Multi-Sequence Spreading Random Access (MSRA) for Compressive Sensing-Based Grant-Free Communication
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Abebe, Ameha Tsegaye | - |
dc.contributor.author | Kang, Chung G. | - |
dc.date.accessioned | 2022-02-15T10:41:45Z | - |
dc.date.available | 2022-02-15T10:41:45Z | - |
dc.date.created | 2022-02-08 | - |
dc.date.issued | 2021-11 | - |
dc.identifier.issn | 0090-6778 | - |
dc.identifier.uri | https://scholar.korea.ac.kr/handle/2021.sw.korea/135851 | - |
dc.description.abstract | The performance of grant-free random access (GF-RA) is limited by the number of accessible random access resources (RRs) due to the absence of collision resolution. Compressive sensing (CS)-based RA schemes scale up the RRs at the expense of increased non-orthogonality among transmitted signals. This paper presents the design of multi-sequence spreading random access (MSRA) which employs multiple spreading sequences to spread the different symbols of a user as opposed to the conventional schemes in which a user employs the same spreading sequence for each symbol. We show that MSRA provides code diversity, enabling the multi-user detection (MUD) to be modeled into a well-conditioned multiple measurement vectors (MMVs) CS problem. The code diversity is quantified by the decrease in the average Babel mutual coherence among the spreading sequences. Moreover, we present a two-stage active user detection (AUD) scheme for both wideband and narrowband implementations. Our theoretical analysis shows that with MSRA activity misdetection falls exponentially while the size of GF-RA frame is increased. Finally, the simulation results show that about 82% increase in utilization of RRs, i.e., more active users, is supported by MSRA than the conventional schemes while achieving the RA failure rate lower bound set by random access collision. | - |
dc.language | English | - |
dc.language.iso | en | - |
dc.publisher | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | - |
dc.title | Multi-Sequence Spreading Random Access (MSRA) for Compressive Sensing-Based Grant-Free Communication | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kang, Chung G. | - |
dc.identifier.doi | 10.1109/TCOMM.2021.3103542 | - |
dc.identifier.scopusid | 2-s2.0-85120487622 | - |
dc.identifier.wosid | 000719563500033 | - |
dc.identifier.bibliographicCitation | IEEE TRANSACTIONS ON COMMUNICATIONS, v.69, no.11, pp.7531 - 7543 | - |
dc.relation.isPartOf | IEEE TRANSACTIONS ON COMMUNICATIONS | - |
dc.citation.title | IEEE TRANSACTIONS ON COMMUNICATIONS | - |
dc.citation.volume | 69 | - |
dc.citation.number | 11 | - |
dc.citation.startPage | 7531 | - |
dc.citation.endPage | 7543 | - |
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.keywordAuthor | Channel estimation | - |
dc.subject.keywordAuthor | Coherence | - |
dc.subject.keywordAuthor | Compressive sensing | - |
dc.subject.keywordAuthor | Data communication | - |
dc.subject.keywordAuthor | Multiuser detection | - |
dc.subject.keywordAuthor | NOMA | - |
dc.subject.keywordAuthor | Narrowband | - |
dc.subject.keywordAuthor | Wideband | - |
dc.subject.keywordAuthor | grant-free random access | - |
dc.subject.keywordAuthor | machine-type communication | - |
dc.subject.keywordAuthor | multiple measurement vector (MMV) | - |
dc.subject.keywordAuthor | multiple-sequence spreading random access (MSRA) | - |
dc.subject.keywordAuthor | non-orthogonal multiple access (NOMA) | - |
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.