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Optimal Least Squares Deterministic Parameter Estimation from a Class of Block-Circulant-with-Circulant-Block Linear Model

机译:一类带有循环块的线性循环模型的最优最小二乘确定性参数估计

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This paper investigates the least-squares (LS) estimation of unknown deterministic parameters from a standard linear model characterized by a class of block-circulant-with-circulant-block (BCCB) matrix. We propose a method for designing the BCCB system matrix coefficients to minimize the mean square error incurred by the LS estimate, under certain equality and inequality constraints. By exploiting the eigenvalue characteristic of BCCB matrices, precise analysis is undertaken to derive a closed-form solution. The considered optimization problem arises in the study of blind channel estimation for single-carrier block transmission with cyclic prefix; the presented analysis reveals several key features associated with the BCCB family, and shows an original investigation of the BCCB matrix structure for facilitating linear optimal parameter estimation
机译:本文研究了以一类带有循环块的循环块(BCCB)矩阵为特征的标准线性模型对未知确定性参数的最小二乘(LS)估计。我们提出了一种设计BCCB系统矩阵系数的方法,以在某些相等和不等式约束下最小化LS估计引起的均方误差。通过利用BCCB矩阵的特征值特性,进行精确分析以得出封闭形式的解决方案。在研究具有循环前缀的单载波块传输的盲信道估计时,出现了被认为是最优化的问题。提出的分析揭示了与BCCB系列相关的几个关键特征,并显示了对BCCB矩阵结构的初步研究,以促进线性最佳参数估计

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