  In communication networks secrecy constraints usually incur an extra limit in
capacity or generalized degrees-of-freedom (GDoF), in the sense that a penalty
in capacity or GDoF is incurred due to the secrecy constraints. Over the past
decades a significant amount of effort has been made by the researchers to
understand the limits of secrecy constraints in communication networks. In this
work, we focus on how to remove the secrecy constraints in communication
networks, i.e., how to remove the GDoF penalty due to secrecy constraints. We
begin with three basic settings: a two-user symmetric Gaussian interference
channel with confidential messages, a symmetric Gaussian wiretap channel with a
helper, and a two-user symmetric Gaussian multiple access wiretap channel.
Interestingly, in this work we show that adding common randomness at the
transmitters can totally remove the penalty in GDoF or GDoF region of the three
settings considered here. The results reveal that adding common randomness at
the transmitters is a powerful way to remove the secrecy constraints in
communication networks in terms of GDoF performance. Common randomness can be
generated offline. The role of the common randomness is to jam the information
signal at the eavesdroppers, without causing too much interference at the
legitimate receivers. To accomplish this role, a new method of Markov
chain-based interference neutralization is proposed in the achievability
schemes utilizing common randomness. From the practical point of view, we hope
to use less common randomness to remove secrecy constraints in terms of GDoF
performance. With this motivation, for most of the cases we characterize the
minimal GDoF of common randomness to remove secrecy constraints, based on our
derived converses and achievability.
