任何通信系统的无监督和非参数迭代软比特出错率估计
Unsupervised and Non Parametric Iterative Soft Bit Error Rate Estimation for Any Communications System
摘要：
本文讨论了无监督软比特出错率（BER）估计的任何通信系统，在没有先验知识的情况下，无论是发送的信息位，或收发机方案是可用的问题。我们发现，BER估计的问题是等效的软信道/接收机输出的条件概率密度函数（PDF）的估计。假设接收机没有软观测的分析模型，我们提出了一种非参数的基于核的pdf估计技术，并证明了所得到的BER估计是渐近无偏和逐点一致的。然后，我们引入了一个迭代的随机期望最大化（EM）算法的先验和后验概率的传输信息比特的估计，并根据传输比特值的软观测的分类。这些输入用于条件pdf的迭代基于核的估计过程。我们分析了所提出的无监督和非参数的BER估计的性能在一个多用户码分多址（CDMA）系统与单用户检测的框架，并显示出有吸引力的性能相比，传统的蒙特卡洛（MC）辅助技术。
英文摘要：
This paper addresses the problem of unsupervised soft bit error rate (BER) estimation for any communications system, where no prior knowledge either about transmitted information bits, or the transceiver scheme is available. We show that the problem of BER estimation is equivalent to estimating the conditional probability density functions (pdf)s of soft channel/receiver outputs. Assuming that the receiver has no analytical model of soft observations, we propose a non parametric Kernel-based pdf estimation technique, and show that the resulting BER estimator is asymptotically unbiased and point-wise consistent. We then introduce an iterative Stochastic Expectation Maximization (EM) algorithm for the estimation of both a priori and a posteriori probabilities of transmitted information bits, and the classification of soft observations according to transmitted bit values. These inputs serve in the iterative Kernel-based estimation procedure of conditional pdfs. We analyze the performance of the proposed unsupervised and non parametric BER estimator in the framework of a multiuser code division multiple access (CDMA) system with single user detection, and show that attractive performance are achieved compared with conventional Monte Carlo (MC)-aided techniques.
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