hannel matrix H is a stochastic process; thus the associated channel capacity C(H) is a random variable. In this case, the ergodic channel capacity is defined as the average of instantaneous channel capacity over the distribution of H. The ergo- dic channel capacity of the MIMO transmission scheme is given by Cergodic where denotes the NTX X NTX covariance matrix of the channel input vector X. According to information theoretic concepts, this capacity cannot be achieved unless channel coding is employed across an infinite number of independently fading blocks. Let us focus on the case of perfect CSI at the receiver side and no CSI at the transmitter side, which implies that the maxi- mization of latter equation is now more restricted than in the previous case. Nevertheless, it has been shown in the literature that the optimal signal covariance matrix must be chosen according = I. This means that the antennas should transmit uncorrelated streams with the same average power. With this result, the ergodic MIMO channel capacity reduces to [15] E{log2(det[Iy/NTHH4])} It is obvious that this is not the Shannon capacity in a true sense, since as mentioned earlier one with perfect channel knowledge at the transmitter can choose a signal covariance matrix that outperforms = I case. Nevertheless, we refer to the preceding expression as the ergo- dic channel capacity with CSI at the receiver and no CSI at the transmitter. The capacity under channel ergodicity is defined as the average of the maximum value of the mutual information between the transmitted and the received signals, where the maximi- zation is carried out with respect to all possible transmit signal statistical distributions. Another measure of channel capacity that is frequently used is outage capacity. With outage capacity, the channel capacity is associated to an outage probability. Capacity is treated as a random variable which depends on the channel instantaneous response and remains constant during the transmission of a finite-length coded block of infor