A subspace-based channel model for frequency selective time variant MIMO channels

In this contribution we propose a subspace-based channel model suitable to represent frequency selective time variant MIMO channels. This approach captures the true nature of the MIMO channel maintaining the spatial correlation present between the antenna arrays. Correlation in time and frequency is conserved as well. The decomposition into eigenmodes, which form the channel subspace, gives an interesting interpretation of the channel's eigenstructure. These investigations lead to a very efficient method to synthesize new channels with the same correlation in time, frequency and space of a reference channel. The model allows the interpolation of a channel in order to retrieve more samples in frequency and time to perform statistical analysis such as bit error rate and capacity curves. In addition the model allows the generation of new random channels with the same spatial, time, and frequency correlations of a reference channel, which, for instance, could be obtained from measurements.