  Discriminatory channel estimation (DCE) is a recently developed strategy to
enlarge the performance difference between a legitimate receiver (LR) and an
unauthorized receiver (UR) in a multiple-input multiple-output (MIMO) wireless
system. Specifically, it makes use of properly designed training signals to
degrade channel estimation at the UR which in turn limits the UR's
eavesdropping capability during data transmission. In this paper, we propose a
new two-way training scheme for DCE through exploiting a whitening-rotation
(WR) based semiblind method. To characterize the performance of DCE, a
closed-form expression of the normalized mean squared error (NMSE) of the
channel estimation is derived for both the LR and the UR. Furthermore, the
developed analytical results on NMSE are utilized to perform optimal power
allocation between the training signal and artificial noise (AN). The
advantages of our proposed DCE scheme are two folds: 1) compared to the
existing DCE scheme based on the linear minimum mean square error (LMMSE)
channel estimator, the proposed scheme adopts a semiblind approach and achieves
better DCE performance; 2) the proposed scheme is robust against active
eavesdropping with the pilot contamination attack, whereas the existing scheme
fails under such an attack.
