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dc.contributor.authorChung, Wen-Chingen_US
dc.contributor.authorChang, Chung-Juen_US
dc.contributor.authorFeng, Kai-Tenen_US
dc.contributor.authorChen, Ying-Yuen_US
dc.date.accessioned2014-12-08T15:23:08Z-
dc.date.available2014-12-08T15:23:08Z-
dc.date.issued2012-07-01en_US
dc.identifier.issn1536-1233en_US
dc.identifier.urihttp://hdl.handle.net/11536/16261-
dc.description.abstractIn this paper, we propose a fuzzy Q-learning-based MIMO configuration mode and MCS level (FQL-MOMS) selection scheme for high speed packet access evolution (HSPA(+)) systems. The FQL-MOMS selection scheme intends to enhance the system throughput under the block error rate (BLER) requirement guarantee. It will determine an appropriate MIMO configuration mode and MCS (modulation and coding scheme) level for packet data transmission in HSPA(+) systems, under the situations that the channel status is varying and the channel quality indication (CQI) has report delay. The FQL-MOMS scheme considers not only the reported CQI and the last transmission result but also the BLER performance metric and the transmission efficiency. Moreover, it is effectively configured, where the fuzzy rules and the reinforcement signals for the Q-learning algorithm are sophisticatedly designed. Simulation results show that the proposed FQL-MOMS scheme increases the system throughput by up to 49.3 and 35.9 percent, compared to the conventional adaptive threshold selection (ATS) scheme [12] and the Q-HARQ scheme [14], respectively, under the BLER requirement fulfillment.en_US
dc.language.isoen_USen_US
dc.subjectHSPA(+)en_US
dc.subjectMIMOen_US
dc.subjectMCSen_US
dc.subjectHARQen_US
dc.subjectBLERen_US
dc.subjectfuzzy logicen_US
dc.subjectQ-learningen_US
dc.titleAn MIMO Configuration Mode and MCS Level Selection Scheme by Fuzzy Q-Learning for HSPA(+) Systemsen_US
dc.typeArticleen_US
dc.identifier.journalIEEE TRANSACTIONS ON MOBILE COMPUTINGen_US
dc.citation.volume11en_US
dc.citation.issue7en_US
dc.citation.epage1151en_US
dc.contributor.department電機工程學系zh_TW
dc.contributor.departmentDepartment of Electrical and Computer Engineeringen_US
dc.identifier.wosnumberWOS:000304148900007-
dc.citation.woscount0-
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