  In this paper, the secret-key capacity is maximized by optimizing the
downlink training sequence in a time division duplexing (TDD) massive
multiple-input-multiple-output (MIMO) scenario. Both single-user and multiple
user cases are considered. As opposed to previous works, the optimal training
sequence and the related secret-key capacity is characterized in closed-form in
the single-user case and the large antenna multiple-user case. Designs taking
into account a constraint on the maximal number of pilots are also proposed. In
the multiple-user case, both the max-min and the sum capacity criteria are
considered, including potential user priorities. In the end, it is shown that
massive MIMO boosts the secret-key capacity by leveraging: i) spatial
dimensionality gain and ii) array gain. Moreover, in the large antenna case,
the multiple-user capacity is obtained with no extra pilot overhead as compared
to the single-user case.
