Matches in SemOpenAlex for { <https://semopenalex.org/work/W4385078953> ?p ?o ?g. }
Showing items 1 to 84 of
84
with 100 items per page.
- W4385078953 abstract "With today’s proliferation of IoT and real-time applications, it has become crucial to properly handle traffic, optimize the quality-of-service (QoS) of wireless networks and design novel approaches to enable reliable communications with bounded latency and high throughput for future wireless services. In order to meet these stringent QoS requirements, there has been a recent surge in research that investigates a deep restructuring of the Radio Access Network (RAN). In particular, the open radio access network (O-RAN) framework promises to deliver flexible, scalable, and agile solutions for improving the handover process of a moving user equipment (UE), by considering factors related to the requirements of applications in terms of QoS, traffic load, signal quality and the diversity of multiple access technologies or radio frequencies of the environment. Building on this basis, this paper investigates the handover process of a moving vehicle, by exploring and comparing the prediction accuracy results of different machine learning (ML) techniques used for anomaly detection. In particular, the structure of one of the O-RAN modules is presented. This module relates to a traffic steering application, specifically designed and used to detect anomalies within the network. Several ML techniques are then implemented in the O-RAN traffic steering module to predict the handover. The results pertaining to the comparison of the implemented ML techniques show that the random forest algorithm gives the highest accuracy (up to 98%), which helps boosting the handover process." @default.
- W4385078953 created "2023-07-23" @default.
- W4385078953 creator A5019615104 @default.
- W4385078953 creator A5024108653 @default.
- W4385078953 creator A5057382530 @default.
- W4385078953 creator A5067656073 @default.
- W4385078953 creator A5075661449 @default.
- W4385078953 date "2023-06-19" @default.
- W4385078953 modified "2023-10-03" @default.
- W4385078953 title "Benchmarking of Anomaly Detection Techniques in O-RAN for Handover Optimization" @default.
- W4385078953 cites W2340607872 @default.
- W4385078953 cites W2794839070 @default.
- W4385078953 cites W2975688759 @default.
- W4385078953 cites W2981096252 @default.
- W4385078953 cites W3012871996 @default.
- W4385078953 cites W3025372446 @default.
- W4385078953 cites W3104330751 @default.
- W4385078953 cites W3133548791 @default.
- W4385078953 cites W3133655841 @default.
- W4385078953 cites W3134779518 @default.
- W4385078953 cites W3217596786 @default.
- W4385078953 doi "https://doi.org/10.1109/iwcmc58020.2023.10183347" @default.
- W4385078953 hasPublicationYear "2023" @default.
- W4385078953 type Work @default.
- W4385078953 citedByCount "0" @default.
- W4385078953 crossrefType "proceedings-article" @default.
- W4385078953 hasAuthorship W4385078953A5019615104 @default.
- W4385078953 hasAuthorship W4385078953A5024108653 @default.
- W4385078953 hasAuthorship W4385078953A5057382530 @default.
- W4385078953 hasAuthorship W4385078953A5067656073 @default.
- W4385078953 hasAuthorship W4385078953A5075661449 @default.
- W4385078953 hasConcept C106365562 @default.
- W4385078953 hasConcept C108037233 @default.
- W4385078953 hasConcept C111852164 @default.
- W4385078953 hasConcept C153646914 @default.
- W4385078953 hasConcept C154945302 @default.
- W4385078953 hasConcept C207029474 @default.
- W4385078953 hasConcept C2780137118 @default.
- W4385078953 hasConcept C2781327853 @default.
- W4385078953 hasConcept C31258907 @default.
- W4385078953 hasConcept C41008148 @default.
- W4385078953 hasConcept C5119721 @default.
- W4385078953 hasConcept C555944384 @default.
- W4385078953 hasConcept C62793504 @default.
- W4385078953 hasConcept C68649174 @default.
- W4385078953 hasConcept C739882 @default.
- W4385078953 hasConcept C76155785 @default.
- W4385078953 hasConcept C79403827 @default.
- W4385078953 hasConcept C85608190 @default.
- W4385078953 hasConceptScore W4385078953C106365562 @default.
- W4385078953 hasConceptScore W4385078953C108037233 @default.
- W4385078953 hasConceptScore W4385078953C111852164 @default.
- W4385078953 hasConceptScore W4385078953C153646914 @default.
- W4385078953 hasConceptScore W4385078953C154945302 @default.
- W4385078953 hasConceptScore W4385078953C207029474 @default.
- W4385078953 hasConceptScore W4385078953C2780137118 @default.
- W4385078953 hasConceptScore W4385078953C2781327853 @default.
- W4385078953 hasConceptScore W4385078953C31258907 @default.
- W4385078953 hasConceptScore W4385078953C41008148 @default.
- W4385078953 hasConceptScore W4385078953C5119721 @default.
- W4385078953 hasConceptScore W4385078953C555944384 @default.
- W4385078953 hasConceptScore W4385078953C62793504 @default.
- W4385078953 hasConceptScore W4385078953C68649174 @default.
- W4385078953 hasConceptScore W4385078953C739882 @default.
- W4385078953 hasConceptScore W4385078953C76155785 @default.
- W4385078953 hasConceptScore W4385078953C79403827 @default.
- W4385078953 hasConceptScore W4385078953C85608190 @default.
- W4385078953 hasFunder F4320306076 @default.
- W4385078953 hasLocation W43850789531 @default.
- W4385078953 hasOpenAccess W4385078953 @default.
- W4385078953 hasPrimaryLocation W43850789531 @default.
- W4385078953 hasRelatedWork W1992775457 @default.
- W4385078953 hasRelatedWork W2024971392 @default.
- W4385078953 hasRelatedWork W2025382211 @default.
- W4385078953 hasRelatedWork W2099577676 @default.
- W4385078953 hasRelatedWork W2136289544 @default.
- W4385078953 hasRelatedWork W2181941071 @default.
- W4385078953 hasRelatedWork W2547767810 @default.
- W4385078953 hasRelatedWork W3153389218 @default.
- W4385078953 hasRelatedWork W3177617945 @default.
- W4385078953 hasRelatedWork W4385078953 @default.
- W4385078953 isParatext "false" @default.
- W4385078953 isRetracted "false" @default.
- W4385078953 workType "article" @default.