Probabilistic Transmission in Covert Cell-Free IoT Networks

In this paper, we develop a covert cell-free Internet of Things (CF-IoT) network and propose a probabilistic covert transmission scheme, where the transmitter (Alice) and access points (APs) opportunistically initiate information transmission and artificial noise (AN) based on channel state information (CSI), respectively, and both Alice and APs are scheduled by a central processing unit (CPU). Meanwhile, we utilize APs to periodically broadcast pilot signals and channel inversion power control (CIPC) strategy to protect the location privacy of the transmitter from powerful eavesdroppers (Eves), who can adopt different detection schemes, namely cooperative detection scheme and independent detection scheme. Then, the minimum detection error probability (DEP) of Eve under different detection schemes has been derived, respectively. Moreover, in view of the fact that multiple APs satisfy the transmission conditions simultaneously, energy efficiency-oriented AP scheduling (EEAS) scheme and legitimate link-oriented AP scheduling (LLAS) scheme have been proposed, and the covert performance of each scheme has been analyzed, including the average covert throughput and covert energy efficiency (CEE), and the closed form expressions of the optimal threshold and transmission energy that maximize covert throughput are obtained. Simulation results demonstrate that the proposed CSI-based probabilistic transmission scheme and EEAS scheme outperform other benchmark schemes in terms of covert performance, which significantly enhances the covertness of CF-IoT networks.