Covert Communication of IRS-Assisted Wireless Networks With Stochastic Geometry Approach

In this letter, we investigate the covert communication in wireless networks with intelligent reflecting surface (IRS), where the Gauss-Poisson process (GPP) is invoked to model the positions of interference nodes TXs and IRSs. The covert communication system is composed of a covert signals transmitter (Alice) and a signals receiver (Bob). A warden (Willie) is presented with the aim of detecting whether Alice is transmitting covert signals to Bob. Specially, we derive analytical expressions for the average detection error probability, and obtain the average minimum detection error probability under Willie's conservative detection strategy as well as the maximum covert throughput under Alice's conservative transmission strategy. It reveals that deploying IRSs can enhance the covertness of the system. Moreover, in additive white Gaussian noise (AWGN) channels, we optimize Alice's position to maximize the covert throughput and find that IRSs can also effectively increase the covert throughput of the considered system under appropriate interferers' density. Furthermore, in the above optimal scenario, covertness and reliability constraint have a greater impact on covert throughput at low and high interferers' density, respectively.