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The use of Multiple Input Multiple Output (MIMO) systems has been widely recognized as an efficient solution to increase the data rate of wireless communications. In this regard, several contributions investigate the performance improvement of MIMO systems in terms of Shannon's mutual information. In most of these contributions, elements of the MIMO channel matrix are assumed to belong to a multivariate...
This paper is devoted to the study of the performance of the linear minimum mean-square error (LMMSE) receiver for (receive) correlated multiple-input multiple-output (MIMO) systems. By the random matrix theory, it is well known that the signal-to-noise ratio (SNR) at the output of this receiver behaves asymptotically like a Gaussian random variable as the number of receive and transmit antennas converge...
This paper studies the fluctuations of the post-processing SNR at the output of the linear MMSE receiver in (receive) correlated multiple input multiple output (MIMO) systems. Although it is known that asymptotically, the SNR behaves like a Gaussian random variable, this approximation may yield to inaccurate estimates for small dimension. In order to circumvent this, we use gamma and generalized gamma...
Consider the linear Wiener receiver for multidimensional signals. Such a receiver is frequently encountered in wireless communications and in array processing, and the Signal to noise ratio (SNR) at its output is a popular performance index. The SNR can be modeled as a random quadratic form and in order to study this quadratic form, one can rely on well-know results in Random Matrix Theory, if one...
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