Quantities of information and their properties: entropy, conditional entropy, divergence, redundancy, mutual information, channel capacity.
Using three different validation metrics, namely, mutual information, channel diversity, and the novel Environment Characterisation Metric, we find that the RCM is able to reflect the measured environment remarkably well.
We identify three bounds, namely, the mutual information, the channel capacity, and the so-called achievable mutual information.
Both mutual information and channel capacity do not consider system design losses caused, for example, by the transmission of cyclic prefix or reference symbols, or the quantization of the transmitter precoding.
Some of the proposed methods consist in channel-wise SNR transformation (Fuchs et al. 1998), incorporation of intermodal noise covariance (Ko and Jun 2010), minimization of mutual information for channel selectivity (Baillet et al. 1999), row normalization of lead-field matrices, weighted normalization (Hong et al. 2013), and integration within a Bayesian framework (Henson et al. 2009).
Therefore, instead of maximizing the average end-to-end mutual information between the channel input and channel output, we now maximize an upper bound of the mutual information.
First, we derive the optimal source symbol covariance to maximize the mutual information between the channel input and the channel output when having the full knowledge of channel at the transmitters.
In this paper, the closed-form source symbol covariance is designed to maximize the mutual information between the channel input and the channel output of correlated wireless multi-hop MIMO systems when having the full knowledge of channel at the transmitters.
In [13], numerical results for the capacity of gamma-gamma atmospheric turbulence channels using on-off keying (OOK) formats are presented by maximizing the mutual information for this channel over a binomial input distribution.
Note that In,max is the maximum mutual information of sub-channel symbols for sub-channel n.
The conditional mutual information for this channel is, therefore, derived as can be seen in (14).
