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Embedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA system

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dc.citedby0
dc.contributor.authorKrishnan P.S.en_US
dc.contributor.authorKiong T.S.en_US
dc.contributor.authorKoh J.en_US
dc.contributor.authorYap D.en_US
dc.contributor.authorid36053261400en_US
dc.contributor.authorid15128307800en_US
dc.contributor.authorid22951210700en_US
dc.contributor.authorid22952562500en_US
dc.date.accessioned2023-12-29T07:57:13Z
dc.date.available2023-12-29T07:57:13Z
dc.date.issued2008
dc.description.abstractGenetic algorithms (GAs) are powerful search techniques that are used successfully to solve problems in many different disciplines. One application would be in WCDMA adaptive beam forming technique. Adaptive antenna has dynamic beam to cater for users' needs and provides better capacity for mobile communication but requires more intelligent and advance beam forming algorithm such as genetic algorithm. Compared to Standard GAs, Parallel Distributed GAs promise substantial gain in terms of convergence performance. In this paper, an embedded parallel and distributed genetic algorithm (EPDGA) with dynamic parameter setting on a multiprocessor system is proposed. The proposed scheme applies a master-slave architecture where the total active unit equipments (UE) are distributed to subpopulations (slaves) that evolve separately and exchange individuals occasionally. The power usage at Node B is used as fitness function to compare the performance of EPDGA and standard GA. Simulation results show that EPDGA converges faster and is better in adaptive antenna beam forming in the aspect of power usage at Node B as compared to standard GA. � 2008 IEEE.en_US
dc.description.natureFinalen_US
dc.identifier.ArtNo4814302
dc.identifier.doi10.1109/NCTT.2008.4814302
dc.identifier.epage361
dc.identifier.scopus2-s2.0-67650159331
dc.identifier.spage356
dc.identifier.urihttps://www.scopus.com/inward/record.uri?eid=2-s2.0-67650159331&doi=10.1109%2fNCTT.2008.4814302&partnerID=40&md5=7827f63fab872eecd53f1e0bcb08d5d6
dc.identifier.urihttps://irepository.uniten.edu.my/handle/123456789/30982
dc.pagecount5
dc.sourceScopus
dc.sourcetitleProceedings of IEEE 2008 6th National Conference on Telecommunication Technologies and IEEE 2008 2nd Malaysia Conference on Photonics, NCTT-MCP 2008
dc.subjectAdaptive beam forming
dc.subjectMaster-slave architecture
dc.subjectParallel distributed genetic algorithm
dc.subjectWCDMA
dc.subjectFunction evaluation
dc.subjectGenetic algorithms
dc.subjectImage storage tubes
dc.subjectInterference suppression
dc.subjectMobile antennas
dc.subjectStandards
dc.subjectAdaptive antenna
dc.subjectAdaptive beam forming
dc.subjectArtificial intelligent
dc.subjectBeamforming algorithms
dc.subjectConvergence performance
dc.subjectDistributed genetic algorithms
dc.subjectDynamic parameters
dc.subjectFitness functions
dc.subjectMaster-slave architecture
dc.subjectMobile communications
dc.subjectMulti processor systems
dc.subjectParallel distributed genetic algorithm
dc.subjectPower usage
dc.subjectSearch technique
dc.subjectSimulation result
dc.subjectW-CDMA system
dc.subjectWCDMA
dc.subjectParallel algorithms
dc.titleEmbedded parallel distributed artificial intelligent processors for adaptive beam forming in WCDMA systemen_US
dc.typeConference paperen_US
dspace.entity.typePublication
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