Soft information perturbation can significantly enhance the successive cancellation list (SCL) decoding performance of polar codes. However, the existing perturbation-based SCL (PSCL) decoding requires a large number of re-decoding attempts, leading to high decoding complexity, and hence limits its application for long polar codes. In this letter, an enhanced PSCL (E-PSCL) decoding is proposed. It utilizes a new biased perturbation strategy that requires a reduced number of redecoding attempts, but yields an advanced decoding performance. To further improve the E-PSCL decoding performance, a reliability metric (RM) is introduced. It can better identify the possibly erroneous positions within the SCL decoding failures. During each decoding attempt, the E-PSCL decoding takes turns to flip these positions. Moreover, for the RM, it is derived from the SCL decoding error probability for which both the frozen bits and the error propagation are considered. Simulation results show that with the same number of decoding attempts, the proposed E-PSCL decoding outperforms the state-of-the-art dynamic SCL flip (D-SCLF) decoding and the conventional PSCL decoding.
For polar codes, successive cancellation list (SCL) decoding algorithm significantly improves finite-length performance compared to SC decoding. SCL-flip decoding can further enhance the performance but the gain diminishes as code length increases, due to the difficulty in locating the first error bit position. In this work, we introduce an SCL-perturbation decoding algorithm to address this issue. A basic version of the algorithm introduces small random perturbations to the received symbols before each SCL decoding attempt, and exhibits non-diminishing gain at large block lengths. Its enhanced version adaptively performs random perturbations or directional perturbation on each received symbol according to previous decoding results, and managed to correct more errors with fewer decoding attempts. Extensive simulation results demonstrate stable gains across various code rates, lengths and list sizes. To the best of our knowledge, this is the first SCL enhancement with non-diminishing gains as code length increases, and achieves unprecedented efficiency. With only one additional SCL-
L decoding attempt (in total two), the proposed algorithm achieves SCL-
2L-equivalent performance. Since the gain is obtained without increasing list size, the algorithm is best suited for hardware implementation.
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.