Detail View

Intelligent Channel Impulse Response Feature Prediction in Underwater Acoustic Networks
Citations

WEB OF SCIENCE

Citations

SCOPUS

Metadata Downloads

DC Field Value Language
dc.contributor.author Yun, Sinwoong -
dc.contributor.author Lee, Jemin -
dc.date.accessioned 2025-02-21T16:10:23Z -
dc.date.available 2025-02-21T16:10:23Z -
dc.date.created 2025-02-20 -
dc.date.issued 2024-10-16 -
dc.identifier.isbn 9798350364637 -
dc.identifier.issn 2162-1241 -
dc.identifier.uri http://hdl.handle.net/20.500.11750/57921 -
dc.description.abstract In this paper, we develop an intelligent channel im-pulse response (CIR) feature prediction algorithm in underwater networks. To this end, we first extract the major features, i.e., CIR values and tap distances, from raw CIR. Then, we implement a feature prediction module by adopting the time-series forecasting learning algorithm. Through the simulation results, we verify the prediction accuracy of the proposed algorithm with the normalized mean square error (NMSE) loss curve. © 2024 IEEE. -
dc.language English -
dc.publisher IEEE Computer Society -
dc.relation.ispartof International Conference on ICT Convergence -
dc.title Intelligent Channel Impulse Response Feature Prediction in Underwater Acoustic Networks -
dc.type Conference Paper -
dc.identifier.doi 10.1109/ICTC62082.2024.10827287 -
dc.identifier.scopusid 2-s2.0-85217715977 -
dc.identifier.bibliographicCitation Yun, Sinwoong. (2024-10-16). Intelligent Channel Impulse Response Feature Prediction in Underwater Acoustic Networks. 15th International Conference on Information and Communication Technology Convergence, ICTC 2024, 362–363. doi: 10.1109/ICTC62082.2024.10827287 -
dc.identifier.url https://2024.ictc.org/program_proceeding -
dc.citation.conferenceDate 2024-10-16 -
dc.citation.conferencePlace KO -
dc.citation.conferencePlace 제주 -
dc.citation.endPage 363 -
dc.citation.startPage 362 -
dc.citation.title 15th International Conference on Information and Communication Technology Convergence, ICTC 2024 -
Show Simple Item Record

File Downloads

  • There are no files associated with this item.

공유

qrcode
공유하기

Total Views & Downloads