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dc.contributor.authorHuang, Chiao-Yinen_US
dc.contributor.authorChung, Wen-Chingen_US
dc.contributor.authorChang, Chung-Juen_US
dc.contributor.authorRen, Fang-Chingen_US
dc.date.accessioned2014-12-08T15:20:45Z-
dc.date.available2014-12-08T15:20:45Z-
dc.date.issued2009en_US
dc.identifier.isbn978-1-4244-2514-3en_US
dc.identifier.issn1090-3038en_US
dc.identifier.urihttp://hdl.handle.net/11536/14765-
dc.description.abstractIn this paper, a fuzzy Q-learning-based hybrid automatic repeat request (FQL-HARQ) scheme is proposed to enhance the system performance of high speed downlink packet access (HSDPA) in universal mobile telecommunications system (UMTS). In the HSDPA system, it is an important issue to choose modulation and coding scheme (MCS) for new data packet when channel quality indicator (CQI) is inaccurate. Hence, the purpose of the FQL-HARQ scheme is to determine a suitable MCS for new data packet so as to maximize the system throughput while guarantee the block error rate (BLER) requirement. In the FQL-HARQ scheme, the fuzzy logic is used to choose a suitable MCS for each new data packet. According to the feedback information from the HSDPA system, the Q-learning algorithm is adopted to update fuzzy rule base. This makes the FQL-HARQ scheme can adapt to the variation of environment. Simulation results show that the proposed scheme can increase the system throughput of up to 70 % compared to the conventional adaptive method in the case with CQI report delay.en_US
dc.language.isoen_USen_US
dc.titleFuzzy Q-Learning-based Hybrid ARQ for High Speed Downlink Packet Accessen_US
dc.typeArticleen_US
dc.identifier.journal2009 IEEE 70TH VEHICULAR TECHNOLOGY CONFERENCE FALL, VOLS 1-4en_US
dc.citation.spage1822en_US
dc.citation.epage1825en_US
dc.contributor.department電信工程研究所zh_TW
dc.contributor.departmentInstitute of Communications Engineeringen_US
dc.identifier.wosnumberWOS:000280580400369-
Appears in Collections:Conferences Paper