Zadoff-Chu Sequence Based Signature Identification for OFDM
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Lee, Kilbom | - |
dc.contributor.author | Kim, Joonsuk | - |
dc.contributor.author | Jung, Jaehoon | - |
dc.contributor.author | Lee, Inkyu | - |
dc.date.accessioned | 2021-09-05T20:30:40Z | - |
dc.date.available | 2021-09-05T20:30:40Z | - |
dc.date.created | 2021-06-15 | - |
dc.date.issued | 2013-10 | - |
dc.identifier.issn | 1536-1276 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/101951 | - |
dc.description.abstract | A signature identification algorithm is a method to obtain the cell identification information for wireless cellular systems or determine the intended user for wireless local area network. In this paper, we propose a simple and efficient signature identification algorithm on the basis of Zadoff-Chu sequence in orthogonal frequency division multiplexing systems. In addition, we prove that the proposed algorithm achieves a maximum likelihood solution if the receiver knows the channel length. Also, the exact probabilities of signature identification failures of the proposed algorithm are provided for different power delay profiles. To demonstrate efficacy of the proposed algorithm in fading channels, we derive the failure probability at high signal-to-noise ratio (SNR). Through a high SNR expression, it is shown that the proposed algorithm fully exploits frequency selective fadings. Especially, we reveal that the slope of the failure probability curves at high SNR is determined by the channel length regardless of power delay profiles. Simulation results show that the proposed algorithm outperforms conventional signature algorithms in frequency selective fading channels. Also, we confirm that our analysis matches well with the empirical results of the proposed signature identification algorithm. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.subject | FREQUENCY-OFFSET ESTIMATION | - |
dc.subject | FADING CHANNELS | - |
dc.subject | SYSTEMS | - |
dc.subject | PERFORMANCE | - |
dc.subject | ESTIMATOR | - |
dc.title | Zadoff-Chu Sequence Based Signature Identification for OFDM | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Lee, Inkyu | - |
dc.identifier.doi | 10.1109/TWC.2013.092013.121533 | - |
dc.identifier.scopusid | 2-s2.0-84890119344 | - |
dc.identifier.wosid | 000327729000011 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS, v.12, no.10, pp.4932 - 4942 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS | - |
dc.citation.title | IEEE TRANSACTIONS ON WIRELESS COMMUNICATIONS | - |
dc.citation.volume | 12 | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 4932 | - |
dc.citation.endPage | 4942 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.journalRegisteredClass | scie | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Engineering | - |
dc.relation.journalResearchArea | Telecommunications | - |
dc.relation.journalWebOfScienceCategory | Engineering, Electrical & Electronic | - |
dc.relation.journalWebOfScienceCategory | Telecommunications | - |
dc.subject.keywordPlus | FREQUENCY-OFFSET ESTIMATION | - |
dc.subject.keywordPlus | FADING CHANNELS | - |
dc.subject.keywordPlus | SYSTEMS | - |
dc.subject.keywordPlus | PERFORMANCE | - |
dc.subject.keywordPlus | ESTIMATOR | - |
dc.subject.keywordAuthor | OFDM | - |
dc.subject.keywordAuthor | Chu sequence | - |
dc.subject.keywordAuthor | cell identification | - |
Items in ScholarWorks are protected by copyright, with all rights reserved, unless otherwise indicated.
(02841) 서울특별시 성북구 안암로 14502-3290-1114
COPYRIGHT © 2021 Korea University. All Rights Reserved.
Certain data included herein are derived from the © Web of Science of Clarivate Analytics. All rights reserved.
You may not copy or re-distribute this material in whole or in part without the prior written consent of Clarivate Analytics.