Adaptive MIMO Transmission for Exploiting the

Capacity of Spatially Correlated Channels


Antonio Forenza, Matthew R. McKay, Ashish Pandharipande,  Robert W. Heath Jr, and Iain B. Collings



submitted to IEEE Trans. on Vehic. Tech., May 2005.


We consider a novel low-complexity adaptive multiple-input multiple-output (MIMO) transmission approach. The approach is based on switching between low-complexity schemes including statistical beamforming, double space-time transmit diversity, and spatial multiplexing, depending on the changing channel statistics, as a practical means of approaching the spatially-correlated MIMO channel capacity. We first derive new ergodic capacity expressions for each MIMO transmission scheme in spatially-correlated channels. Based on these results, we demonstrate that adaptive switching between MIMO schemes yields significant capacity gains over fixed transmission schemes. We also derive accurate analytical approximations for the optimal signal-to-noise ratio (SNR) switching thresholds, which correspond to the crossing-points of the capacity curves. These thresholds are shown to vary depending on the spatial correlation, and are used to identify key switching parameters. Finally, we propose a practical switching algorithm that is shown to yield significant spectral efficiency improvements over non-adaptive schemes for typical channel scenarios.