In this paper, we present performance of pilot based channel estimation techniques such as Least Squares (LS) and Linear Minimum Mean Square Error (LMMSE) for different interpolation methods and modulation schemes. The performance is evaluated using the mean squared error (MSE) as the performance metric of interest for downlink LTE system. Simulation results show that for low SNR environment, a...

In this paper, we consider the steady state Mean Square Error (MSE) analysis for 2-D LMS algorithm in which the filter's weights are updated in both vertical and horizontal directions using Fornasini and Marchesini (F-M) state space model. The MSE analysis is conducted using the wellknown independence assumption. First we show that computation of the Weight-Error Correlation Matrix (WECM) for F...

This paper addresses the effects of sea clutter on the clutter-based atmospheric refractivity estimation techniques. It provides a mean square error (MSE) metric for refractivity estimators based on the available clutter-to-noise (CNR) ratio, the type of the sea clutter statistics (Rayleigh, K-distributed and log-normal) and the parameters forming these probability density functions (pdf) such ...

Soil pollution by metal(loid)s resulting from rapid economic development is a major concern. Accurately estimating the spatial distribution of soil metal(loid) pollution has great significance in preventing and controlling soil pollution. In this study, 126 topsoil samples were collected in Kunshan City and the geo-accumulation index was selected as a pollution index. We used Kriging interpolat...

This paper addresses Automatic Blind Modulation Recognition (ABMR)problem, utilizing a Mean Square Error (MSE) decision rule to recognize and differentiate M-ary PSK modulated signals in presence of noise and fading. The performance of the modulation recognition scheme has been evaluated by simulating different types of PSK signals. By putting appropriate Mean Square Error Difference Threshold ...

Introduction Multivariate Fay–Herriot models for estimating small area indicators are introduced. Among the available procedures for fitting linear mixed models, the residual maximum likelihood (REML) is employed. The empirical best predictor (EBLUP) of the vector of area means is derived. An approximation to the matrix of mean squared crossed prediction errors (MSE) is given and four MSE estim...

This paper describes a method that minimizes the mean squared error (MSE) in estimating the spherical harmonic components of the surface air temperature field. The ratio of the MSE to the variance of the spherical harmonic component is expressed in terms of the length scale Xo, and the positions and weights of the measurement stations. The weights are optimized by the condition of minimizing th...