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Coverage, Capacity and Load Balance Optimization in Mobile Networks

Yaghoobianzadeh Sardroudi, Amir Mohammad | 2022

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  1. Type of Document: M.Sc. Thesis
  2. Language: Farsi
  3. Document No: 55281 (05)
  4. University: Sharif University of Technology
  5. Department: Electrical Engineering
  6. Advisor(s): Hossein Khalaj, Babak
  7. Abstract:
  8. For several years, self-organizing networks have been introduced by 3GPP to reduce the costs of mobile operators. Self-organizing networks, by introducing a kind of intelligence to the mobile network, will cause optimal performance and, as a result, reduce the operating costs of operators. Improving network coverage and increasing user data rates are always among the priorities of operators to increase profits and customer satisfaction. Coverage and capacity optimization is one of the most important functions introduced in self-organized networks. In this study, in addition to the coverage and capacity optimization function, the load balance optimization and the contradictory interaction of these two problems have also been investigated. Based on the graph representation of the mobile network, an intelligent clustering method has been presented, and through this cell clustering, optimization has been made possible in large networks. The algorithm will converge faster to the near global optimal settings by using this clustering method. Also, an agile and stable hybrid structure is introduced for implementing functions in a real mobile network. The effectiveness of the proposed formulation for the problem is shown in comparison with the existing methods. Also, a mechanism for detecting changes in the environment has been used to avoid loss of network performance
  9. Keywords:
  10. Load Balancing ; Machine Learning ; Genetic Algorithm ; Network Capacity Optimization ; Self Organizing Networks ; Network Coverage Optimization

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