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dc.contributor.author박상규-
dc.date.accessioned2016-06-21T04:58:11Z-
dc.date.available2016-06-21T04:58:11Z-
dc.date.issued2015-02-
dc.identifier.citationJournal of Knowledge Information Technology and Systems, v. 10, NO 1, Page. 103-112en_US
dc.identifier.issn1975-7700-
dc.identifier.urihttp://www.kkits.or.kr/pds/2015/2015-10-1-10.pdf?PHPSESSID=098b037b74987be68a635f64b91ccd23-
dc.identifier.urihttp://hdl.handle.net/20.500.11754/21808-
dc.description.abstractThis paper newly proposed a channel element relocation which can reduces multiplication complexity of ML by applying cholesky decomposition. In wireless communication, maximum likelihood(ML) detection scheme that shows the best bit error rate(BER) performance is usually used; however, a huge amount of multiplication complexity has been pointed out as a default. To lower multiplication complexity of ML detection scheme, various methods have been proposed. Among of them, QRM-MLD algorithm which uses QR decomposition was proposed. The QRM-MLD algorithm maintains the optimal BER performance of ML and reduces the huge amount of multiplication complexity of ML detection. But, QR decomposition shows a huge increase according to augmentation of a number of antennas because of amount of complexity of decomposition process of QR decomposition. For this reason, cholesky decomposition which has low complexity on decomposition process was proposed. Cholesky decomposition does not have high complexity on decomposition process but show reduced complexity than QR decomposition when a number of antennas increase. However, despite reduced complexity, there is a need of additional decrease of ML complexity. To satisfy the need, this paper proposes channel element relocation which applies to Cholesky decomposition and shows additional complexity reduction. Comparision with proposed method and QRM-MLD and conventional Cholesky decomposition shows that proposed method has low complexity. 본 논문은 채널원소 재배치를 Cholesky 분해에 적 용하여 ML검출기법의 감소된 복잡도를 제안하고 있 다. ML검출기법이 가지는 높은 복잡도를 낮추기 위해 제안된 방법 중 Cholesky 분해를 적용하는 방법이 있 다. 본 논문에서 제안하는 방법은 Cholesky 분해를 적 용하기 전 채널 행렬의 원소를 행과 열에 따라 새로 이 정렬하는 방법으로 간단한 방법을 통해 기존에 방 식과 대비했을 때 많은 복잡도를 감소시킬 수 있다는 장점이 있다. 또한 복잡도를 크게 감소시키는 동시에 ML 검출기법의 BER을 그대로 유지할 수 있다는 장점 이 있다. 본 논문에서는 ML 검출기법와 QRM-MLD 검 출기법과 제안하는 방법의 복잡도와 BER을 비교하여 성능을 분석할 것이다.en_US
dc.language.isoko_KRen_US
dc.publisher한국지식정보기술학회 (KKITS)en_US
dc.subjectMIMOen_US
dc.subjectML detectionsen_US
dc.subjectcomplexitiesen_US
dc.subjectQRM-MLDen_US
dc.subjectCholesky decompositionen_US
dc.titleImproved Cholesky Decomposition using Channel Element Relocation for MIMO Systemsen_US
dc.title.alternative채널 원소 재배치를 이용한 향상된 기법의 Cholesky 분해기법en_US
dc.typeArticleen_US
dc.relation.no1-
dc.relation.volume10-
dc.relation.page103-112-
dc.relation.journal한국지식정보기술학회 논문지-
dc.relation.code2015041354-
dc.sector.campusS-
dc.sector.daehakCOLLEGE OF ENGINEERING[S]-
dc.sector.departmentDEPARTMENT OF ELECTRONIC ENGINEERING-
dc.identifier.pidskpark-
Appears in Collections:
COLLEGE OF ENGINEERING[S](공과대학) > ELECTRONIC ENGINEERING(융합전자공학부) > Articles
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