Due to their fast and flexible deployment, drones can support terrestrial networks for rapid information dissemination by broadcasting emergency messages to ground devices in public safety scenarios (e.g., bushfire and… Click to show full abstract
Due to their fast and flexible deployment, drones can support terrestrial networks for rapid information dissemination by broadcasting emergency messages to ground devices in public safety scenarios (e.g., bushfire and flood). In this paper, we consider a drone-initiated device-to-device-aided (D2D-aided) multihop multicast network where a drone is deployed to broadcast an emergency alert message to all terrestrial D2D users at the first time slot. After that, the D2D users that have successfully received the message become the active transmitters and multicast the message through multihop for the next time slots. Using stochastic geometry, we propose a general analytical framework to compute the link coverage probability, the mean local delay for a D2D user and the network coverage probability. The Monte Carlo simulation results confirm the accuracy of the proposed framework. Our results reveal the impacts of the different system parameters (i.e., height and transmit power of the drone and density and sensitivity radius of the D2D users) on the link performance and the network performance. It is found that a higher drone altitude provides better link and network coverage probabilities and lower mean local delay. The results show that under practical setups, the cell edge user located 2 km from the ground projection of the drone has a link coverage probability around 90% after 5 time slots and a mean local delay of 2.32 time slots with a drone height as low as 200 m.
               
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