Research On The Impact Of Correlation On Channel Capacity Of MIMO Wireless Communication Systems

The Multiple-Input Multiple-Output (MIMO) technology is the most promising breakthroughs in improving system performance, capacity and spectrum efficiency. The performance promised by MIMO is highly depended on the propagation channel models. So the corresponding MIMO radio channel models are established to study and evaluate the system performance.First, we introduce the background and elements of MIMO techniques. Comparison is given between other techniques and MIMO wireless communications to demonstrate necessity and inevitability of research on MIMO. Then provide the problem to be resolved existing in MIMO communication in detail, pointing out the research direction of our work.Then, we describe a statistical-based vector channel model for uniform circular arrays (UCA) and uniform linear arrays (ULA) and developed a statistical time-varying multipath MIMO channel model to be used in our research firstly. Then, we derived the exact and approximate functions of these two models. In the analytical results, it is found that the standard deviation of the angular energy distribution or the angle spread is the donating factor for the determining correlation, and the approximate analysis can replace the exact analysis in some cases and reduce the computational complexity 74 percent. Base on these results, we investigate the MIMO channel capacity of the uniform circular arrays (UCA) model. We prove that, for this model, increase in correlation is equivalent to decrease in signal-to-noise ratio (SNR), the radius of the circular receive antenna array and angle spread are the dominating factors for the channel capacity. In the end, the study of the development of the MIMO systems is discussed.