Please use this identifier to cite or link to this item: http://hdl.handle.net/10321/1187
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dc.contributor.advisorOlugbara, Oludayo O.-
dc.contributor.advisorOwolawi, P. A.-
dc.contributor.authorElujide, Israel Oludayo-
dc.date.accessioned2015-01-15T10:48:58Z-
dc.date.available2015-01-15T10:48:58Z-
dc.date.issued2015-01-15-
dc.identifier.other618429-
dc.identifier.urihttp://hdl.handle.net/10321/1187-
dc.descriptionSubmitted in fulfillment of the requirements of the Master of Technology Degree in Information Technology, Durban University of Technology, Durban, South Africa, 2014.en_US
dc.description.abstractThis dissertation reports on handover in downlink Long Term Evolution (LTE) networks. The LTE is seen as the technology that will bring about Fourth Generation (4G) mobile broadband experience. The necessity to maintain quality of service for delay sensitive data services and applications used by mobile users makes mobility and handover between base stations in the downlink LTE very critical. Unfortunately, several handover schemes in LTE are based on Reference Symbols Received Power (RSRP) which include measurement error due to limited symbols in downlink packets. However, prompt and precise handover decision cannot be based on inaccurate measurement. Therefore, the downlink LTE intra-system handover is studied with focus on user measurement report. The study centers on preparation stage of the LTE handover procedure. Two different types of physical layer filtering technique namely linear averaging and local averaging are focused upon among others investigated. The performance of LTE conventional physical layer filtering technique, linear filtering, is compared with an alternative technique called local averaging. The output of each physical layer filtering is then used for LTE standardized radio resource layer filtering (otherwise called L3 filtering). The analysis of results from handover decision is based on simulations performed in an LTE system-level simulator. The performance metrics for the results are evaluated in terms of overall system and mobility-related performance. The system performance is based on spectral efficiency and throughput while mobility-related performance is based on handover failure. The performance comparison of the results shows that local averaging technique provides improved system performance of about 51.2 % for spectral efficiency and 42.8% cell-edge throughput for high speed users. Local averaging also produces a reduction of about 26.95% in average number of handover failure when L 3 filtering is applied for low speed mobile terminal. This result confirms that both averaging techniques are suitable for LTE network. Moreover, in the case of high mobility local averaging tends to be better than linear averaging.en_US
dc.format.extent80 pen_US
dc.language.isoenen_US
dc.subject.lcshLong-Term Evolution (Telecommunications)--South Africaen_US
dc.subject.lcshMobile communication systems--Technological innovations--South Africaen_US
dc.subject.lcshWireless communication systems--Technological innovations--South Africaen_US
dc.titleAnalysis of handover decision making in downlink Long Term Evolution networksen_US
dc.typeThesisen_US
dc.description.levelMen_US
item.languageiso639-1other-
item.fulltextWith Fulltext-
item.grantfulltextopen-
Appears in Collections:Theses and dissertations (Accounting and Informatics)
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