Improved Network Performance for Swarm Drones Communication

Recently, unmanned aerial vehicles (UAVs) have emerged as an appealing option for many different applications such as logistics, search and rescue missions, precision architecture, and many more. Applications like these normally cover a large area and may require a network handover between access points or base stations to maintain the active connection with the ground control station (GCS). Due to the high mobility characteristic of UAVs, some challenges are presented when performing handover in UAV networks. First, high mobility creates more fluctuations in the signal strength data, which is a key factor in handover decisions and may result in unnecessary handovers. To address these issues, this thesis proposes the usage of fuzzy-based anticipatory networking techniques to develop an effective network handover prediction system.