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fbtwitterlinkedinvimeoflicker grey 14rssslideshare1
Raisanen, Larry.
Languages: English
Types: Doctoral thesis
Subjects: QA75
Although considerable effort has been placed on developing techniques and algo rithms to create feasible cell plans, much less effort has been placed on understanding the relationship between variables and objectives. The purpose of this thesis is to improve the body of knowledge aimed at understanding the trade-offs and tensions in the selection of transmission sites and in the configuration of macro-cells for GSM and related FDMA wireless systems. The work begins by using an abstract 2-dimensional (2D) model for area coverage. A multiple objective optimisation framework is de veloped to optimise the sequential placement and configuration of downlink wireless cells. This is deployed using a range of evolutionary algorithms whose performance is compared. The framework is further tuned via a decoding mechanisms using the best performing evolutionary algorithm. The relationship between primary variables in the 2D model is analysed in detail. To improve realism, the thesis additionally addresses complexities relating to planning in 3-dimensional (3D) environments. A detailed open source static model is developed and the optimisation framework is extended to accommodate the additional model complexities and choices in algorithm design are compared. Finally, sensitivity analysis is performed to determine the relationship between objectives in the 3D model and benchmark solutions are provided.
  • The results below are discovered through our pilot algorithms. Let us know how we are doing!

    • 4.15 Analysis by selected a and /? values of the weak-domination of PMCOS over S p f a ..................................................................................................
    • 3.2 Power settings used in t e s t s ......................................................................
    • 3.3 The ave. set coverage values obtained in each problem class, for all pairwise comparisons of a lg o r ith m s ........................................................
    • 3.4 Ave. spacing values by algorithm for each test problem c l a s s .............
    • 3.5 Ave. speed of execution in s e c o n d s .........................................................
    • 3.6 Comparison of intermediate populations for each algorithm, using the set coverage metric for a total of 1500 g en eratio n s...............................
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