In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-of...In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-off is shown clearly and demonstrated with the paradigm of hybrid decoding. For regular LDPC code, the SNR-threshold performance and error-floor performance could be improved to the optimal level of ML decoding if the decoding complexity is progressively increased, usually corresponding to the near-ML decoding with progressively increased size of list. For irregular LDPC code, the SNR-threshold performance and error-floor performance could only be improved to a bottle-neck even with unlimited decoding complexity. However, with the technique of CRC-aided hybrid decoding, the ML performance could be greatly improved and approached with reasonable complexity thanks to the improved code-weight distribution from the concatenation of CRC and irregular LDPC code. Finally, CRC-aided 5GNR-LDPC code is evaluated and the capacity-approaching capability is shown.展开更多
The problem of improving the performance of min-sum decoding of low-density parity-check （LDPC） codes is considered in this paper. Based on min-sum algorithm, a novel modified min-sum decoding algorithm for LDPC cod...The problem of improving the performance of min-sum decoding of low-density parity-check （LDPC） codes is considered in this paper. Based on min-sum algorithm, a novel modified min-sum decoding algorithm for LDPC codes is proposed. The proposed algorithm modifies the variable node message in the iteration process by averaging the new message and previous message if their signs are different. Compared with the standard min-sum algorithm, the modification is achieved with only a small increase in complexity, but significantly improves decoding performance for both regular and irregular LDPC codes. Simulation results show that the performance of our modified decoding algorithm is very close to that of the standard sum-product algorithm for moderate length LDPC codes.展开更多
In this paper, two-dimensional (2-D) correction scheme is proposed to improve the performance of conventional Min-Sum (MS) decoding of regular low density parity check codes. The adopted algorithm to obtain the correc...In this paper, two-dimensional (2-D) correction scheme is proposed to improve the performance of conventional Min-Sum (MS) decoding of regular low density parity check codes. The adopted algorithm to obtain the correction factors is simply based on estimating the mean square difference (MSD) between the transmitted codeword and the posteriori information of both bit and check node that produced at the MS decoder. Semi-practical tests using software-defined radio (SDR) and specific code simulations show that the proposed quasi-optimal algorithm provides a comparable error performance as Sum-Product (SP) decoding while requiring less complexity.展开更多
文摘In this paper, both the high-complexity near-ML list decoding and the low-complexity belief propagation decoding are tested for some well-known regular and irregular LDPC codes. The complexity and performance trade-off is shown clearly and demonstrated with the paradigm of hybrid decoding. For regular LDPC code, the SNR-threshold performance and error-floor performance could be improved to the optimal level of ML decoding if the decoding complexity is progressively increased, usually corresponding to the near-ML decoding with progressively increased size of list. For irregular LDPC code, the SNR-threshold performance and error-floor performance could only be improved to a bottle-neck even with unlimited decoding complexity. However, with the technique of CRC-aided hybrid decoding, the ML performance could be greatly improved and approached with reasonable complexity thanks to the improved code-weight distribution from the concatenation of CRC and irregular LDPC code. Finally, CRC-aided 5GNR-LDPC code is evaluated and the capacity-approaching capability is shown.
基金supported by the Major State Basic Research Development Program of China (2009CB320300)
文摘The problem of improving the performance of min-sum decoding of low-density parity-check （LDPC） codes is considered in this paper. Based on min-sum algorithm, a novel modified min-sum decoding algorithm for LDPC codes is proposed. The proposed algorithm modifies the variable node message in the iteration process by averaging the new message and previous message if their signs are different. Compared with the standard min-sum algorithm, the modification is achieved with only a small increase in complexity, but significantly improves decoding performance for both regular and irregular LDPC codes. Simulation results show that the performance of our modified decoding algorithm is very close to that of the standard sum-product algorithm for moderate length LDPC codes.
文摘In this paper, two-dimensional (2-D) correction scheme is proposed to improve the performance of conventional Min-Sum (MS) decoding of regular low density parity check codes. The adopted algorithm to obtain the correction factors is simply based on estimating the mean square difference (MSD) between the transmitted codeword and the posteriori information of both bit and check node that produced at the MS decoder. Semi-practical tests using software-defined radio (SDR) and specific code simulations show that the proposed quasi-optimal algorithm provides a comparable error performance as Sum-Product (SP) decoding while requiring less complexity.
