算法
估计员
数学
复正态分布
多输入多输出
基质(化学分析)
最小均方误差
均方误差
衰退
克拉姆-饶行
估计理论
上下界
矩阵分解
QR分解
高斯分布
统计
解码方法
波束赋形
数学分析
物理
量子力学
特征向量
复合材料
材料科学
作者
Aditya K. Jagannatham,Bhaskar D. Rao
标识
DOI:10.1109/tsp.2005.862908
摘要
This paper proposes a whitening-rotation (WR)-based algorithm for semi-blind estimation of a complex flat-fading multi-input multi-output (MIMO) channel matrix H. The proposed algorithm is based on decomposition of H as the matrix product H=WQ/sup H/, where W is a whitening matrix and Q is unitary rotation matrix. The whitening matrix W can be estimated blind using only received data while Q is estimated exclusively from pilot symbols. Employing the results for the complex-constrained Cramer-Rao Bound (CC-CRB), it is shown that the lower bound on the mean-square error (MSE) in the estimate of H is directly proportional to its number of unconstrained parameters. Utilizing the bounds, the semi-blind scheme is shown to be very efficient when the number of receive antennas is greater than or equal to the number of transmit antennas. Closed-form expressions for the CRB of the semi-blind technique are presented. Algorithms for channel estimation based on the decomposition are also developed and analyzed. In particular, the properties of the constrained maximum-likelihood (ML) estimator of Q for an orthogonal pilot sequence is examined, and the constrained estimator for a general pilot sequence is derived. In addition, a Gaussian likelihood function is considered for the joint optimization of W and Q, and its performance is studied. Simulation results are presented to support the algorithms and analysis, and they demonstrate improved performance compared to exclusively training-based estimation.
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