Covert Communication Assisted by Movable Time-Modulated Arrays

In this letter, we propose a novel method to improve the performance of covert communication via using movable time modulated array (MTMA). Compared with the conventional time modulated array (TMA), we leverage the spatial position of the antenna as a new dimension to enhance the degree of freedom in MTMA. First, we derive the closed-form expression for the covertness constraint by considering the characteristics of MTMA. On the basis, we jointly optimize the transmit power, blocklength, antenna position, and switch states of the MTMA to maximize the covert throughput, in which we propose an attention-enhanced swish deep neural network (ASDNN) to address the intractable optimization problem. Finally, numerical results demonstrate the superiority of the proposed scheme over benchmark schemes in terms of covert throughput.