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Joint Trajectory and Energy Efficiency Optimization for Multi-UAV Assisted Offloading

In multi-UAV assisted offloading environment, to enhance the offloading transmission rate and energy efficiency (EE) with limitation of pre-assigned docking station for UAV and users' of-floading task size, UAVs' service assignment with users, users' transmit power and time-scheduling, as well as UAVs' trajectory should be jointly optimized. However, these dynamics factors are inter-evolved with each other, especially the service assignment among UAVs and users is indicated by the binary vector that makes aforementioned issue be a mixed integer non-convex optimization that is challenge to be solved. This paper proposes a clustering-combined successive convex approximation (SCA) approach to maximize the users' EE with jointly optimized the service assignment, users' transmission power as well as UAVs' trajectory. Different from the approaches that simple relax the binary service assignment indication in to the consecutive space, and then take block coordinate descent (BCD) technique for energy and trajectory optimization, the proposed clustering-combined SCA can effectively optimize UAVs' trajectory as well as users' offloading scheduling in multi-UAV scenario. The numeral simulation reveals which outperform those relaxation method with respect to users' offloading EE and UAV's trajectory.