Unmanned Aerial Vehicles (UAVs) or drones have become extremely popular and are used in various commercial applications. They can provide better services for these applications if they work together and form a UAV network. The Flying Ad-hoc Network (FANET), Internet of Drones (IoD) and the private UAV network are such type of UAV networks invented in the past. A private UAV network is beneficial for these applications where all UAVs belong to a person or one organisation. In this research, we implemented the communication between UAVs and UAV to the ground station at the Media Access Control (MAC) layer in the private UAV network by switching through UAV nodes. To test this communication, we implemented two small private UAV testbed networks with Storm 4 Mini and AR 2.0 UAV models. In the Storm 4 Mini private UAV network, the video signals were transmitted over the 5GHz network while each UAV was controlled through the analog signals from their remote controller over the 2.4 GHz frequency spectrum. Whereas, control and video signals were transmitted over the 2.4 GHz network in the wireless frame format for the AR 2.0 UAV testbed network. This research outlines the real-time practical problems for communication between UAVs and UAV to the ground station in the private UAV network and provides the solutions for those problems. The video transmission delay from each UAV to the ground station was one of them. This video delay was presented in the network due to the use of a common single communication channel between UAVs. To resolve this issue, we proposed and developed new data and control channels that can be used for the communication between UAVs and UAV to the ground station in this UAV network. This new channelisation avoids congestion and packet drop for video and control signal traffic in this network. In a private UAV network where UAVs are connected in tandem, the UAVs that are in the middle of the network have to carry the control and video signals of other UAVs. Given the limited processing power and dynamic memory capacity of UAVs, this would increase the queuing delays for transmission these signals. As such, we studied the frame formats of existing control, feedback and video signals for the smartphone operated commercial UAV and proposed a new approach of signaling for control and feedback frames for the private UAV network. The control and feedback signals transmission delays from each UAV to the ground station were calculated with both types of signaling mechanisms for this UAV network. The result of these delays comparison shows that newly developed signaling mechanism for the private UAV network with the single control and feedback frame has less delay on the average.
History
Location
Central Queensland University
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