1. 西安电子科技大学计算机科学与技术学院,陕西,西安,710071
2. 宝鸡文理学院数学与信息科学学院,陕西,宝鸡,721013
3. 西安电子科技大学计算机科学与技术学院,陕西,西安,710071
4. 宝鸡文理学院数学与信息科学学院,陕西,宝鸡,721013
网络出版:2020-04-25,
纸质出版:2020
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王彪, 慕建君, 焦晓鹏, 等. 基于改进罚函数的LDPC码分层调度ADMM惩罚译码[J]. 电子学报, 2020,48(4):827-832.
ADMM Penalized Decoding with Layered Scheduling for LDPC Codes Based on Improved Penalty Function[J]. Acta Electronica Sinica, 2020, 48(4): 827-832.
王彪, 慕建君, 焦晓鹏, 等. 基于改进罚函数的LDPC码分层调度ADMM惩罚译码[J]. 电子学报, 2020,48(4):827-832. DOI: 10.3969/j.issn.0372-2112.2020.04.025.
ADMM Penalized Decoding with Layered Scheduling for LDPC Codes Based on Improved Penalty Function[J]. Acta Electronica Sinica, 2020, 48(4): 827-832. DOI: 10.3969/j.issn.0372-2112.2020.04.025.
通过增加伪码字的代价,基于交替方向乘子法(Alternating Direction Method of Multipliers,ADMM)的惩罚译码方法可以改善低密度奇偶校验(Low-Density Parity-Check,LDPC)码低信噪比区域的译码性能,同时具有低的译码复杂度.而减少ADMM惩罚译码的欧几里德投影次数、选择合适的消息调度策略和设计有效的罚函数是提高ADMM惩罚译码速度的三种重要方法.为了进一步提高ADMM惩罚译码速度,通过利用Wei等人提出的方法来减少欧几里德投影的次数,本文设计了基于I-
l
1
-PF罚函数的水平分层调度与垂直分层调度策略的两种LDPC码ADMM惩罚译码方法.仿真实验表明,与现有ADMM惩罚译码方法相比较,所设计的译码方法不仅具有较好的译码性能,而且能够显著降低LDPC码译码的平均迭代次数和平均译码时间.
By making the pseudocodewords more costly
the penalized decoding method based on alternating direction method of multipliers (ADMM) can improve the decoding performance for low-density parity-check (LDPC) codes at low signal-to-noise ratios and also has low decoding complexity.Reducing the number of Euclidean projection in ADMM penalized decoding
selecting the appropriate message scheduling strategy and designing effective penalty function are three important methods to increase the ADMM penalized decoding speed.In order to increase the ADMM penalized decoding speed further
by using
the method proposed by Wei et al to reduce the number of Euclidean projections
this paper designs two kinds of ADMM penalized decoding methods with the horizontal layered scheduling and the vertical layered scheduling strategy for LDPC codes based on the I-
l
1
-PF penalty function.Simulation results show that the designed methods not only have better decoding performance but also significantly reduce the average number of iterations and the average decoding time compared with the existing ADMM penalized decoding methods.
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