Abstract: A design method of a high energy efficiency unmanned aerial vehicle (UAV) green data acquisition system belongs to the technical field of data acquisition and optimization for UAV uplink communication. Firstly, a system optimization objective is constructed; and in a uplink communication network of a single UAV and ground sensors, the UAV receives data periodically. Secondly, according to a constructed optimization problem, the optimization objective is maximization of EE({W},{t},{S}). Finally, an original problem is decomposed into two approximate concave-convex fractional sub-problem based on a block coordinate descent method and a successive convex approximation technique to obtain a suboptimal solution; an overall iterative algorithm is proposed: in each iteration, by solving the sub-problems, wake-up scheduling S, time slot t and UAV trajectory W are alternately optimized. The solution obtained in each iteration is used as the input of next iteration.

Abstract: The present invention provides a design method of a high energy efficiency Unmanned Aerial Vehicle (UAV) communication system assisted by an intelligent reflecting surface, and belongs to the technical field of UAV communication network energy efficiency optimization. A communication process comprises two transmission links, one link is directly sent from an information source to an information sink, and the other link is reflected and transmitted by an intelligent reflecting surface attached to a UAV. The two links exist simultaneously. Based on an idea of block iteration, an original problem is decomposed into three sub-problems, and a non-convex optimization problem is transformed into solvable concave-convex fractional program problems by a continuous convex approximation technique.

Abstract: A design method of a high energy efficiency unmanned aerial vehicle (UAV) green data acquisition system belongs to the technical field of data acquisition and optimization for UAV uplink communication. Firstly, a system optimization objective is constructed; and in a uplink communication network of a single UAV and ground sensors, the UAV receives data periodically. Secondly, according to a constructed optimization problem, the optimization objective is maximization of EE({W},{t},{S}). Finally, an original problem is decomposed into two approximate concave-convex fractional sub-problem based on a block coordinate descent method and a successive convex approximation technique to obtain a suboptimal solution; an overall iterative algorithm is proposed: in each iteration, by solving the sub-problems, wake-up scheduling S, time slot t and UAV trajectory W are alternately optimized. The solution obtained in each iteration is used as the input of next iteration.