University of Khartoum

Self-Organizing Networks in Long Term Evolution

Self-Organizing Networks in Long Term Evolution

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Title: Self-Organizing Networks in Long Term Evolution
Author: bashier, Ehsan hussain
Abstract: The latest step being studied and developed in wireless telecommunication system is an evolution of 3G(3rd Generation ) into the 4G which is known as LTE (Long Term Evolution). Along with this evolution, the ability to automate the management processes has emerged as a key technology requirement, thus Self organizing Networks (SON) were introduced as part of the LTE. The achievement of SON depend on the achievement of it is main functionalities, which are self configuration, self optimization, and self healing. The objective of this project is to develop mechanisms for the self configuration and self optimization of the LTE base stations (EnodeB’s). In the first part of the project a solution for enodeB’s self configuration process was developed and implemented successfully using the PHP language. An Auto configuration Server (ACS) was built based on Linux operating system to perform the configuration process. By the completion of the self configuration process, the new enodeB will have been provided with a static IP address and the configuration file that contains the default setting of the configuration parameters. This was done to place the enodeB in the operational state. The model was tested using small LAN. In the second part of the project an algorithm for the coverage and capacity self optimization (CCO) of the enodeB was developed. A code for the algorithm simulation was written using MATLAB. For the Final Part of the work, the general algorithm for the Automatic Neighbor Relation (ANR) was analyzed and simulated by writing a code for it using MATLAB. The self configuration test results showed an enhancement of the system operation performance by reducing the time and efforts required for the enodeBs configuration. The self optimization simulation results showed that by using the CCO & ANR algorithm the system capacity is maximized and failed handover operations are reduced. The proposed solutions had some limitation since it was based on a number of assumptions. These assumptions were made because of the unavailability of live network statistics and information which are very important factors in the design and analysis.
URI: http://khartoumspace.uofk.edu/handle/123456789/18537
Date: 2011-07


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