  With the rapid development of various services in wireless communications,
spectrum resource has become increasingly valuable. Faster than Nyquist (FTN)
signaling, proposed in the 1970s, is a promising paradigm for improving
spectrum utilization. This paper proposes intelligent variable-packing-ratio
(VPR)-based transmissions for high spectrum efficiency (SE) and security,
respectively. Aided by deep learning (DL)-based estimation, the proposed scheme
for high SE can achieve a higher capacity with negligible modification to
existing communication paradigms (e.g., spectrum allocation or frame
structure). Also, for VPR-based secure transmission, a dynamic generation
scheme is proposed to produce randomly distributed positions to switch the
packing ratio, which can effectively avoid detections and attacks. In addition,
we propose a simplified DL-based packing ratio estimation for both of these two
scenarios so that the receiver can estimate the packing ratio without any
in-band or out-band control messages. Simulation results show that the proposed
simplified estimation achieves nearly the same accuracy and convergence speed
as the original multi-branch fully-connected structure with a complexity
reduction of 20 folds. Finally, we derive the closed-form SE of the proposed
VPR transmission under different channels. The numerical results validate the
correctness of the derivation and demonstrate the SE gains of the VPR scheme
beyond conventional Nyquist transmission.
