Base station placement of gsm cellular network in static and dynamic traffic demand using evolutionary multiobjective optimization algorithm

Abstract

Every cellular organization desires to achieve the seamless connectivity and maximum coverage through proper base stations placement All the required design variables of BS such as x y coordinates power height and tilt as well as multiple objectives such as maximization of coverage and minimization of cost with traffic demand overlap and hand over constraints are considered A Modified Nondominated Sorting Genetic Algorithm II MNSGA II is proposed for maintaining appreciable horizontal and vertical diversities by introducing control elitism and dynamic crowding distance operators to solve this multiobjective BS problem In this thesis the synthetic test systems as well as the physical and geometrical structure of real propagation environments are considered under static and dynamic traffic demand Three case studies have been carried out for BS placement using MNSGA II In the first work all the necessary design variables of BS placement are determined using NSGA II and MNSGA II for a 15 15 Km2 synthetic test system The proposed MNSGA II produces better Pareto front than NSGA II with good vertical and horizontal diversity The effect of function evaluations overlap and handover is analyzed for this problem The second work analyses the suitable path loss model validation of existing BS locations and additional BS location to improve the coverage for the real propagation environment of an urban area with static traffic demand newline