  This work considers the joint design of training and data transmission in
physical-layer secret communication systems, and examines the role of
artificial noise (AN) in both of these phases. In particular, AN in the
training phase is used to prevent the eavesdropper from obtaining accurate
channel state information (CSI) whereas AN in the data transmission phase can
be used to mask the transmission of the confidential message. By considering
AN-assisted training and secrecy beamforming schemes, we first derive bounds on
the achievable secrecy rate and obtain a closed-form approximation that is
asymptotically tight at high SNR. Then, by maximizing the approximate
achievable secrecy rate, the optimal power allocation between signal and AN in
both training and data transmission phases is obtained for both conventional
and AN-assisted training based schemes. We show that the use of AN is necessary
to achieve a high secrecy rate at high SNR, and its use in the training phase
can be more efficient than that in the data transmission phase when the
coherence time is large. However, at low SNR, the use of AN provides no
advantage since CSI is difficult to obtain in this case. Numerical results are
presented to verify our theoretical claims.
