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Predictive decision and reliable accessing for UAV communication in space-air-ground integrated networks

Bowen Zeng, Zhongshan Zhang, Xuhui Ding, Xiangyuan Bu, Jianping An

2022China Communications19 citationsDOI

Abstract

The cooperation of multiple Unmanned Aerial Vehicles (UAVs) has become a promising scenario in Space-Air-Ground Integrated Networks (SA-GINs) recently due to their widespread applications, where wireless communication is a basic necessity and is normally categorized into control and non-payload communication (CNPC) as well as payload communication. In this paper, we attempt to tackle two challenges of UAV communication respectively on establishing reliable CNPC links against the high mobility of UAVs as well as changeable communication conditions, and on offering dynamic resource optimization for Quality-of-Service (QoS) guaranteed payload communication with variable link connectivity. Firstly, we propose the concept of air controlling center (ACC), a virtual application equipped on the infrastructure in SAGINs, which can collect global information for estimating UAV trajectory and communication channels. We then introduce the knapsack problem for modelling resource optimization of UAV communication in order to provide optimal access points for both CNPC and payload communication. Meanwhile, using the air controlling information, predictive decision algorithm and handover strategy are introduced for the reliable connection with multiple access points. Simulation results demonstrate that our proposal ensures an approximate always-on reliable accessing of communication links and outperforms the existing methods against high mobility, sparse distribution, and physical obstacles.

Topics & Concepts

Payload (computing)Computer scienceHandoverKnapsack problemQuality of serviceWirelessCommunications systemComputer networkResource allocationDistributed computingReal-time computingTelecommunicationsNetwork packetAlgorithmUAV Applications and OptimizationSatellite Communication SystemsDistributed Control Multi-Agent Systems
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