ches. Therefore, the output SNR and the corresponding array gain increase linearly with the number of the diversity branches (i.e., the number of received antennas). The trade-off among transmission rate, error rate, and SINR for the scenarios where the transmitter has no channel knowledge and the receiver has perfect knowledge of channel state information has been studied in the literature. If the MIMO channel is assumed to be block-fading (A Block-Fading Channel is a model which assumes the fading-gain stochastic process is piece-wise constant over the blocks of N input symbols. The channel is modeled as a sequence of independent random variables, each representing the fading gain in a block.) and that the length of the transmitted codewords is less than or equal to the channel block length, and if the channel were perfectly known to the transmitter, we could choose a signaling rate equal to or less than channel capacity and achieve error-free trans- mission. The coding scheme to achieve capacity consists of performing modal decomposition, which decouples the MIMO channel into parallel SISO channels, and then using ideal SISO channel coding. In practice, turbo codes can achieve near MIMO channel capacity performance. If the channel is r2ej92 FIGURE 10-30 A generic linear combining receiver CHAPTER 10 The IEEE 802. 16m Physical Layer (Part II) unknown to the transmitter, modal decomposition is not possible. Since the channel is selected randomly according to a given fading distribution, there will always be a non-zero probability that a given transmission rate is not supported by the channel. We assume that the transmitted codeword is decoded successfully if the rate is at or below the mutual information, assuming a spatially white transmit covariance matrix, associated with the given channel realization. A decoding error is declared if the rate exceeds the mutual information. Therefore, if the transmitter does not have any knowledge of the channel, the PER would be equal to the outage probability associated wit