Comparison of Particle Swarm Optimization and Genetic Algorithm for the Path Loss Reduction in an Urban Area

In this paper, we use the shooting and bouncing ray/image (SBR/Image) method to compute the path loss for different outdoor environments in the commercial area of Taipei. Three types of antenna arrays such as L shape, Y shape, and circular shape arrays are used in the base station and their corresponding path loss on several routes in the outdoor environment are calculated. Moreover, the genetic algorithm (GA) and particle swarm optimization algorithm (PSO) are employed to optimize the excitation voltages and phases for these antenna arrays to reduce the path loss. The GA and PSO optimization is applied to a high order nonlinear optimization problem. As such the chosen optimization problem for a direct algebraic solution exists. By the obtained antenna patterns, we can know the route with the lowest path loss; meanwhile, transmission power using this route in the base station can be reduced. Numerical results show that the performance in reduction of path loss by PSO algorithm is better than that by GA for these antenna arrays. The investigated results can help communication engineers improve their planning and design of outdoor communication system.