Unmanned aerial vehicles (UAVs) as aerial relays have found many applications in the current communication network. Since the air‐to‐ground (AtG) link differs from the terrestrial link, ensuring a reliable AtG transmission remains to be a meaningful issue. This article investigates that a UAV works as an aerial relay to forward information from multiple access points to multiple remote base stations in an emergency situation. Using the full‐duplex decode‐and‐forward relaying mode, we formulate a problem to minimize the maximum outage probability among all links, jointly optimizing the UAV altitude, power control, and bandwidth allocation. The outage probability function takes into account the line‐of‐sight probability‐based AtG fading and the self‐interference introduced by full‐duplex relaying, both of which make our formulated problem nonconvex. We reformulate the outage probability function into a more tractable function. Then, we decouple the original problem into two subproblems, that is, altitude optimization as well as power control and bandwidth allocation. Each subproblem is solved by the successive convex optimization technique, and an overall iteration algorithm is proposed to solve the original problem based on the block coordinate descent theory. Simulation results reveal the reliability gain of our proposed algorithm compared with our designed benchmark. Besides, the optimal UAV three‐dimensional location that minimizes the global min‐max outage probability is found by numerical simulations. Finally, the average throughput gain can also be obtained by our proposed algorithm.

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With the rapid development of electric vehicles and artificial intelligence technology, the automatic driving industry has entered a rapid development stage. However, there is a risk of traffic accidents due to the blind spot of vision, whether autonomous vehicles or traditional vehicles. In this article, a multi-sensor fusion perception method is proposed, in which the semantic information from the camera and the range information from the LiDAR are fused at the data layer and the LiDAR point cloud containing semantic information is clustered to obtain the type and location information of the objects. Based on the sensor equipments deployed on the roadside, the sensing information processed by the fusion method is sent to the nearby vehicles in real-time through 5G and V2X technology for blind spot early warning, and its feasibility is verified by experiments and simulations. The blind spot warning scheme based on roadside multi-sensor fusion perception proposed in this article has been experimentally verified in the closed park, which can obviously reduce the traffic accidents caused by the blind spot of vision, and is of great significance to improve traffic safety.

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