基于EXIT图和自适应微粒群算法的度分布对优化方法
doi: 10.3724/SP.J.1146.2008.01052
An Optimization Method of Degree Distributions Based on EXIT Chart and APSO Algorithm
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摘要: 综合EXIT图法和自适应微粒群优化(APSO)算法的优点，该文提出了一种基于EXIT图和APSO算法的非正则LDPC码度分布对优化方法。该方法设计了衡量EXIT曲线匹配程度的全局代价函数，并运用APSO算法对度分布对进行快速迭代优化，迭代过程中不需要固定CND曲线，可以获得EXIT曲线更加匹配的优化度分布对，以及更高的噪声门限。仿真结果表明，该方法在码结构优化方面有着很好的性能，且优化速度较高斯逼近法有了较大提高。Abstract: Based on EXIT chart and APSO algorithm, a new method to optimize the degree distributions of irregular LDPC codes is proposed in this paper. An overall cost function is first designed to measure the matching extent of EXIT curves. Then the degree distributions are optimized iteratively by using the Adaptive Particle Swarm Optimizer (APSO) algorithm. Such a procedure needs not to fasten the Check Nodes Decoder(CND) curve. And therefore, some new degree distributions with higher noise threshold are obtained. Simulation results show that APSO-EXIT algorithm has a good performance to achieve optimal code structures, and it is more effective than Gaussian Approximation in computation.
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