  Channel estimation is challenging in multi-antenna communication systems,
because of the large number of parameters to estimate. It is possible to
facilitate this task by using a physical model describing the multiple paths
constituting the channel, in the hope of reducing the number of unknowns in the
problem. Adjusting the number of estimated paths leads to a bias-variance
tradeoff. This paper explores this tradeoff, aiming to find the optimal number
of paths to estimate. Moreover, the approach based on a physical model is
compared to the classical least squares and Bayesian techniques. Finally, the
impact of channel estimation error on the system data rate is assessed.
