基于贝叶斯和确定性crb的SIMO单载波循环前缀系统半盲信道估计

Samir-Mohamad Omar, D. Slock, O. Bazzi
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引用次数: 6

摘要

传统上,对不同的半盲信道估计算法的性能进行了评估,并在一定的下界下进行了比较。其中一个在文献中被广泛使用的著名的下界是克莱默-拉奥界(CRB)。根据我们对符号和信道的处理方式,可以衍生出不同版本的CRB。关于如何处理符号和/或信道,有两种可能的情况,即确定性未知或随机。此外,这些符号要么与信道共同估计,要么被消除。换句话说,我们有六个不同的案子要处理。本文给出了文献中存在的适合其中一些情况的crb,并在SIMO单载波循环前缀系统(SC-CP)的背景下推导了其他crb。在此基础上,我们提出了一个统一的框架,允许以具体的方式派生所有版本的crb。通过进行有限的蒙特卡罗模拟,对所有导出的crb进行了数值验证。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Bayesian and deterministic CRBs for semi-blind channel estimation in SIMO single carrier cyclic prefix systems
Traditionally, the performance of different semi-blind channel estimation algorithms has been assessed and compared to a certain lower bound. One of these famous lower bounds that has been extensively used in the literature is the Cramer Rao Bound (CRB). Depending on how we treat the symbols and the channel, different versions of CRB have been derived. There are two possible cases on how to treat the symbols and/or the channel namely, deterministic unknowns or random. Moreover, the symbols are either jointly estimated with the channel or eliminated. In other words, we have six different cases to be handled. In this paper we present the CRBs that exist in the literature and fit to some of these cases and derive the others in the context of SIMO single carrier cyclic prefix systems (SC-CP). On the top of that we present a unified framework that permits to derive all versions of CRBs in a concrete manner. All the derived CRBs are validated numerically by conducting limited Monte-Carlo simulations.
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