Matches in SemOpenAlex for { <https://semopenalex.org/work/W3211830369> ?p ?o ?g. }
- W3211830369 endingPage "2565" @default.
- W3211830369 startingPage "2547" @default.
- W3211830369 abstract "In recent years, with the rapid enhancement of computing power, deep learning methods have been widely applied in wireless networks and achieved impressive performance. To effectively exploit the information of graph-structured data as well as contextual information, graph neural networks (GNNs) have been introduced to address a series of optimization problems of wireless networks. In this overview, we first illustrate the construction method of wireless communication graph for various wireless networks and simply introduce the progress of several classical paradigms of GNNs. Then, several applications of GNNs in wireless networks such as resource allocation and several emerging fields, are discussed in detail. Finally, some research trends about the applications of GNNs in wireless communication systems are discussed." @default.
- W3211830369 created "2021-11-22" @default.
- W3211830369 creator A5014343967 @default.
- W3211830369 creator A5046019676 @default.
- W3211830369 creator A5056225611 @default.
- W3211830369 creator A5057209439 @default.
- W3211830369 creator A5069049205 @default.
- W3211830369 creator A5085579919 @default.
- W3211830369 creator A5089676168 @default.
- W3211830369 date "2021-01-01" @default.
- W3211830369 modified "2023-10-15" @default.
- W3211830369 title "An Overview on the Application of Graph Neural Networks in Wireless Networks" @default.
- W3211830369 cites W2558748708 @default.
- W3211830369 cites W2616867685 @default.
- W3211830369 cites W2797462110 @default.
- W3211830369 cites W2807731816 @default.
- W3211830369 cites W2807873315 @default.
- W3211830369 cites W2808409763 @default.
- W3211830369 cites W2809343047 @default.
- W3211830369 cites W2903871660 @default.
- W3211830369 cites W2904832339 @default.
- W3211830369 cites W2911286998 @default.
- W3211830369 cites W2935726879 @default.
- W3211830369 cites W2962883549 @default.
- W3211830369 cites W2962886429 @default.
- W3211830369 cites W2963084622 @default.
- W3211830369 cites W2963241486 @default.
- W3211830369 cites W2965341826 @default.
- W3211830369 cites W2965399951 @default.
- W3211830369 cites W2968149264 @default.
- W3211830369 cites W2970903767 @default.
- W3211830369 cites W2971598376 @default.
- W3211830369 cites W2978699164 @default.
- W3211830369 cites W2985061404 @default.
- W3211830369 cites W2986755220 @default.
- W3211830369 cites W2992716901 @default.
- W3211830369 cites W2999301586 @default.
- W3211830369 cites W3004349648 @default.
- W3211830369 cites W3006512888 @default.
- W3211830369 cites W3006643426 @default.
- W3211830369 cites W3008862053 @default.
- W3211830369 cites W3011667710 @default.
- W3211830369 cites W3012413020 @default.
- W3211830369 cites W3012918605 @default.
- W3211830369 cites W3015741275 @default.
- W3211830369 cites W3016246792 @default.
- W3211830369 cites W3017152929 @default.
- W3211830369 cites W3019262619 @default.
- W3211830369 cites W3035251962 @default.
- W3211830369 cites W3037471945 @default.
- W3211830369 cites W3047104333 @default.
- W3211830369 cites W3047312226 @default.
- W3211830369 cites W3082320588 @default.
- W3211830369 cites W3109305417 @default.
- W3211830369 cites W3109493217 @default.
- W3211830369 cites W3111499798 @default.
- W3211830369 cites W3111885788 @default.
- W3211830369 cites W3114450627 @default.
- W3211830369 cites W3118230956 @default.
- W3211830369 cites W3122846486 @default.
- W3211830369 cites W3123684968 @default.
- W3211830369 cites W3127786530 @default.
- W3211830369 cites W3130869292 @default.
- W3211830369 cites W3152787073 @default.
- W3211830369 cites W3155413563 @default.
- W3211830369 cites W3159040448 @default.
- W3211830369 cites W3160036209 @default.
- W3211830369 cites W3161224652 @default.
- W3211830369 cites W3161818956 @default.
- W3211830369 cites W3162001942 @default.
- W3211830369 cites W3162073532 @default.
- W3211830369 cites W3162620739 @default.
- W3211830369 cites W3162881616 @default.
- W3211830369 cites W3173386267 @default.
- W3211830369 cites W3177008180 @default.
- W3211830369 cites W3187064824 @default.
- W3211830369 cites W3199434555 @default.
- W3211830369 cites W3212093355 @default.
- W3211830369 cites W3213116167 @default.
- W3211830369 cites W4210257598 @default.
- W3211830369 doi "https://doi.org/10.1109/ojcoms.2021.3128637" @default.
- W3211830369 hasPublicationYear "2021" @default.
- W3211830369 type Work @default.
- W3211830369 sameAs 3211830369 @default.
- W3211830369 citedByCount "31" @default.
- W3211830369 countsByYear W32118303692022 @default.
- W3211830369 countsByYear W32118303692023 @default.
- W3211830369 crossrefType "journal-article" @default.
- W3211830369 hasAuthorship W3211830369A5014343967 @default.
- W3211830369 hasAuthorship W3211830369A5046019676 @default.
- W3211830369 hasAuthorship W3211830369A5056225611 @default.
- W3211830369 hasAuthorship W3211830369A5057209439 @default.
- W3211830369 hasAuthorship W3211830369A5069049205 @default.
- W3211830369 hasAuthorship W3211830369A5085579919 @default.
- W3211830369 hasAuthorship W3211830369A5089676168 @default.
- W3211830369 hasBestOaLocation W32118303691 @default.
- W3211830369 hasConcept C108037233 @default.
- W3211830369 hasConcept C120314980 @default.