Fading countermeasures with cognitive topology management for aerial mesh networks

Based on recent developments in the area of lithium polymer batteries and carbon fiber-reinforced plastic materials Micro Unmanned Aerial Vehicles (MUAVs) significantly gain in importance. One of the challenges in using third party cellular networks for MUAV utilization lies in the directivity of the widely used antennas, which are usually illuminating the ground area but not the aerial user space. Hence, we additionally introduce a self-configuring mesh network between the MUAVs based on Inter-Drone-Links (IDL) in order to compensate connection losses by means of relaying. Besides, these IDL enable for real-time calculation of sensing gradients and allow the agents to determine potential fields for influencing the mobility behavior. The objective of our proposed cognitive and sensor aided mesh network is to maximize the spatial sensing coverage as well as the connectivity between the cooperative MUAVs. Besides these contrary optimization goals, we developed bio-inspired algorithms that seek concurrently for a global target and a coherent topology of the swarm in order to avoid self-separations. In this paper we particularly focus on an agent-based methodology for communication aware mobility behavior of self-organizing MUAVs. These MUAVs operate at high vehicular speeds and provoke fast topology changes leading to a transient aerial mesh network. To determine the key figures of the system, the performance of dynamically adapted mobility algorithms is analyzed and compared under lognormal channel conditions.