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dc.contributor.authorChen, YSen_US
dc.contributor.authorChang, CJen_US
dc.contributor.authorHsieh, YLen_US
dc.date.accessioned2014-12-08T15:17:38Z-
dc.date.available2014-12-08T15:17:38Z-
dc.date.issued2006-01-01en_US
dc.identifier.issn1536-1276en_US
dc.identifier.urihttp://dx.doi.org/10.1109/TWC.2006.1576521en_US
dc.identifier.urihttp://hdl.handle.net/11536/12782-
dc.description.abstractThis paper proposes a channel effect prediction-based power control scheme using pipeline recurrent neural network (PRNN)/extended recursive least squares (ERLS) for uplinks in direct sequence code division multiple access (DS-CDMA) cellular mobile systems. Conventional signal-to-interference (SIR) prediction-based power control schemes may incur prediction mistakes caused by the adjustment of transmission power. The proposed power control scheme purely tracks the variation of channel effect and, thus, can be immune to any power adjustment. Furthermore, it adopts the PRNN with ERLS for predicting the channel effect. Simulation results show that the channel effect prediction-based power control scheme using PRNN/ERLS achieves a 40% higher system capacity and a lower outage probability than the conventional SIR prediction-based power control scheme using grey prediction method (IEEE Trans. Veh. Technol., Vol. 49, No. 6, p. 2081, 2000).en_US
dc.language.isoen_USen_US
dc.subjectchannel effect predictionen_US
dc.subjectdirect sequence code division multiple access (DS-CDMA)en_US
dc.subjectextended recursive least squares (ERLS)en_US
dc.subjectpower controlen_US
dc.subjectpipeline recurrent neural network (PRNN)en_US
dc.titleA channel effect prediction-based power control scheme using PRNN/ERLS for uplinks in DS-CDMA cellular mobile systemsen_US
dc.typeArticleen_US
dc.identifier.doi10.1109/TWC.2006.1576521en_US
dc.identifier.journalIEEE TRANSACTIONS ON WIRELESS COMMUNICATIONSen_US
dc.citation.volume5en_US
dc.citation.issue1en_US
dc.citation.spage23en_US
dc.citation.epage27en_US
dc.contributor.department交大名義發表zh_TW
dc.contributor.departmentNational Chiao Tung Universityen_US
dc.identifier.wosnumberWOS:000234754100005-
dc.citation.woscount15-
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