Matches in SemOpenAlex for { <https://semopenalex.org/work/W3026084580> ?p ?o ?g. }
Showing items 1 to 91 of
91
with 100 items per page.
- W3026084580 endingPage "155014772092637" @default.
- W3026084580 startingPage "155014772092637" @default.
- W3026084580 abstract "Data volume demand has increased dramatically due to huge user device increasement along with the development of cellular networks. And macrocell in 5G networks may encounter sudden traffic due to dense users caused by sports or celebration activities. To resolve such temporal hotspot, additional network access point has become a new solution for it, and unmanned aerial vehicle equipped with base stations is taken as an effective solution for coverage and capacity improvement. How to plan the best three-dimensional location of the aerial base station according to the users’ business needs and service scenarios is a key issue to be solved. In this article, first, aiming at maximizing the spectral efficiency and considering the effects of line-of-sight and non-line-of-sight path loss for 5G mmWave networks, a mathematical optimization model for the location planning of the aerial base station is proposed. For this model, the model definition and training process of deep Q-learning are constructed, and through the large-scale pre-learning experience of different user layouts in the training process to gain experience, finally improve the timeliness of the training process. Through the simulation results, it points out that the optimization model can achieve more than 90% of the theoretical maximum spectral efficiency with acceptable service quality." @default.
- W3026084580 created "2020-05-29" @default.
- W3026084580 creator A5028799457 @default.
- W3026084580 creator A5064125880 @default.
- W3026084580 creator A5065282041 @default.
- W3026084580 creator A5066809562 @default.
- W3026084580 creator A5070348919 @default.
- W3026084580 creator A5090076224 @default.
- W3026084580 date "2020-05-01" @default.
- W3026084580 modified "2023-10-04" @default.
- W3026084580 title "Three-dimensional aerial base station location for sudden traffic with deep reinforcement learning in 5G mmWave networks" @default.
- W3026084580 cites W2031834036 @default.
- W3026084580 cites W2093144928 @default.
- W3026084580 cites W2131049857 @default.
- W3026084580 cites W2142246654 @default.
- W3026084580 cites W2145339207 @default.
- W3026084580 cites W2163168488 @default.
- W3026084580 cites W2558431499 @default.
- W3026084580 cites W2886509985 @default.
- W3026084580 cites W2891453704 @default.
- W3026084580 cites W2909275884 @default.
- W3026084580 cites W2962896865 @default.
- W3026084580 cites W2963553511 @default.
- W3026084580 cites W2963615009 @default.
- W3026084580 cites W2972656576 @default.
- W3026084580 cites W2980338210 @default.
- W3026084580 cites W2981078741 @default.
- W3026084580 cites W2988592481 @default.
- W3026084580 cites W3098405735 @default.
- W3026084580 cites W3102527375 @default.
- W3026084580 doi "https://doi.org/10.1177/1550147720926374" @default.
- W3026084580 hasPublicationYear "2020" @default.
- W3026084580 type Work @default.
- W3026084580 sameAs 3026084580 @default.
- W3026084580 citedByCount "5" @default.
- W3026084580 countsByYear W30260845802021 @default.
- W3026084580 countsByYear W30260845802022 @default.
- W3026084580 countsByYear W30260845802023 @default.
- W3026084580 crossrefType "journal-article" @default.
- W3026084580 hasAuthorship W3026084580A5028799457 @default.
- W3026084580 hasAuthorship W3026084580A5064125880 @default.
- W3026084580 hasAuthorship W3026084580A5065282041 @default.
- W3026084580 hasAuthorship W3026084580A5066809562 @default.
- W3026084580 hasAuthorship W3026084580A5070348919 @default.
- W3026084580 hasAuthorship W3026084580A5090076224 @default.
- W3026084580 hasBestOaLocation W30260845801 @default.
- W3026084580 hasConcept C127162648 @default.
- W3026084580 hasConcept C137246740 @default.
- W3026084580 hasConcept C153646914 @default.
- W3026084580 hasConcept C154945302 @default.
- W3026084580 hasConcept C2778291847 @default.
- W3026084580 hasConcept C31258907 @default.
- W3026084580 hasConcept C41008148 @default.
- W3026084580 hasConcept C44154836 @default.
- W3026084580 hasConcept C68649174 @default.
- W3026084580 hasConcept C79403827 @default.
- W3026084580 hasConcept C97541855 @default.
- W3026084580 hasConceptScore W3026084580C127162648 @default.
- W3026084580 hasConceptScore W3026084580C137246740 @default.
- W3026084580 hasConceptScore W3026084580C153646914 @default.
- W3026084580 hasConceptScore W3026084580C154945302 @default.
- W3026084580 hasConceptScore W3026084580C2778291847 @default.
- W3026084580 hasConceptScore W3026084580C31258907 @default.
- W3026084580 hasConceptScore W3026084580C41008148 @default.
- W3026084580 hasConceptScore W3026084580C44154836 @default.
- W3026084580 hasConceptScore W3026084580C68649174 @default.
- W3026084580 hasConceptScore W3026084580C79403827 @default.
- W3026084580 hasConceptScore W3026084580C97541855 @default.
- W3026084580 hasFunder F4320321001 @default.
- W3026084580 hasIssue "5" @default.
- W3026084580 hasLocation W30260845801 @default.
- W3026084580 hasLocation W30260845802 @default.
- W3026084580 hasOpenAccess W3026084580 @default.
- W3026084580 hasPrimaryLocation W30260845801 @default.
- W3026084580 hasRelatedWork W1972062186 @default.
- W3026084580 hasRelatedWork W1982136315 @default.
- W3026084580 hasRelatedWork W2042799635 @default.
- W3026084580 hasRelatedWork W2089019167 @default.
- W3026084580 hasRelatedWork W2290772520 @default.
- W3026084580 hasRelatedWork W2495022702 @default.
- W3026084580 hasRelatedWork W2585072051 @default.
- W3026084580 hasRelatedWork W2736348906 @default.
- W3026084580 hasRelatedWork W2794570086 @default.
- W3026084580 hasRelatedWork W2966774092 @default.
- W3026084580 hasVolume "16" @default.
- W3026084580 isParatext "false" @default.
- W3026084580 isRetracted "false" @default.
- W3026084580 magId "3026084580" @default.
- W3026084580 workType "article" @default.