{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,8,2]],"date-time":"2024-08-02T06:30:47Z","timestamp":1722580247983},"reference-count":66,"publisher":"MDPI AG","issue":"15","license":[{"start":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T00:00:00Z","timestamp":1690934400000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Sensors"],"abstract":"Deploying unmanned aerial vehicles (UAVs) as aerial base stations is an exceptional approach to reinforce terrestrial infrastructure owing to their remarkable flexibility and superior agility. However, it is essential to design their flight trajectory effectively to make the most of UAV-assisted wireless communications. This paper presents a novel method for improving wireless connectivity between UAVs and terrestrial users through effective path planning. This is achieved by developing a goal-directed trajectory planning method using active inference. First, we create a global dictionary using traveling salesman problem with profits (TSPWP) instances executed on various training examples. This dictionary represents the world model and contains letters representing available hotspots, tokens representing local paths, and words depicting complete trajectories and hotspot order. By using this world model, the UAV can understand the TSPWP\u2019s decision-making grammar and how to use the available letters to form tokens and words at various levels of abstraction and time scales. With this knowledge, the UAV can assess encountered situations and deduce optimal routes based on the belief encoded in the world model. Our proposed method outperforms traditional Q-learning by providing fast, stable, and reliable solutions with good generalization ability.<\/jats:p>","DOI":"10.3390\/s23156873","type":"journal-article","created":{"date-parts":[[2023,8,2]],"date-time":"2023-08-02T15:17:17Z","timestamp":1690989437000},"page":"6873","source":"Crossref","is-referenced-by-count":1,"title":["A Goal-Directed Trajectory Planning Using Active Inference in UAV-Assisted Wireless Networks"],"prefix":"10.3390","volume":"23","author":[{"ORCID":"http:\/\/orcid.org\/0000-0002-6598-2805","authenticated-orcid":false,"given":"Ali","family":"Krayani","sequence":"first","affiliation":[{"name":"Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy"},{"name":"Italian National Inter-University Consortium for Telecommunications (CNIT), 43124 Parma, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-6195-3134","authenticated-orcid":false,"given":"Khalid","family":"Khan","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0003-1515-120X","authenticated-orcid":false,"given":"Lucio","family":"Marcenaro","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy"},{"name":"Italian National Inter-University Consortium for Telecommunications (CNIT), 43124 Parma, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0002-9626-3483","authenticated-orcid":false,"given":"Mario","family":"Marchese","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy"},{"name":"Italian National Inter-University Consortium for Telecommunications (CNIT), 43124 Parma, Italy"}]},{"ORCID":"http:\/\/orcid.org\/0000-0001-6617-1417","authenticated-orcid":false,"given":"Carlo","family":"Regazzoni","sequence":"additional","affiliation":[{"name":"Department of Electrical, Electronic, Telecommunications Engineering and Naval Architecture, University of Genoa, 16145 Genoa, Italy"},{"name":"Italian National Inter-University Consortium for Telecommunications (CNIT), 43124 Parma, Italy"}]}],"member":"1968","published-online":{"date-parts":[[2023,8,2]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"2241","DOI":"10.1109\/JIOT.2018.2887086","article-title":"UAV Communications for 5G and Beyond: Recent Advances and Future Trends","volume":"6","author":"Li","year":"2019","journal-title":"IEEE Internet Things J."},{"key":"ref_2","doi-asserted-by":"crossref","unstructured":"Krayani, A., Baydoun, M., Marcenaro, L., Gao, Y., and Regazzoni, C.S. 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