Neural networks based physical cell identity: assignment for self organized 3gpp long term evolution

dc.contributor.authorMuhammad Basit Shahab
dc.contributor.authorAbdul Aziz Bhatti
dc.date.accessioned2012-09-05T11:41:40Z
dc.date.available2012-09-05T11:41:40Z
dc.date.issued2012
dc.description.abstractThis paper proposes neural networks based graph coloring technique to assign Physical Cell Identities throughout the self organized 3GPP Long Term Evolution Networks. PCIs are allocated such that no two cells in the vicinity of each other or with a common neighbor get the same identity. Efficiency of proposed methodology resides in the fact that minimum number of identities is utilized in the network wise assignment. Simulations are performed on a very large scale network, where initially all the cells are without any PCIs assigned. Results of simulations are demonstrated to analyze the performance of the proposed techniqueen_US
dc.identifier.citationPaper Presented at 35th International Conference on Telecommunication and Signal Processing, TSP, Prague, Czech Republic 3-4 July, 2012
dc.identifier.isbn978-1-4673-1118-2
dc.identifier.urihttps://escholar.umt.edu.pk/handle/123456789/576
dc.language.isoenen_US
dc.publisherIEEEen_US
dc.subjectPhysical Cell Identityen_US
dc.subjectNeural Networksen_US
dc.subjectSelf Organized Networksen_US
dc.subjectLong Term Evolutionen_US
dc.titleNeural networks based physical cell identity: assignment for self organized 3gpp long term evolutionen_US
dc.typeOtheren_US
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