive cancellation decoding. However, the conventional SCF decoding has high computational complexity. In this paper, we propose the interleaver-aided successive cancellation flip (ISCF) decoding to reduce the computational complexity. The computational complexity of the ISCF decoding is less by at least 32% than the conventional SCF decoding for error frame at Eb/N0=3.5dB.