期刊论文

Study on Optimization of Quantization Algorithm in ADMM Decoding Algorithm Based on Lookup Table

中文

计算机科学

1002-137X

2019

46

11

328-333

10.11896/jsjkx.181001871

国家自然科学基金项目(61501334) 华中师范大学中央高校基本科研业务费(CCNU16A05028)资助。

本校为第一机构

在基于ADMM的线性规划译码中,待投影向量向校验多胞体进行欧几里得投影计算是最复杂和耗时的部分。基于查找表的ADMM-LDPC译码算法通过简单的查表操作来替代复杂的投影运算,简化了投影过程,提升了算法的效率,但消耗了大量的内存资源。之后研究者提出了非均匀量化方法,该方法虽然极大地减少了内存消耗,但是所采用的量化方案的计算复杂度较高,从而使得该方法在量化段数较多的条件下难以实现。针对该问题,文中提出了一种新的非均匀量化方法。首先,针对不同的码字,在不同信噪比条件下,通过实验统计待投影向量中元素的分布特性,探究其分布规律,并设计相应的函数作为量化映射关系;然后,采用差分进化算...

In the linear programming decoding based on ADMM, the Euclidean projection calculation of the projection vector to the check multi-cellular body is the most complex and time-consuming part. The ADMM-LDPC decoding algorithm based on look-up tables replace the time complexity of algorithm with simple table look-up operations to simplify the projection process and improve the efficiency of the algorithm, however it expends much memory consumption. Later, the researchers proposed the nonuniform quantization method, which can decrease the memory consumption effectively, but the computation complexi...