{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,24]],"date-time":"2026-03-24T07:52:16Z","timestamp":1774338736443,"version":"3.50.1"},"reference-count":36,"publisher":"Wiley","issue":"1","license":[{"start":{"date-parts":[[2021,8,18]],"date-time":"2021-08-18T00:00:00Z","timestamp":1629244800000},"content-version":"vor","delay-in-days":229,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":["onlinelibrary.wiley.com"],"crossmark-restriction":true},"short-container-title":["Wireless Communications and Mobile Computing"],"published-print":{"date-parts":[[2021,1]]},"abstract":"<jats:p>Using unmanned aerial vehicles (UAVs) in emergency communications is a promising technology because of their flexible deployment, low cost, and high mobility. However, due to the limited energy of the onboard battery, the service duration of the UAV is greatly limited. In this paper, we study an emerging energy\u2010efficient UAV emergency network, where a UAV works as an aerial base station to serve a group of users with different statistical quality\u2010of\u2010service (QoS) constraints in the downlink. In particular, the energy efficiency of the UAV is defined as the sum effective capacity of the downlink users divided by the energy consumption of the UAV, which includes the energy consumed by communication and the energy consumed by hovering. Then, we formulate an optimization problem to maximize the energy efficiency of the UAV by jointly optimizing the UAV\u2019s altitude, downlink transmit power, and bandwidth allocation while meeting a statistical delay QoS requirement for each user. The formulated optimization problem is a nonlinear nonconvex optimization problem of fractional programming, which is difficult to solve. In order to deal with the nonconvex optimization problem, the following two steps are used. First, we transform the fractional objective function into a tractable subtractive function. Second, we decompose the original optimization problem into three subproblems, and then, we propose an efficient iterative algorithm to obtain the energy efficiency maximization value by using the Dinkelbach method, the block coordinate descent, and the successive convex optimization technique. Extensive simulation results show that our proposed algorithm has significant energy savings compared with a benchmark scheme.<\/jats:p>","DOI":"10.1155\/2021\/7595347","type":"journal-article","created":{"date-parts":[[2021,8,19]],"date-time":"2021-08-19T03:21:26Z","timestamp":1629343286000},"update-policy":"https:\/\/doi.org\/10.1002\/crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Energy Efficiency Maximization for UAV\u2010Assisted Emergency Communication Networks"],"prefix":"10.1155","volume":"2021","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-9253-2466","authenticated-orcid":false,"given":"Haibin","family":"Niu","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xinyu","family":"Zhao","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Liming","family":"Hou","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Dongjun","family":"Ma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"311","published-online":{"date-parts":[[2021,8,18]]},"reference":[{"key":"e_1_2_9_1_2","doi-asserted-by":"publisher","DOI":"10.1109\/MWC.2018.1800160"},{"key":"e_1_2_9_2_2","doi-asserted-by":"publisher","DOI":"10.1109\/MCOM.2016.7470933"},{"key":"e_1_2_9_3_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2021.3049387"},{"key":"e_1_2_9_4_2","doi-asserted-by":"publisher","DOI":"10.1109\/JIOT.2020.3013752"},{"key":"e_1_2_9_5_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2021.3055525"},{"key":"e_1_2_9_6_2","doi-asserted-by":"publisher","DOI":"10.1109\/TCOMM.2020.3030679"},{"key":"e_1_2_9_7_2","first-page":"1","article-title":"Mode selection and cooperative jamming for covert communication in D2D underlaid UAV networks","author":"Yang B.","year":"2021","journal-title":"IEEE Network"},{"key":"e_1_2_9_8_2","article-title":"Cisco visual networking index: global mobile data traffic forecast update, 2017\u20132022","volume":"2017","author":"Forecast G.","year":"2019","journal-title":"Update"},{"key":"e_1_2_9_9_2","first-page":"630","article-title":"Effective capacity: a wireless link model for support of quality of service","volume":"2","author":"Wu D.","year":"2003","journal-title":"IEEE Transactions on Wireless Communications"},{"key":"e_1_2_9_10_2","doi-asserted-by":"publisher","DOI":"10.1109\/COMST.2019.2929001"},{"key":"e_1_2_9_11_2","first-page":"3092","article-title":"Statistical-QoS driven energy efficiency optimization over green 5G mobile wireless networks","volume":"34","author":"Cheng W.","year":"2016","journal-title":"IEEE Journal on Selected Areas in Communications"},{"key":"e_1_2_9_12_2","doi-asserted-by":"publisher","DOI":"10.1109\/JSAC.2018.2864415"},{"key":"e_1_2_9_13_2","doi-asserted-by":"crossref","unstructured":"BabuN. 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