ZF V-BLAST for Imperfect MIMO Channels using Average Performance Optimization

In practice, channel estimation is often imperfect due to the noise and interference. This paper extends the V-BLAST system to the imperfect channel state information by dividing the channel matrix into two parts. Upon an assumption that the channel estimation error vectors are independent complex Gaussian with zero mean and known second-order statistics, a symbol detection ordering criteria for ZF V-BLAST system is proposed which aims at providing, in each layer, the maximum average signal to interference-plus-noise ratio (SINR), over the random channel errors. This robust V-BLAST ordering rule takes the imperfect CSI into account, while maintaining the simple implementation of the V-BLAST structure. It is shown that the new ordering criterion is capable of achieving global performance optimization and outperforms the standard ZF V-BLAST when estimation errors exist.