Robust estimation of signal and interference power in rayleigh fading channels

This paper deals with the problem of signal and interference power estimation in communication over wireless fading channels. In this work, a new class of estimators for joint estimation of signal and Gaussian interference variance is proposed. Our study includes developing a unified framework that covers the design and performance analysis of the estimators. The estimators addressed in this paper, namely maximum likelihood, minimum variance unbiased, best linear unbiased and sub-space estimators, require knowledge of eigenvectors and eigenvalues of the channel autocorrelation matrix. To relax this requirement, a tracking mechanism for least-squares estimation of the channel eigen-space is devised. Several aspects of the statistical characteristics of the resulting estimators are presented. As a salient feature, the proposed methods are suitably applicable to estimation of signal and interference power in wideband code division multiple access (WCDMA) used in third generation (3G) mobile wireless communication systems