ive fading). There is a new realization of the channel at every transmitted packet, if the channel remains invariant for the duration of the packet; otherwise, the variation of the channel is explicitly modeled in the signal detection. As mentioned earlier, there are NRX X NTX paths between the transmitter and the receiver where each channel is the sum of several FIR filters with different delay spreads. The channels may or may not be correlated. The MIMO schemes can be used with non-OFDM systems when the channel is modeled as flat fading such that yi(nT) = h1kxk(nT) n(nT). An important question is to what extent MIMO techniques can increase the throughput and improve the reliability of the wireless communication systems. This question can be answered by calculating the informa- tion theoretic capacity of a single-input-single-output (SISO) channel and comparing it with the capacity of single-input-multiple-output (SIMO), multiple-input-single-output (MISO), and MIMO channels. For a memoryless SISO channel (i.e., one transmit and one receive antenna), the channel capacity is given by CSISO = log2(1+y/h|2) where h is the normalized complex-valued gain/attenuation of a fixed wireless channel or that of a particular realization of a random channel and r = Es/No denotes the SNR at the receive antenna port. As the number of receive antennas increases, the statistics of channel capacity improve. Using NRX receive antennas and one transmit antenna, a SIMO system is formed with a capacity given by (when the channel is unknown to the transmitter) where hi is the gain of the ith channel corresponding to the ith receive-antenna. Note that increasing the value of NRX results in a logarithmic increase in average channel capacity. It can be shown that knowledge of the channel at the transmit- ter in SIMO cases does not provide any capacity benefit. In the case of MISO or transmit diversity, where the transmitter does not typically have knowledge of the channel, the capacity is given by CMISO = log2(1 y/NTx |hil2. It is noted f