Why Does a Kronecker Model Result in Misleading Capacity Estimates?

Many recent works that study the performance of multi-input multi-output (MIMO) systems in practice assume a Kronecker model where the variances of the channel entries, upon decomposition on to the transmit and the receive eigen-bases, admit a separable form. Measurement campaigns, however, show that the Kronecker model results in poor estimates for capacity. Motivated by these observations, a channel model that does not impose a separable structure has been recently proposed and shown to fit the capacity of measured channels better. In this work, we show that this recently proposed modeling framework can be viewed as a natural consequence of channel decomposition on to its canonical coordinates, the transmit and/or the receive eigen-bases. Using tools from random matrix theory, we then establish the theoretical basis behind the Kronecker mismatch at the low- and the high-SNR extremes: 1) Sparsity of the dominant statistical degrees of freedom (DoF) in the true channel at the low-SNR extreme, and 2) Non-regularity of the sparsity structure (disparities in the distribution of the DoF across the rows and the columns) at the high-SNR extreme.Comment: 39 pages, 5 figures, under review with IEEE Trans. Inform. Theor

Spatio-temporal correlation models for indoor MIMO channels

Accurate modeling of the spatio-temporal cross-correlation between the subchannels of a multiple-input multiple-output (MIMO) channel is an important prerequisite of multi-element antenna system design. In this thesis, a new model for indoor MIMO channels is proposed, and a closed form expression for the spatio-temporal cross-correlation function is derived. This new analytical correlation expression includes many physical parameters of interest such as the angle-of-arrivals at the base station and the user, the associated angle spreads, and other parameters, in a compact form. Comparison of this model with narrowband indoor MIMO data collected at Brigham Young University exhibits the utility of the model. Specifically, capacity calculations and the application of the model to maximum likelihood detection in correlated narrowband MIMO channels demonstrates close match to empirical data. As a different approach to indoor correlation modeling, the commonly used Kronecker product model is considered, which shows large deviation from the measured data in terms of correlation, capacity, and bit error rate

Spatial Correlation in Indoor MIMO Channels

This paper presents the analysis of spatial correlation in MIMO channels, calculated from data measured in o#ce environments at 5.2GHz. Results are compared with those from channels generated using a stochastic MIMO channel model and the e#ect of di#erent comparison metrics is shown. The suitability of the stochastic model under di#erent propagation conditions is also investigated