Capacity and Character Expansions: Moment generating function and other exact results for MIMO correlated channels
<|reference_start|>Capacity and Character Expansions: Moment generating function and other exact results for MIMO correlated channels: We apply a promising new method from the field of representations of Lie groups to calculate integrals over unitary groups, which are important for multi-antenna communications. To demonstrate the power and simplicity of this technique, we first re-derive a number of results that have been used recently in the community of wireless information theory, using only a few simple steps. In particular, we derive the joint probability distribution of eigenvalues of the matrix GG*, with G a semicorrelated Gaussian random matrix or a Gaussian random matrix with a non-zero mean (and G* its hermitian conjugate) . These joint probability distribution functions can then be used to calculate the moment generating function of the mutual information for Gaussian channels with multiple antennas on both ends with this probability distribution of their channel matrices G. We then turn to the previously unsolved problem of calculating the moment generating function of the mutual information of MIMO (multiple input-multiple output) channels, which are correlated at both the receiver and the transmitter. From this moment generating function we obtain the ergodic average of the mutual information and study the outage probability. These methods can be applied to a number of other problems. As a particular example, we examine unitary encoded space-time transmission of MIMO systems and we derive the received signal distribution when the channel matrix is correlated at the transmitter end.<|reference_end|>
@article{simon2005capacity,
    title={Capacity and Character Expansions: Moment generating function and other
  exact results for MIMO correlated channels},
    author={Steven H. Simon, Aris L. Moustakas and Luca Marinelli},
    journal={IEEETrans.Info.Theor.52:5336-5351,2006},
    year={2005},
    doi={10.1109/TIT.2006.885519},
    archivePrefix={arXiv},
    eprint={cs/0509080},
    primaryClass={cs.IT cond-mat.mes-hall cond-mat.stat-mech hep-lat math-ph math.IT math.MP}
}