Title : 
Biased estimation of Rician K factor
         
        
            Author : 
Shroff, Nitesh ; Giridhar, K.
         
        
            Author_Institution : 
Indian Inst. of Technol. Madras, Chennai
         
        
        
        
        
        
            Abstract : 
The time varying envelope of the received signal, for the case when a line of sight (LoS) component exists between the transmitter and the receiver, is described by a Rician distribution with Rician factor K. The Rician factor is a measure of the severity of the fading, with K = 0 being the most severe Rayleigh fading, and K = oo representing essentially a non-fading channel. K factor estimation is often thus required for link budget calculation as well as to determine the best possible space - time precoder when multiple transmit antennas are used. Here, we discuss the maximum likelihood estimator (MLE) and a moment based estimator for the estimation of the K factor. The James-Stein estimator (JSE), which is a biased, non - linear estimator, is then used to estimate the K factor and its performance is compared with the MLE. It is shown that using biased estimators (such as the JSE) for K factor estimation, can significantly improve the estimation performance. At low and high K factors, the JSE is similar to MLE, whereas for medium values of K, the JSE can outperform MLE significantly.
         
        
            Keywords : 
Rayleigh channels; Rician channels; antenna arrays; channel coding; channel estimation; maximum likelihood estimation; precoding; space-time codes; time-varying channels; JSE; James-Stein estimator; MLE; Rician K factor; biased estimation; line of sight component; maximum likelihood estimator; multiple transmit antennas; nonfading channel; space-time precoder; time varying envelope; Computer networks; Estimation error; Image restoration; MIMO; Maximum likelihood estimation; Probability density function; Rayleigh channels; Rician channels; Telecommunication computing; Transmitters; Biased Estimation; Expectaion - Maximization (EM) algorithm; James - Stein estiamtor (JSE); Maximum Likelihood (ML); Mean Squared Error (MSE); Rician K factor;
         
        
        
        
            Conference_Titel : 
Information, Communications & Signal Processing, 2007 6th International Conference on
         
        
            Conference_Location : 
Singapore
         
        
            Print_ISBN : 
978-1-4244-0982-2
         
        
            Electronic_ISBN : 
978-1-4244-0983-9
         
        
        
            DOI : 
10.1109/ICICS.2007.4449770