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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.<\/jats:p>","DOI":"10.1186\/s13638-021-01987-3","type":"journal-article","created":{"date-parts":[[2021,4,28]],"date-time":"2021-04-28T17:03:59Z","timestamp":1619629439000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":12,"title":["Trajectory planning in UAV emergency networks with potential underlaying D2D communication based on K-means"],"prefix":"10.1186","volume":"2021","author":[{"given":"Shuo","family":"Zhang","sequence":"first","affiliation":[]},{"ORCID":"https:\/\/orcid.org\/0000-0002-5671-266X","authenticated-orcid":false,"given":"Shuo","family":"Shi","sequence":"additional","affiliation":[]},{"given":"Tianming","family":"Feng","sequence":"additional","affiliation":[]},{"given":"Xuemai","family":"Gu","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2021,4,28]]},"reference":[{"issue":"4","key":"1987_CR1","doi-asserted-by":"publisher","first-page":"1801","DOI":"10.1109\/COMST.2014.2319555","volume":"16","author":"A Asadi","year":"2014","unstructured":"A. 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