Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Jin, Xianglan | - |
dc.contributor.author | Jin, Dong-Sup | - |
dc.contributor.author | No, Jong-Seon | - |
dc.contributor.author | Shin, Dong-Joon | - |
dc.date.accessioned | 2022-07-16T18:52:20Z | - |
dc.date.available | 2022-07-16T18:52:20Z | - |
dc.date.created | 2021-05-12 | - |
dc.date.issued | 2011-10 | - |
dc.identifier.issn | 0916-8516 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/167473 | - |
dc.description.abstract | The probability of making mistakes on the decoded signals at the relay has been used for the maximum-likelihood (ML) decision at the receiver in the decode-and-forward (DF) relay network. It is well known that deriving the probability is relatively easy for the uncoded single-antenna transmission with M-pulse amplitude modulation (PAM). However, in the multiplexing multiple-input multiple-output (MIMO) transmission, the multi-dimensional decision region is getting too complicated to derive the probability. In this paper, a high-performance near-ML decoder is devised by applying a well-known pairwise error probability (PEP) of two paired-signals at the relay in the MIMO DF relay network. It also proves that the near-ML decoder can achieve the maximum diversity of M-S M-D + M-R Min(M-S, M-D), where M-S, M-R, and M-D are the number of antennas at the source, relay, and destination, respectively. The simulation results show that 1) the near-ML decoder achieves the diversity we derived and 2) the bit error probability of the near-ML decoder is almost the same as that of the ML decoder. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEICE-INST ELECTRONICS INFORMATION COMMUNICATIONS ENG | - |
dc.title | Diversity Analysis of MIMO Decode-and-Forward Relay Network by Using Near-ML Decoder | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Shin, Dong-Joon | - |
dc.identifier.doi | 10.1587/transcom.E94.B.2828 | - |
dc.identifier.scopusid | 2-s2.0-80053526755 | - |
dc.identifier.wosid | 000295601400016 | - |
dc.identifier.bibliographicCitation | IEICE TRANSACTIONS ON COMMUNICATIONS, v.E94B, no.10, pp.2828 - 2836 | - |
dc.relation.isPartOf | IEICE TRANSACTIONS ON COMMUNICATIONS | - |
dc.citation.title | IEICE TRANSACTIONS ON COMMUNICATIONS | - |
dc.citation.volume | E94B | - |
dc.citation.number | 10 | - |
dc.citation.startPage | 2828 | - |
dc.citation.endPage | 2836 | - |
dc.type.rims | ART | - |
dc.type.docType | Article | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
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 | MAXIMUM-LIKELIHOOD DETECTION | - |
dc.subject.keywordPlus | USER COOPERATION DIVERSITY | - |
dc.subject.keywordPlus | TIME BLOCK-CODES | - |
dc.subject.keywordPlus | PERFORMANCE ANALYSIS | - |
dc.subject.keywordPlus | PROTOCOLS | - |
dc.subject.keywordPlus | CHANNELS | - |
dc.subject.keywordAuthor | decode-and-forward (DF) | - |
dc.subject.keywordAuthor | diversity | - |
dc.subject.keywordAuthor | maximum-likelihood (ML) | - |
dc.subject.keywordAuthor | multiple-input multiple-output (MIMO) | - |
dc.subject.keywordAuthor | pairwise error probability (PEP) | - |
dc.subject.keywordAuthor | relay | - |
dc.identifier.url | https://www.jstage.jst.go.jp/article/transcom/E94.B/10/E94.B_10_2828/_article | - |
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