Symbol detection in V-BLAST architectures under channel estimation errors

We introduce a modified vertical Bell laboratories layered space-time (V-BLAST) detection algorithm to reduce unexpected effects of the channel estimation errors. Assuming that the channel estimation errors are independent and identically distributed Gaussian random variables, we derive a better nulling weight, which minimizes the power of various terms generated by the channel estimation errors. The symbol ordering operation is also modified by choosing the minimum mean-square error symbol at each iteration. The proposed detection algorithm requires the knowledge of channel estimation error's variance, but its performance is robust to the inaccurate estimation of it. The simulation results show that the performance of the proposed algorithm is superior to that of the conventional VBLAST detection algorithm when channel estimation errors exist.