Biblio

We present a covert (low probability of detection) communication scheme that exploits the node multiplicity and channel variations in wireless broadcast networks. The transmitter hides the covert (private) message by superimposing it onto a non-covert (public) message such that the total transmission power remains the same whether or not the covert message is transmitted. It makes the detection of the covert message impossible unless the non-covert message is decoded. We exploit the multiplicity of non-covert messages (users) to provide a degree of freedom in choosing the non-covert message such that the total detection error probability (sum of the probability of false alarm and missed detection) is maximized. We also exploit the channel variation to minimize the throughput loss on the non-covert message by sending the covert message only when the transmission rate of the non-covert message is low. We show that the total detection error probability converges fast to 1 as the number of non-covert users increases and that the total detection error probability increases as the transmit power increases, without requiring a pre-shared secret among the nodes.

Covert or low probability of detection communication is crucial to protect user privacy and provide a strong security. We analyze the joint impact of imperfect knowledge of the channel gain (channel uncertainty) and noise power (noise uncertainty) on the average probability of detection error at the eavesdropper and the covert throughput in Rayleigh fading channel. We characterize the covert throughput gain provided by the channel uncertainty as well as the covert throughput loss caused by the channel fading as a function of the noise uncertainty. Our result shows that the channel fading is essential to hiding the signal transmission, particularly when the noise uncertainty is below a threshold and/or the receive SNR is above a threshold. The impact of the channel uncertainty on the average probability of detection error and covert throughput is more significant when the noise uncertainty is larger.