Statistical prefiltering for MMSE and ML receivers with correlated MIMO channels

Abstract

The performance of wireless MIMO systems is known to suffer significantly from fading correlation between the antenna elements in a poor scattering environment if the transmitter is non-adaptive. However, acquiring accurate short-term channel state information to control TX adaptivity can be serious problem, in particular in FDD systems. Thus, we are proposing statistical linear transmit prefiltering schemes for MMSE and ML detection in the receiver that are solely based on long-term channel state information. It is demonstrated that long-term channel state information. It is demonstrated that long-term adaptive prefiltering can achieve a significant gain over non-adaptive (blind) transmission. Prefiltering for ML detection in a strongly correlated channel is shown to yield almost the same performance as the blind scheme in an uncorrelated channel. Moreover, exploiting long-term properties of the channel is especially appealing in terms of computational complexity and channel estimation, as the long-term channel estimation process can be carried out in a wide time window.