scholarly journals Analysis of MIMO Receiver Using Generalized Least Squares Method in Colored Environments

2014 ◽  
Vol 2014 ◽  
pp. 1-6 ◽  
Author(s):  
Mohamed Lassaad Ammari ◽  
Paul Fortier
Keyword(s):  
Least Squares ◽  
Additive Noise ◽  
Least Squares Method ◽  
Mimo Systems ◽  
Multiple Input Multiple Output ◽  
Generalized Least Squares ◽  
Mimo Channel ◽  
Mimo Channels ◽  
Detection Techniques ◽  
Generalized Least Squares Estimator

The classical detection techniques for multiple-input multiple-output (MIMO) systems are usually designed with the assumption that the additive complex Gaussian noise is uncorrelated. However, for closely spaced antennas, the additive noise is correlated due to the mutual antenna coupling. This letter analyzes an improved zero-forcing (ZF) technique for MIMO channels in colored environments. The additive noise is assumed to be correlated and the Rayleigh MIMO channel is considered doubly correlated. The improved ZF detector, based on the generalized least squares estimator (GLS), takes into account the noise covariance matrix and provides an unbiased estimator of the transmitted symbol vectors. We introduce some novel bounds on the achievable sum rate, on the normalized mean square error at the receiver output, and on the outage probability. The derived expressions are compared to Monte Carlo simulations.

scholarly journals Effect of Polarization on the Correlation and Capacity of Indoor MIMO Channels

2012 ◽  
Vol 2012 ◽  
pp. 1-11 ◽  
Author(s):  
Hsun-Chang Lo ◽  
Ding-Bing Lin ◽  
Teng-Chieh Yang ◽  
Hsueh-Jyh Li
Keyword(s):  
Fading Channels ◽  
Channel Capacity ◽  
Mimo Systems ◽  
Mimo System ◽  
Multiple Input Multiple Output ◽  
Mimo Channel ◽  
Analysis Method ◽  
Mimo Channels ◽  
Received Power ◽  
Value Decomposition

We describe a simple multiple-input/multiple-output (MIMO) channel measurement system for acquiring indoor MIMO channel responses. Four configurations of the polarization diversity antenna, referred to asVVV,YYH,YVYandVHH, were studied in terms of the capacity of indoor MIMO systems. Measurements were taken for a3×3MIMO system in the 2.4 GHz band. In addition, the channel capacity, singular-value decomposition, and correlation coefficient were used to explain the effects of various polarization schemes on MIMO fading channels. We also propose an analysis method for polarization channel capacity; this method includes the normalization of the received power and polarization effect for different polarization schemes. The validation of the model is based upon data collected in both light-of-sight (LOS) and non-light-of-sight (NLOS) environments. From the numerical simulation results, the proposed analysis method was close to measurements made in an indoor environment.

ASYMPTOTIC EFFICIENCY OF THE ORDINARY LEAST SQUARES ESTIMATOR FOR REGRESSIONS WITH UNSTABLE REGRESSORS

2002 ◽  
Vol 18 (5) ◽  
pp. 1121-1138 ◽  
Author(s):  
DONG WAN SHIN ◽  
MAN SUK OH
Keyword(s):  
Least Squares ◽  
Asymptotic Efficiency ◽  
Characteristic Root ◽  
Sufficient Conditions ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Least Squares Estimator ◽  
Characteristic Roots ◽  
Generalized Least Squares Estimator ◽  
Ordinary Least Squares Estimator

For regression models with general unstable regressors having characteristic roots on the unit circle and general stationary errors independent of the regressors, sufficient conditions are investigated under which the ordinary least squares estimator (OLSE) is asymptotically efficient in that it has the same limiting distribution as the generalized least squares estimator (GLSE) under the same normalization. A key condition for the asymptotic efficiency of the OLSE is that one multiplicity of a characteristic root of the regressor process is strictly greater than the multiplicities of the other roots. Under this condition, the covariance matrix Γ of the errors and the regressor matrix X are shown to satisfy a relationship (ΓX = XC + V for some matrix C) for V asymptotically dominated by X, which is analogous to the condition (ΓX = XC for some matrix C) for numerical equivalence of the OLSE and the GLSE.

Harmonizing biomass tables by generalized least squares

1985 ◽  
Vol 15 (2) ◽  
pp. 331-340 ◽  
Author(s):  
T. Cunia ◽  
R. D. Briggs
Keyword(s):  
Least Squares ◽  
Least Squares Method ◽  
Weighted Least Squares ◽  
Regression Function ◽  
Generalized Least Squares ◽  
Ordinary Least Squares ◽  
Sample Tree ◽  
Tree Data ◽  
Regression Techniques ◽  
Ordinary Least Squares Method

To construct biomass tables for various tree components that are consistent with each other, one may use linear regression techniques with dummy variables. When the biomass of these components is measured on the same sample trees, one should also use the generalized rather than ordinary least squares method. A procedure is shown which allows the estimation of the covariance matrix of the sample biomass values and circumvents the problem of storing and inverting large covariance matrices. Applied to 20 sets of sample tree data, the generalized least squares regressions generated estimates which, on the average were slightly higher (about 1%) than the sample data. The confidence and prediction bands about the regression function were wider, sometimes considerably wider than those estimated by the ordinary weighted least squares.

The least-squares intersection of a family of lines and its application to phase equilibria

1982 ◽  
Vol 60 (15) ◽  
pp. 1978-1981 ◽  
Author(s):  
John W. Lorimer
Keyword(s):  
Phase Equilibria ◽  
Least Squares ◽  
Least Squares Method ◽  
Solid Phase ◽  
Generalized Least Squares ◽  
First Approximation ◽  
Generalized Least Squares Method ◽  
Point Of Intersection ◽  
Straight Lines ◽  
General Method

A generalized least-squares method is described for finding the point of intersection of a family of straight lines, each of which is defined by two experimental points. It is shown that the method of the least-squares triangle (Can. J. Chem. 59, 3076 (1981)) is a good first approximation to the general method. An example demonstrates the method of iteration of both parameters and observations for a problem involving evaluation of solid phase compositions from solubility measurements.

Confidence Sets for the Coefficients Vector of a Linear Regression Model with Nonspherical Disturbances

1997 ◽  
Vol 13 (3) ◽  
pp. 406-429 ◽  
Author(s):  
Anoop Chaturvedi ◽  
Hikaru Hasegawa ◽  
Ajit Chaturvedi ◽  
Govind Shukla
Keyword(s):  
Linear Regression ◽  
Regression Model ◽  
Least Squares ◽  
Linear Regression Model ◽  
Generalized Least Squares ◽  
Least Squares Estimator ◽  
Regression Coefficients ◽  
Confidence Sets ◽  
Generalized Least Squares Estimator ◽  
Coverage Probabilities

In this present paper, considering a linear regression model with nonspherical disturbances, improved confidence sets for the regression coefficients vector are developed using the Stein rule estimators. We derive the large-sample approximations for the coverage probabilities and the expected volumes of the confidence sets based on the feasible generalized least-squares estimator and the Stein rule estimator and discuss their ranking.

On the Capacity of MIMO Channels with Outdated Channel State Information

2011 ◽  
Vol 204-210 ◽  
pp. 2053-2056
Author(s):  
Ying Li ◽  
Yi Jun Zhu ◽  
Lan Ma ◽  
Yao Zhu
Keyword(s):  
Fading Channels ◽  
Channel State Information ◽  
Multiple Input Multiple Output ◽  
Ergodic Capacity ◽  
Mimo Channel ◽  
Wide Sense ◽  
Mimo Channels ◽  
Channel State ◽  
State Information ◽  
Input Multiple Output

A Multiple-input multiple-output (MIMO) time-varying flat fading channel is considered. The transmitter obtained the channel state information (CSI) relying on the reciprocity principle or by the feedback from the receiver. Thus, channel state information at the transmitter (CSIT) is outdated due to the delay between the estimation of the channel and the transmission of the data. In order to achieve the maximum channel capacity, the transmitter linearly precoded the signal before transmission based on the outdated CSIT. Under the assumptions of wide-sense stationary uncorrelated scattering Rayleigh fading channels and Jake’s model, the instantaneous mutual information and ergodic capacity is derived for MIMO channels with outdated CSIT. The information outage probability of MIMO channel with outdated CSIT is also presented.

Determination of Estimators with Minimum Asymptotic Covariance Matrices

1993 ◽  
Vol 9 (4) ◽  
pp. 633-648 ◽  
Author(s):  
Charles E. Bates ◽  
Halbert White
Keyword(s):  
Least Squares ◽  
Rate Of Convergence ◽  
Asymptotic Variance ◽  
Generalized Least Squares ◽  
Covariance Matrices ◽  
Variance Estimator ◽  
Objective Functions ◽  
Generalized Least Squares Estimator ◽  
Asymptotic Covariance

We give a straightforward condition sufficient for determining the minimum asymptotic variance estimator in certain classes of estimators relevant to econometrics. These classes are relatively broad, as they include extremum estimation with smooth or nonsmooth objective functions; also, the rate of convergence to the asymptotic distribution is not required to be n−½. We present examples illustrating the content of our result. In particular, we apply our result to a class of weighted Huber estimators, and obtain, among other things, analogs of the generalized least-squares estimator for least Lp-estimation, 1 ≤ p < ∞.

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