一种迭代处理单元外部信息转移函数的精确计算方法

An Accurate Method for Calculating Extrinsic Information Transfer Functions of Iterative Processing Unit

针对现有计算方法得到的迭代处理单元的外部信息转移（EXIT）函数精确度较差的问题，提出了一种EXIT函数的精确计算方法——最优直方图法（OptHIST）．首先根据信息比特的取值（＋1或-1）将对数似然比数据进行分类，然后采用最优直方图估计对数似然比的概率分布函数，得到在积分最小均方误差意义上最优的概率分布函数，最后通过对对数似然的概率分布函数进行积分得到精确的EXIT函数．OptHIST法比直方图法鲁棒性更强，比直接求均值法适应性更广．实验结果表明，对于采用严格的后验概率算法的处理单元，OptHIST法可比直方图法减小误差约7%～15％．

Focusing on the problem that the extrinsic information transfer （EXIT） functions of the iterative processing unit in existing methods are of low accuracy, an accurate method named optimal histogram （OptHIST） is proposed. The OptHIST algorithm is implemented in the following steps. The log-likelihood ratio data are classified according to the value （＋ 1 or-1） of the info bits, and the optimal histogram is then used to estimate the probability distribution function of the log-likelihood ratio. The optimal probability distribution function is obtained in the sense of the integrated mean squared error. Then the exact EXIT function is obtained through integrating the probability distribution function of log-likelihood ratio. Compared with the existing methods, the proposed OptHIST method is more robust than the histogram method and more applicable than the direct average method. Simulation results show that the OptHIST method can reduce the error by about 7% to 15%, compared with the histogram method, for the processing unit which adopts rigid a-post probability algorithm.