Trajectory planning in UAV emergency networks with potential underlaying D2D communication based on K-means

Shuo Zhang,Xuemai Gu,Tianming Feng,Shuo Shi

doi:10.1186/s13638-021-01987-3

Abstract

At present, unmanned aerial vehicles (UAVs) have been widely used in communication systems, and the fifth-generation wireless system (5G) has further promoted the vigorous development of them. The trajectory planning of UAV is an important factor that affects the timeliness and completion of missions, especially in scenarios such as emergency communications and post-disaster rescue. In this paper, we consider an emergency communication network where a UAV aims to achieve complete coverage of potential underlaying device-to-device (D2D) users. Trajectory planning issues are grouped into clustering and supplementary phases for optimization. Aiming at trajectory length and sum throughput, two trajectory planning algorithms based on K-means are proposed, respectively. In addition, in order to balance sum throughput with trajectory length, we present a joint evaluation index. Then relying on this index, a third trajectory optimization algorithm is further proposed. Simulation results show the validity of the proposed algorithms which have advantages over the well-known benchmark scheme in terms of trajectory length and sum throughput.

Highlights

1.1 Motivation With the continuous update and iteration of communication technology, the era of fifth-generation wireless systems (5G) has quietly come to us and gradually opened up a new phase of interconnection of all things
In order to better balance the relationship between trajectory length and sum throughput, we present a joint evaluation index and propose algorithm 3 based on this index
3 Trajectory length optimization algorithm based on improved K‐means In order to make unmanned aerial vehicle (UAV) trajectory length as small as possible, we propose trajectory length optimization algorithm based on improved K-means (TLOA-IK)

Summary

Introduction

1.1 Motivation With the continuous update and iteration of communication technology, the era of fifth-generation wireless systems (5G) has quietly come to us and gradually opened up a new phase of interconnection of all things. The main optimization objective of UAV trajectory planning is mission completion time or the number of stop points, without taking into account throughput performance of the GT side. 1.3 Contributions This paper studies the trajectory planning problem of UAV emergency networks for potential underlaying DUs with Homogeneous Poisson Point Process (HPPP) distribution. The selection method of initial clustering centers is improved, and the improved K-means algorithm is used to obtain the set of stop points in the first stage to construct the initial reference trajectory and determine the initial coverage. 3.2 Stop point selection strategy When initial SPs wuk are unable to achieve full coverage of the target area, i.e., there are DUs that cannot communicate effectively with UAV, the relationships between uncovered DUs and reference trajectory need to be determined.

Optimization of the clustering phase

Conclusion