MIMO channel modeling and the principle of maximum entropy
We devise theoretical grounds for constructing channel models for multiple-input multiple-output (MIMO) systems based on information-theoretic tools. The paper provides a general method to derive a channel model which is consistent with one's state of knowledge. The framework we give here has already been fruitfully explored with success in the context of Bayesian spectrum analysis and parameter estimation. For each channel model, we conduct an asymptotic analysis (in the number of antennas) of the achievable transmission rate using tools from random matrix theory. A central limit theorem is provided on the asymptotic behavior of the mutual information and validated in the finite case by simulations. The results are useful both in terms of designing a system based on criteria such as quality of service and in optimizing transmissions in multiuser networks.
channel modeling entropy multiple-input multiple-output (mimo) antenna arrays bayesian probability theory random matrices