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dc.contributor.authorLin, Kate Ching-Juen_US
dc.contributor.authorShen, Wei-Liangen_US
dc.contributor.authorChen, Ming-Syanen_US
dc.contributor.authorTan, Kunen_US
dc.date.accessioned2018-08-21T05:54:12Z-
dc.date.available2018-08-21T05:54:12Z-
dc.date.issued2017-06-01en_US
dc.identifier.issn1063-6692en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TNET.2017.2671742en_US
dc.identifier.urihttp://hdl.handle.net/11536/145664-
dc.description.abstractRecent advances have demonstrated the potential of network MIMO (netMIMO), which combines a practical number of distributed antennas as a virtual netMIMO AP (nAP) to improve spatial multiplexing of an WLAN. Existing solutions, however, either simply cluster nearby antennas as static nAPs, or dynamically cluster antennas on a per-packet basis so as to maximize the sum rate of the scheduled clients. To strike the balance between the above two extremes, in this paper, we present the design, implementation and evaluation of FlexNEMO, a practical two-phase netMIMO clustering system. Unlike previous perpacket clustering approaches, FlexNEMO only clusters antennas when client distribution and traffic pattern change, as a result being more practical to be implemented. A medium access control protocol customized for uplink transmissions is then designed to allow the clients at the center of nAPs to have a higher probability to gain uplink access opportunities, but still ensure long-term fairness among clients. By combining on-demand clustering and priority-based access control, FlexNEMO not only improves antenna utilization, but also optimizes the channel condition for every individual client. We evaluated our design via both test bed experiments on USRPs and trace-driven emulations. The results demonstrate that FlexNEMO can deliver 94.7% and 93.7% throughput gains over static antenna clustering in a 4-antenna test bed and 16-antenna emulation, respectively.en_US
dc.language.isoen_USen_US
dc.subjectMIMOen_US
dc.subjectwireless LANen_US
dc.titleUser-Centric Network MIMO With Dynamic Clusteringen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TNET.2017.2671742en_US
dc.identifier.journalIEEE-ACM TRANSACTIONS ON NETWORKINGen_US
dc.citation.volume25en_US
dc.citation.spage1910en_US
dc.citation.epage1923en_US
dc.contributor.department資訊工程學系zh_TW
dc.contributor.departmentDepartment of Computer Scienceen_US
dc.identifier.wosnumberWOS:000403825400045en_US
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